Index

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _ 
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

a - Variable in class org.tribuo.util.infotheory.impl.CachedTriple
 
ABSOLUTE - Enum constant in enum class org.tribuo.regression.sgd.fm.TrainTest.LossEnum
ABSOLUTE - Enum constant in enum class org.tribuo.regression.sgd.TrainTest.LossEnum
AbsoluteLoss - Class in org.tribuo.regression.sgd.objectives
Absolute loss (i.e., l1).
AbsoluteLoss() - Constructor for class org.tribuo.regression.sgd.objectives.AbsoluteLoss
Constructs an absolute loss.
AbstractCARTTrainer<T extends Output<T>> - Class in org.tribuo.common.tree
Base class for Trainer's that use an approximation of the CART algorithm to build a decision tree.
AbstractCARTTrainer(int, float, float, float, boolean, long) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer
After calls to this superconstructor subclasses must call postConfig().
AbstractCARTTrainer.AbstractCARTTrainerProvenance - Class in org.tribuo.common.tree
Deprecated.
AbstractCARTTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer.AbstractCARTTrainerProvenance
Deprecated.
Deserialization constructor.
AbstractCARTTrainerProvenance(AbstractCARTTrainer<T>) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer.AbstractCARTTrainerProvenance
Deprecated.
Constructs a provenance for the host AbstractCARTTrainer.
AbstractEvaluator<T extends Output<T>,C extends MetricContext<T>,E extends Evaluation<T>,M extends EvaluationMetric<T,C>> - Class in org.tribuo.evaluation
Base class for evaluators.
AbstractEvaluator() - Constructor for class org.tribuo.evaluation.AbstractEvaluator
 
AbstractFMModel<T extends Output<T>> - Class in org.tribuo.common.sgd
A quadratic factorization machine model trained using SGD.
AbstractFMModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, FMParameters, boolean) - Constructor for class org.tribuo.common.sgd.AbstractFMModel
Constructs a factorization machine model trained via SGD.
AbstractFMTrainer<T extends Output<T>,U,V extends AbstractFMModel<T>> - Class in org.tribuo.common.sgd
A trainer for a quadratic factorization machine model which uses SGD.
AbstractFMTrainer() - Constructor for class org.tribuo.common.sgd.AbstractFMTrainer
For olcut.
AbstractFMTrainer(StochasticGradientOptimiser, int, int, int, long, int, double) - Constructor for class org.tribuo.common.sgd.AbstractFMTrainer
Constructs an SGD trainer for a factorization machine.
AbstractLinearSGDModel<T extends Output<T>> - Class in org.tribuo.common.sgd
A linear model trained using SGD.
AbstractLinearSGDModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, LinearParameters, boolean) - Constructor for class org.tribuo.common.sgd.AbstractLinearSGDModel
Constructs a linear model trained via SGD.
AbstractLinearSGDTrainer<T extends Output<T>,U,V extends AbstractLinearSGDModel<T>> - Class in org.tribuo.common.sgd
A trainer for a linear model which uses SGD.
AbstractLinearSGDTrainer() - Constructor for class org.tribuo.common.sgd.AbstractLinearSGDTrainer
For olcut.
AbstractLinearSGDTrainer(StochasticGradientOptimiser, int, int, int, long) - Constructor for class org.tribuo.common.sgd.AbstractLinearSGDTrainer
Constructs an SGD trainer for a linear model.
AbstractSequenceEvaluator<T extends Output<T>,C extends MetricContext<T>,E extends SequenceEvaluation<T>,M extends EvaluationMetric<T,C>> - Class in org.tribuo.sequence
Base class for sequence evaluators.
AbstractSequenceEvaluator() - Constructor for class org.tribuo.sequence.AbstractSequenceEvaluator
 
AbstractSGDModel<T extends Output<T>> - Class in org.tribuo.common.sgd
A model trained using SGD.
AbstractSGDModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, FeedForwardParameters, boolean, boolean) - Constructor for class org.tribuo.common.sgd.AbstractSGDModel
Constructs a linear model trained via SGD.
AbstractSGDModel.PredAndActive - Class in org.tribuo.common.sgd
A nominal tuple used to capture the prediction and the number of active features used by the model.
AbstractSGDTrainer<T extends Output<T>,U,V extends Model<T>,X extends FeedForwardParameters> - Class in org.tribuo.common.sgd
A trainer for a model which uses SGD.
AbstractSGDTrainer(boolean) - Constructor for class org.tribuo.common.sgd.AbstractSGDTrainer
Base constructor called by subclass no-args constructors used by OLCUT.
AbstractSGDTrainer(StochasticGradientOptimiser, int, int, int, long, boolean) - Constructor for class org.tribuo.common.sgd.AbstractSGDTrainer
Constructs an SGD trainer.
AbstractTrainingNode<T extends Output<T>> - Class in org.tribuo.common.tree
Base class for decision tree nodes used at training time.
AbstractTrainingNode(int, int, AbstractTrainingNode.LeafDeterminer) - Constructor for class org.tribuo.common.tree.AbstractTrainingNode
Builds an abstract training node.
AbstractTrainingNode.LeafDeterminer - Class in org.tribuo.common.tree
Contains parameters needed to determine whether a node is a leaf.
accuracy() - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
The overall accuracy of the evaluation.
accuracy() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The accuracy.
accuracy(Label) - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
The per label accuracy of the evaluation.
accuracy(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the accuracy for this label.
accuracy(EvaluationMetric.Average, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the accuracy using the specified average type and confusion matrix.
accuracy(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the accuracy given this confusion matrix.
accuracy(T, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates a per label accuracy given this confusion matrix.
ACCURACY - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The accuracy.
ADABOOST - Enum constant in enum class org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
Creates an AdaBoostTrainer.
AdaBoostTrainer - Class in org.tribuo.classification.ensemble
Implements Adaboost.SAMME one of the more popular algorithms for multiclass boosting.
AdaBoostTrainer(Trainer<Label>, int) - Constructor for class org.tribuo.classification.ensemble.AdaBoostTrainer
Constructs an adaboost trainer using the supplied weak learner trainer and the specified number of boosting rounds.
AdaBoostTrainer(Trainer<Label>, int, long) - Constructor for class org.tribuo.classification.ensemble.AdaBoostTrainer
Constructs an adaboost trainer using the supplied weak learner trainer, the specified number of boosting rounds and the supplied seed.
AdaDelta - Class in org.tribuo.math.optimisers
An implementation of the AdaDelta gradient optimiser.
AdaDelta() - Constructor for class org.tribuo.math.optimisers.AdaDelta
Sets rho to 0.95 and epsilon to 1e-6.
AdaDelta(double) - Constructor for class org.tribuo.math.optimisers.AdaDelta
Keeps rho at 0.95, passes through epsilon.
AdaDelta(double, double) - Constructor for class org.tribuo.math.optimisers.AdaDelta
It's recommended to keep rho at 0.95.
ADADELTA - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The AdaDelta optimiser.
ADADELTA - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
The AdaDelta optimiser.
AdaGrad - Class in org.tribuo.math.optimisers
An implementation of the AdaGrad gradient optimiser.
AdaGrad(double) - Constructor for class org.tribuo.math.optimisers.AdaGrad
Creates an AdaGrad optimiser using the specified initial learning rate.
AdaGrad(double, double) - Constructor for class org.tribuo.math.optimisers.AdaGrad
Creates an AdaGrad optimiser using the specified learning rate and epsilon.
AdaGrad(double, double, double) - Constructor for class org.tribuo.math.optimisers.AdaGrad
Creates an AdaGrad optimiser using the specified learning rate, epsilon and initial accumulator value.
ADAGRAD - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The AdaGrad optimiser.
ADAGRAD - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
The AdaGrad optimiser.
ADAGRADDA - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The AdaGrad Dual Averaging optimiser.
AdaGradRDA - Class in org.tribuo.math.optimisers
An implementation of the AdaGrad gradient optimiser with regularized dual averaging.
AdaGradRDA(double, double) - Constructor for class org.tribuo.math.optimisers.AdaGradRDA
Creates an AdaGradRDA optimiser with the specified parameter values.
AdaGradRDA(double, double, double, double, int) - Constructor for class org.tribuo.math.optimisers.AdaGradRDA
Creates an AdaGradRDA optimiser with the specified parameter values.
ADAGRADRDA - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
The AdaGrad Regularised Dual Averaging optimiser.
Adam - Class in org.tribuo.math.optimisers
An implementation of the Adam gradient optimiser.
Adam() - Constructor for class org.tribuo.math.optimisers.Adam
Sets initialLearningRate to 0.001, betaOne to 0.9, betaTwo to 0.999, epsilon to 1e-6.
Adam(double, double) - Constructor for class org.tribuo.math.optimisers.Adam
Sets betaOne to 0.9 and betaTwo to 0.999
Adam(double, double, double, double) - Constructor for class org.tribuo.math.optimisers.Adam
It's highly recommended not to modify these parameters, use one of the other constructors.
ADAM - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The Adam optimiser.
ADAM - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
The Adam optimiser.
ADAMAX - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The Adamax optimiser.
add - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Adds the specified constant.
add() - Static method in interface org.tribuo.util.Merger
A merger which adds the elements.
add(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that adds the operand to each value.
add(int) - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
Adds an index where the feature value occurs.
add(int, double) - Method in class org.tribuo.math.la.DenseVector
 
add(int, double) - Method in interface org.tribuo.math.la.SGDVector
Adds value to the element at index.
add(int, double) - Method in class org.tribuo.math.la.SparseVector
 
add(int, int, double) - Method in class org.tribuo.math.la.DenseMatrix
 
add(int, int, double) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
add(int, int, double) - Method in interface org.tribuo.math.la.Matrix
Adds the argument value to the value at the supplied index.
add(int, Row<T>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
add(String) - Method in class org.tribuo.impl.BinaryFeaturesExample
Adds a single feature with a value of 1.
add(String, double) - Method in class org.tribuo.impl.ArrayExample
Adds a single feature.
add(String, double) - Method in class org.tribuo.MutableFeatureMap
Adds an occurrence of a feature with a given name.
add(Example<T>) - Method in class org.tribuo.ImmutableDataset
Adds an Example to the dataset, which will remove features with unknown names.
add(Example<T>) - Method in class org.tribuo.MutableDataset
Adds an example to the dataset, which observes the output and each feature value.
add(Example<T>, Merger) - Method in class org.tribuo.ImmutableDataset
Adds a Example to the dataset, which will insert feature ids, remove unknown features and sort the examples by the feature ids (merging duplicate ids).
add(Feature) - Method in class org.tribuo.Example
Adds a feature.
add(Feature) - Method in class org.tribuo.impl.ArrayExample
 
add(Feature) - Method in class org.tribuo.impl.BinaryFeaturesExample
Adds a feature to this example.
add(Feature) - Method in class org.tribuo.impl.IndexedArrayExample
 
add(Feature) - Method in class org.tribuo.impl.ListExample
 
add(SGDVector) - Method in class org.tribuo.math.la.DenseVector
Adds other to this vector, producing a new DenseVector.
add(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Adds other to this vector, producing a new SGDVector.
add(SGDVector) - Method in class org.tribuo.math.la.SparseVector
Adds other to this vector, producing a new SGDVector.
add(SequenceExample<T>) - Method in class org.tribuo.sequence.ImmutableSequenceDataset
Adds a SequenceExample to the dataset, which will insert feature ids, remove unknown features and sort the examples by the feature ids.
add(SequenceExample<T>) - Method in class org.tribuo.sequence.MutableSequenceDataset
Adds a SequenceExample to this dataset.
add(SequenceExample<T>, Merger) - Method in class org.tribuo.sequence.ImmutableSequenceDataset
Adds a SequenceExample to the dataset, which will insert feature ids, remove unknown features and sort the examples by the feature ids.
add(Row<T>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
ADD - Enum constant in enum class org.tribuo.classification.sequence.viterbi.ViterbiModel.ScoreAggregation
Adds the scores.
ADD - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Element-wise addition with broadcasting.
addAcrossDim1(int[], double) - Method in class org.tribuo.math.la.DenseMatrix
Adds the specified value to the specified elements across dimension 1.
addAcrossDim2(int[], double) - Method in class org.tribuo.math.la.DenseMatrix
Adds the specified value to the specified elements across dimension 2.
addAll(int, Collection<? extends Row<T>>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
addAll(Collection<? extends Example<T>>) - Method in class org.tribuo.MutableDataset
Adds all the Examples in the supplied collection to this dataset.
addAll(Collection<? extends Feature>) - Method in class org.tribuo.Example
Adds a collection of features.
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.ArrayExample
 
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.BinaryFeaturesExample
Adds a collection of features to this example.
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.IndexedArrayExample
 
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.ListExample
 
addAll(Collection<? extends Row<T>>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
addAll(Collection<SequenceExample<T>>) - Method in class org.tribuo.sequence.MutableSequenceDataset
Adds all the SequenceExamples in the supplied collection to this dataset.
addAllAttribute(Iterable<? extends OnnxMl.AttributeProto>) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
addAllDim(Iterable<? extends OnnxMl.TensorShapeProto.Dimension>) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
addAllDims(Iterable<? extends Long>) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
addAllDims(Iterable<? extends Long>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The shape of the tensor.
addAllDoubleData(Iterable<? extends Double>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
addAllExternalData(Iterable<? extends OnnxMl.StringStringEntryProto>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
addAllFloatData(Iterable<? extends Float>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
addAllFloats(Iterable<? extends Float>) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of floats
addAllGraphs(Iterable<? extends OnnxMl.GraphProto>) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
addAllInitializationBinding(Iterable<? extends OnnxMl.StringStringEntryProto>) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
addAllInitializer(Iterable<? extends OnnxMl.TensorProto>) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
addAllInput(Iterable<? extends OnnxMl.ValueInfoProto>) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
addAllInput(Iterable<String>) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
addAllInt32Data(Iterable<? extends Integer>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
addAllInt64Data(Iterable<? extends Long>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int64.
addAllInts(Iterable<? extends Long>) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of ints
addAllMetadataProps(Iterable<? extends OnnxMl.StringStringEntryProto>) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
addAllNode(Iterable<? extends OnnxMl.NodeProto>) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
addAllOpsetImport(Iterable<? extends OnnxMl.OperatorSetIdProto>) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
addAllOutput(Iterable<? extends OnnxMl.ValueInfoProto>) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
addAllOutput(Iterable<String>) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
addAllQuantizationAnnotation(Iterable<? extends OnnxMl.TensorAnnotation>) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
addAllQuantParameterTensorNames(Iterable<? extends OnnxMl.StringStringEntryProto>) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
addAllSparseInitializer(Iterable<? extends OnnxMl.SparseTensorProto>) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
addAllSparseTensors(Iterable<? extends OnnxMl.SparseTensorProto>) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
addAllStringData(Iterable<? extends ByteString>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For strings.
addAllStrings(Iterable<? extends ByteString>) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of UTF-8 strings
addAllTensors(Iterable<? extends OnnxMl.TensorProto>) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
addAllTrainingInfo(Iterable<? extends OnnxMl.TrainingInfoProto>) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
addAllUint64Data(Iterable<? extends Long>) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
addAllUpdateBinding(Iterable<? extends OnnxMl.StringStringEntryProto>) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
addAllValueInfo(Iterable<? extends OnnxMl.ValueInfoProto>) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
addAttribute(int, OnnxMl.AttributeProto) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
addAttribute(int, OnnxMl.AttributeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
addAttribute(OnnxMl.AttributeProto) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
addAttribute(OnnxMl.AttributeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
addAttributeBuilder() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
addAttributeBuilder(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
addBias - Variable in class org.tribuo.common.sgd.AbstractSGDModel
 
addBias - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
addChar() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Add a character to the buffer that we're building for a token.
addDim(int, OnnxMl.TensorShapeProto.Dimension) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
addDim(int, OnnxMl.TensorShapeProto.Dimension.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
addDim(OnnxMl.TensorShapeProto.Dimension) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
addDim(OnnxMl.TensorShapeProto.Dimension.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
addDimBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
addDimBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
addDims(long) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
addDims(long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The shape of the tensor.
addDoubleData(double) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
addExample(Example<T>) - Method in class org.tribuo.sequence.SequenceExample
Adds an Example to this sequence.
addExternalData(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
addExternalData(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
addExternalData(OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
addExternalData(OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
addExternalDataBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
addExternalDataBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
addFloatData(float) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
addFloats(float) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of floats
addGraphs(int, OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
addGraphs(int, OnnxMl.GraphProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
addGraphs(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
addGraphs(OnnxMl.GraphProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
addGraphsBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
addGraphsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
addInitializationBinding(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
addInitializationBinding(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
addInitializationBinding(OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
addInitializationBinding(OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
addInitializationBindingBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
addInitializationBindingBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
addInitializer(int, OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
addInitializer(int, OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
addInitializer(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
addInitializer(OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
addInitializerBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
addInitializerBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
addInput(int, OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
addInput(int, OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
addInput(OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
addInput(OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
addInput(String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
addInputBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
addInputBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
addInputBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
addInt32Data(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
addInt64Data(long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int64.
addInts(long) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of ints
addMetadataProps(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
addMetadataProps(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
addMetadataProps(OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
addMetadataProps(OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
addMetadataPropsBuilder() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
addMetadataPropsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
addNode(int, OnnxMl.NodeProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
addNode(int, OnnxMl.NodeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
addNode(OnnxMl.NodeProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
addNode(OnnxMl.NodeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
addNodeBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
addNodeBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
addOpsetImport(int, OnnxMl.OperatorSetIdProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
addOpsetImport(int, OnnxMl.OperatorSetIdProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
addOpsetImport(OnnxMl.OperatorSetIdProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
addOpsetImport(OnnxMl.OperatorSetIdProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
addOpsetImportBuilder() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
addOpsetImportBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
addOutput(int, OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
addOutput(int, OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
addOutput(OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
addOutput(OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
addOutput(String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
addOutputBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
addOutputBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
addOutputBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
addQuantizationAnnotation(int, OnnxMl.TensorAnnotation) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
addQuantizationAnnotation(int, OnnxMl.TensorAnnotation.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
addQuantizationAnnotation(OnnxMl.TensorAnnotation) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
addQuantizationAnnotation(OnnxMl.TensorAnnotation.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
addQuantizationAnnotationBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
addQuantizationAnnotationBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
addQuantParameterTensorNames(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
addQuantParameterTensorNames(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
addQuantParameterTensorNames(OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
addQuantParameterTensorNames(OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
addQuantParameterTensorNamesBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
addQuantParameterTensorNamesBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
addRepeatedField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
addSparseInitializer(int, OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
addSparseInitializer(int, OnnxMl.SparseTensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
addSparseInitializer(OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
addSparseInitializer(OnnxMl.SparseTensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
addSparseInitializerBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
addSparseInitializerBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
addSparseTensors(int, OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
addSparseTensors(int, OnnxMl.SparseTensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
addSparseTensors(OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
addSparseTensors(OnnxMl.SparseTensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
addSparseTensorsBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
addSparseTensorsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
addStringData(ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For strings.
addStrings(ByteString) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of UTF-8 strings
addTensors(int, OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
addTensors(int, OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
addTensors(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
addTensors(OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
addTensorsBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
addTensorsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
addTrainingInfo(int, OnnxMl.TrainingInfoProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
addTrainingInfo(int, OnnxMl.TrainingInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
addTrainingInfo(OnnxMl.TrainingInfoProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
addTrainingInfo(OnnxMl.TrainingInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
addTrainingInfoBuilder() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
addTrainingInfoBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
addUint64Data(long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
addUpdateBinding(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
addUpdateBinding(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
addUpdateBinding(OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
addUpdateBinding(OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
addUpdateBindingBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
addUpdateBindingBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
addValueInfo(int, OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
addValueInfo(int, OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
addValueInfo(OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
addValueInfo(OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
addValueInfoBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
addValueInfoBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
ADJUSTED_MI - Enum constant in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
The normalized mutual information adjusted for chance.
adjustedMI() - Method in interface org.tribuo.clustering.evaluation.ClusteringEvaluation
Measures the adjusted normalized mutual information between the predicted ids and the supplied ids.
adjustedMI(ClusteringMetric.Context) - Static method in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
Calculates the adjusted normalized mutual information between two clusterings.
advance() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
advance() - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
advance() - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
advance() - Method in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
advance() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
advance() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
advance() - Method in interface org.tribuo.util.tokens.Tokenizer
Advances the tokenizer to the next token.
advance() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
aggregate(List<Feature>) - Method in interface org.tribuo.data.text.FeatureAggregator
Aggregates feature values with the same names.
aggregate(List<Feature>) - Method in class org.tribuo.data.text.impl.AverageAggregator
 
aggregate(List<Feature>) - Method in class org.tribuo.data.text.impl.SumAggregator
 
aggregate(List<Feature>) - Method in class org.tribuo.data.text.impl.UniqueAggregator
 
AggregateConfigurableDataSource<T extends Output<T>> - Class in org.tribuo.datasource
Aggregates multiple ConfigurableDataSources, uses AggregateDataSource.IterationOrder to control the iteration order.
AggregateConfigurableDataSource(List<ConfigurableDataSource<T>>) - Constructor for class org.tribuo.datasource.AggregateConfigurableDataSource
Creates an aggregate data source which will iterate the provided sources in the order of the list (i.e., using AggregateDataSource.IterationOrder.SEQUENTIAL.
AggregateConfigurableDataSource(List<ConfigurableDataSource<T>>, AggregateDataSource.IterationOrder) - Constructor for class org.tribuo.datasource.AggregateConfigurableDataSource
Creates an aggregate data source using the supplied sources and iteration order.
AggregateConfigurableDataSource.AggregateConfigurableDataSourceProvenance - Class in org.tribuo.datasource
AggregateConfigurableDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.AggregateConfigurableDataSource.AggregateConfigurableDataSourceProvenance
Deserialization constructor.
AggregateDataSource<T extends Output<T>> - Class in org.tribuo.datasource
Aggregates multiple DataSources, uses AggregateDataSource.IterationOrder to control the iteration order.
AggregateDataSource(List<DataSource<T>>) - Constructor for class org.tribuo.datasource.AggregateDataSource
Creates an aggregate data source which will iterate the provided sources in the order of the list (i.e., using AggregateDataSource.IterationOrder.SEQUENTIAL.
AggregateDataSource(List<DataSource<T>>, AggregateDataSource.IterationOrder) - Constructor for class org.tribuo.datasource.AggregateDataSource
Creates an aggregate data source using the supplied sources and iteration order.
AggregateDataSource.AggregateDataSourceProvenance - Class in org.tribuo.datasource
Provenance for the AggregateDataSource.
AggregateDataSource.IterationOrder - Enum Class in org.tribuo.datasource
Specifies the iteration order of the inner sources.
AggregateDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
Deserialization constructor.
ai.onnx.proto - package ai.onnx.proto
 
algorithm - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Type of learner (or base learner).
algorithm - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
Type of SVR.
algorithm - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
Choose the training algorithm (stepwise forward selection or least angle regression).
ALGORITHM_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
ALL - Enum constant in enum class org.tribuo.json.StripProvenance.ProvenanceTypes
Selects all provenance stored in the model.
ALL_OUTPUTS - Static variable in class org.tribuo.Model
Used in getTopFeatures when the Model doesn't support per output feature lists.
AllClassificationOptions() - Constructor for class org.tribuo.classification.experiments.TrainTest.AllClassificationOptions
 
allProvenances() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
 
allProvenances() - Method in class org.tribuo.dataset.MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance
 
allProvenances() - Method in class org.tribuo.provenance.DatasetProvenance
Returns a list of all the provenances.
allProvenances() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
 
AllTrainerOptions - Class in org.tribuo.classification.experiments
Aggregates all the classification algorithms.
AllTrainerOptions() - Constructor for class org.tribuo.classification.experiments.AllTrainerOptions
 
AllTrainerOptions.AlgorithmType - Enum Class in org.tribuo.classification.experiments
Types of algorithms supported.
alpha - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
Regularisation strength in the Elastic Net.
alpha - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
L1 regularization term for weights (default 0).
alpha - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
L1 regularization term for weights (default 0).
alphas - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainBPResults
The alpha values array from forward propagation.
annotateGraph(Graph, Session) - Static method in class org.tribuo.interop.tensorflow.TensorFlowUtil
Annotates a graph with an extra placeholder and assign operation for each VariableV2.
ANOMALOUS - Enum constant in enum class org.tribuo.anomaly.Event.EventType
An anomalous event, with id 1.
ANOMALOUS_EVENT - Static variable in class org.tribuo.anomaly.AnomalyFactory
The anomalous event.
ANOMALY_DETECTION - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Anomaly detection, maps to Tribuo's Event.
anomalyCount - Variable in class org.tribuo.anomaly.AnomalyInfo
The number of anomalous events observed.
AnomalyDataGenerator - Class in org.tribuo.anomaly.example
Generates three example train and test datasets, used for unit testing.
AnomalyDataGenerator() - Constructor for class org.tribuo.anomaly.example.AnomalyDataGenerator
 
AnomalyEvaluation - Interface in org.tribuo.anomaly.evaluation
An Evaluation for anomaly detection Events.
AnomalyEvaluator - Class in org.tribuo.anomaly.evaluation
An Evaluator for anomaly detection Events.
AnomalyEvaluator() - Constructor for class org.tribuo.anomaly.evaluation.AnomalyEvaluator
 
AnomalyFactory - Class in org.tribuo.anomaly
A factory for generating events.
AnomalyFactory() - Constructor for class org.tribuo.anomaly.AnomalyFactory
 
AnomalyFactory.AnomalyFactoryProvenance - Class in org.tribuo.anomaly
Provenance for AnomalyFactory.
AnomalyFactoryProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.anomaly.AnomalyFactory.AnomalyFactoryProvenance
Constructs an anomaly factory provenance from the marshalled form.
AnomalyInfo - Class in org.tribuo.anomaly
The base class for tracking anomalous events.
AnomalyInfo() - Constructor for class org.tribuo.anomaly.AnomalyInfo
Constructs a new empty anomaly info.
AnomalyInfo(AnomalyInfo) - Constructor for class org.tribuo.anomaly.AnomalyInfo
Copies the supplied anomaly info.
AnomalyMetric - Class in org.tribuo.anomaly.evaluation
A metric for evaluating anomaly detection problems.
AnomalyMetric(MetricTarget<Event>, String, ToDoubleBiFunction<MetricTarget<Event>, AnomalyMetric.Context>) - Constructor for class org.tribuo.anomaly.evaluation.AnomalyMetric
Creates an anomaly detection metric, with a specific name, using the supplied evaluation function.
AnomalyMetrics - Enum Class in org.tribuo.anomaly.evaluation
Default metrics for evaluating anomaly detection.
apply(int, int, CharSequence) - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer.SplitCharactersSplitterFunction
 
apply(int, int, CharSequence) - Method in interface org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitFunction
Applies the split function.
apply(E) - Method in interface org.tribuo.evaluation.EvaluationRenderer
Convert the evaluation to a string.
apply(ONNXOperators) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String), using this ONNXRef as the argument to inputs.
apply(ONNXOperators, String) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String), using this ONNXRef as the argument to inputs.
apply(ONNXOperators, List<String>, Map<String, Object>) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, List, Map), using this ONNXRef as the argument to inputs.
apply(ONNXOperators, List<ONNXRef<?>>) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String, Map), using this ONNXRef as the first argument to inputs, with otherInputs append as subsequent arguments.
apply(ONNXOperators, List<ONNXRef<?>>, String) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String, Map), using this ONNXRef as the argument to inputs, with otherInputs append as subsequent arguments.
apply(ONNXOperators, List<ONNXRef<?>>, List<String>, Map<String, Object>) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, List, Map), using this ONNXRef as the first argument to inputs, with otherInputs append as subsequent arguments.
apply(ONNXOperators, Map<String, Object>) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String, Map), using this ONNXRef as the argument to inputs.
apply(ONNXOperators, ONNXRef<?>) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String, Map), passing this ONNXRef and other as a length 2 list to inputs.
apply(ONNXOperators, ONNXRef<?>, String) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String), passing this ONNXRef and other as a length 2 list to inputs.
apply(ONNXOperators, ONNXRef<?>, Map<String, Object>) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.operation(ONNXOperators, List, String, Map), passing this ONNXRef and other as a length 2 list to inputs.
applyCase(String) - Method in enum class org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Apply the appropriate casing operation.
applyOptimiser(Graph, Operand<T>, Map<String, Float>) - Method in enum class org.tribuo.interop.tensorflow.GradientOptimiser
Applies the optimiser to the graph and returns the optimiser step operation.
applyTransformerList(double, List<Transformer>) - Static method in class org.tribuo.transform.TransformerMap
Applies a List of Transformers to the supplied double value, returning the transformed value.
APPROX - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
Approximate greedy algorithm, using a quantile sketch of the data and a gradient histogram.
ARCH_STRING - Static variable in class org.tribuo.provenance.ModelProvenance
 
archString - Variable in class org.tribuo.provenance.ModelProvenance
 
argmax(List<R>, Function<R, Double>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Calculates the argmax of a metric across the supplied evaluations.
argmax(List<T>) - Static method in class org.tribuo.util.Util
Find the index of the maximum value in a list.
argmax(EvaluationMetric<T, C>, List<? extends Model<T>>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Calculates the argmax of a metric across the supplied models (i.e., the index of the model which performed the best).
argmax(EvaluationMetric<T, C>, Model<T>, List<? extends Dataset<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Calculates the argmax of a metric across the supplied datasets.
argmin(List<T>) - Static method in class org.tribuo.util.Util
Find the index of the minimum value in a list.
array - Variable in class org.tribuo.common.tree.impl.IntArrayContainer
The array of ints.
array(String, double[]) - Method in class org.tribuo.util.onnx.ONNXContext
Creates a float tensor for this ONNXContext, populated according to parameters.
array(String, double[], boolean) - Method in class org.tribuo.util.onnx.ONNXContext
Creates a tensor for this ONNXContext, populated according to parameters.
array(String, float[]) - Method in class org.tribuo.util.onnx.ONNXContext
Creates a float tensor for this ONNXContext, populated according to parameters.
array(String, int[]) - Method in class org.tribuo.util.onnx.ONNXContext
Creates an int tensor for this ONNXContext, populated according to parameters.
array(String, long[]) - Method in class org.tribuo.util.onnx.ONNXContext
Creates a long tensor for this ONNXContext, populated according to parameters.
ARRAY_FEATURE_EXTRACTOR - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Array feature extractor, selects the indices specified by the second tensor from the last dimension of the first tensor.
arrayBuilder(ONNXContext, String, double[]) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the array.
arrayBuilder(ONNXContext, String, double[], boolean) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the array.
arrayBuilder(ONNXContext, String, float[]) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the array.
arrayBuilder(ONNXContext, String, int[]) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the array.
arrayBuilder(ONNXContext, String, long[]) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the array.
ArrayExample<T extends Output<T>> - Class in org.tribuo.impl
An Example backed by two arrays, one of String and one of double.
ArrayExample(Example<T>) - Constructor for class org.tribuo.impl.ArrayExample
Copy constructor.
ArrayExample(T) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output.
ArrayExample(T, float) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output and a weight.
ArrayExample(T, float, int) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output and a weight, with an initial size for the feature arrays.
ArrayExample(T, float, Map<String, Object>) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output, a weight and the metadata.
ArrayExample(T, String[], double[]) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output, an array of names and an array of values.
ArrayExample(T, List<? extends Feature>) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output and a list of features.
ArrayExample(T, Map<String, Object>) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output and the metadata.
ArrayExample(T, Example<U>, float) - Constructor for class org.tribuo.impl.ArrayExample
Clones an example's features, but uses the supplied output and weight.
asMap() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
asMap() - Method in interface org.tribuo.evaluation.Evaluation
Get a map of all the metrics stored in this evaluation.
asMap() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
asMap() - Method in interface org.tribuo.sequence.SequenceEvaluation
Get a map of all the metrics stored in this evaluation.
ASSIGN_OP - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
The name of the assignment op.
ASSIGN_PLACEHOLDER - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
The name given to the assignment operation from the placeholders.
assignTo(Ret) - Method in class org.tribuo.util.onnx.ONNXRef
Convenience method that calls ONNXContext.assignTo(ONNXRef, ONNXRef), using this ONNXRef as the argument to input.
assignTo(RHS, LHS) - Method in class org.tribuo.util.onnx.ONNXContext
Creates an ONNXOperators.IDENTITY node connecting input to output, effectively permitting assignment of values.
ATTENTION_MASK - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Input name for the attention mask.
ATTRIBUTE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
 
attributes - Variable in enum class org.tribuo.util.onnx.ONNXOperators
The operator attributes.
auc(double[], double[]) - Static method in class org.tribuo.util.Util
Calculates the area under the curve, bounded below by the x axis.
AUCROC - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The area under the receiver-operator curve (ROC).
AUCROC(Label) - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
Area under the ROC curve.
AUCROC(Label, List<Prediction<Label>>) - Static method in enum class org.tribuo.classification.evaluation.LabelMetrics
Area under the ROC curve.
AUCROC(MetricTarget<Label>, List<Prediction<Label>>) - Static method in enum class org.tribuo.classification.evaluation.LabelMetrics
Area under the ROC curve.
AUTO - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
XGBoost chooses between XGBoostTrainer.TreeMethod.EXACT and XGBoostTrainer.TreeMethod.APPROX depending on dataset size.
AverageAggregator - Class in org.tribuo.data.text.impl
A feature aggregator that averages feature values across a feature list.
AverageAggregator() - Constructor for class org.tribuo.data.text.impl.AverageAggregator
 
averageAUCROC(boolean) - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
Area under the ROC curve averaged across labels.
AVERAGED_PRECISION - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The averaged precision.
averagedExplainedVariance() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
The average explained variance across all dimensions.
averagedPrecision(boolean[], double[]) - Static method in class org.tribuo.classification.evaluation.LabelEvaluationUtil
Summarises a Precision-Recall Curve by taking the weighted mean of the precisions at a given threshold, where the weight is the recall achieved at that threshold.
averagedPrecision(Label) - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
Summarises a Precision-Recall Curve by taking the weighted mean of the precisions at a given threshold, where the weight is the recall achieved at that threshold.
averagedPrecision(Label, List<Prediction<Label>>) - Static method in enum class org.tribuo.classification.evaluation.LabelMetrics
 
averagedPrecision(MetricTarget<Label>, List<Prediction<Label>>) - Static method in enum class org.tribuo.classification.evaluation.LabelMetrics
 
averageMAE() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
The average Mean Absolute Error across all dimensions.
averageR2() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
The average R2 across all dimensions.
averageRMSE() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
The average RMSE across all dimensions.
AveragingCombiner - Class in org.tribuo.regression.ensemble
A combiner which performs a weighted or unweighted average of the predicted regressors independently across the output dimensions.
AveragingCombiner() - Constructor for class org.tribuo.regression.ensemble.AveragingCombiner
Constructs an averaging combiner.

B

b - Variable in class org.tribuo.util.infotheory.impl.CachedTriple
 
backRef - Variable in class org.tribuo.util.onnx.ONNXRef
 
BAGGING - Enum constant in enum class org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
Creates a BaggingTrainer.
BaggingTrainer<T extends Output<T>> - Class in org.tribuo.ensemble
A Trainer that wraps another trainer and produces a bagged ensemble.
BaggingTrainer() - Constructor for class org.tribuo.ensemble.BaggingTrainer
For the configuration system.
BaggingTrainer(Trainer<T>, EnsembleCombiner<T>, int) - Constructor for class org.tribuo.ensemble.BaggingTrainer
Constructs a bagging trainer with the supplied parameters using Trainer.DEFAULT_SEED as the RNG seed.
BaggingTrainer(Trainer<T>, EnsembleCombiner<T>, int, long) - Constructor for class org.tribuo.ensemble.BaggingTrainer
Constructs a bagging trainer with the supplied parameters.
BALANCED_ERROR_RATE - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The balanced error rate, i.e., the mean of the per class recalls.
BALANCED_ERROR_RATE - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The balanced error rate, i.e., the mean of the per class recalls.
balancedErrorRate() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the balanced error rate, i.e., the mean of the per label recalls.
balancedErrorRate() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the balanced error rate.
balancedErrorRate() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
balancedErrorRate(ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the balanced error rate, i.e., the mean of the recalls.
bandwidth - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Model bandwidth in MBps.
bandwidth - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelDeploymentConfig
The bandwidth for the load balancer in MBps.
BasicPipeline - Class in org.tribuo.data.text.impl
An example implementation of TextPipeline.
BasicPipeline(Tokenizer, int) - Constructor for class org.tribuo.data.text.impl.BasicPipeline
Constructs a basic text pipeline which tokenizes the input and generates word n-gram features in the range 1 to ngram.
batchSize - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
batchSize - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Minibatch size.
begin - Variable in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
The subsequence start index.
begin - Variable in class org.tribuo.classification.sgd.crf.Chunk
The starting point of this chunk.
BEGIN_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
beliefPropagation(ChainHelper.ChainCliqueValues) - Static method in class org.tribuo.classification.sgd.crf.ChainHelper
Runs belief propagation on a linear chain CRF.
bert - Variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.BERTFeatureExtractorOptions
BERTFeatureExtractor instance
BERTFeatureExtractor<T extends Output<T>> - Class in org.tribuo.interop.onnx.extractors
Builds examples and sequence examples using features from BERT.
BERTFeatureExtractor(OutputFactory<T>, Path, Path) - Constructor for class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Constructs a BERTFeatureExtractor.
BERTFeatureExtractor(OutputFactory<T>, Path, Path, BERTFeatureExtractor.OutputPooling, int, boolean) - Constructor for class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Constructs a BERTFeatureExtractor.
BERTFeatureExtractor.BERTFeatureExtractorOptions - Class in org.tribuo.interop.onnx.extractors
CLI options for running BERT.
BERTFeatureExtractor.OutputPooling - Enum Class in org.tribuo.interop.onnx.extractors
The type of output pooling to perform.
BERTFeatureExtractorOptions() - Constructor for class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.BERTFeatureExtractorOptions
 
betas - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainBPResults
The beta values array from backward propagation.
BFLOAT16 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Non-IEEE floating-point format based on IEEE754 single-precision floating-point number truncated to 16 bits.
BFLOAT16_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Non-IEEE floating-point format based on IEEE754 single-precision floating-point number truncated to 16 bits.
BIAS_FEATURE - Static variable in class org.tribuo.Model
Used to denote the bias feature in a linear model.
binarise - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Binarises the output around 1.0.
binarise() - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that sets negative and zero values to zero and positive values to one.
BINARISED_CATEGORICAL - Enum constant in enum class org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Categoricals binarised into separate features.
BINARY_CLASSIFICATION - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Binary classification.
binaryAUCROC(boolean[], double[]) - Static method in class org.tribuo.classification.evaluation.LabelEvaluationUtil
Calculates the area under the receiver operator characteristic curve, i.e., the AUC of the ROC curve.
BinaryCrossEntropy - Class in org.tribuo.multilabel.sgd.objectives
A multilabel version of binary cross entropy loss which expects logits.
BinaryCrossEntropy() - Constructor for class org.tribuo.multilabel.sgd.objectives.BinaryCrossEntropy
Constructs a BinaryCrossEntropy objective.
BinaryFeaturesExample<T extends Output<T>> - Class in org.tribuo.impl
An Example backed by a single array of feature names.
BinaryFeaturesExample(Example<T>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Copy constructor.
BinaryFeaturesExample(T) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output.
BinaryFeaturesExample(T, float) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output and a weight.
BinaryFeaturesExample(T, float, int) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output and a weight, with an initial size for the feature arrays.
BinaryFeaturesExample(T, float, Map<String, Object>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output, a weight and the metadata.
BinaryFeaturesExample(T, String[]) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output and an array of names.
BinaryFeaturesExample(T, List<? extends Feature>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output and a list of features.
BinaryFeaturesExample(T, Map<String, Object>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output and the metadata.
BinaryFeaturesExample(T, Example<U>, float) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Clones an example's features, but uses the supplied output and weight.
BinaryResponseProcessor<T extends Output<T>> - Class in org.tribuo.data.columnar.processors.response
A ResponseProcessor that takes a single value of the field as the positive class and all other values as the negative class.
BinaryResponseProcessor(String, String, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Constructs a binary response processor which emits a positive value for a single string and a negative value for all other field values.
BinaryResponseProcessor(List<String>, String, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Constructs a binary response processor which emits a positive value for a single string and a negative value for all other field values.
BinaryResponseProcessor(List<String>, List<String>, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Constructs a binary response processor which emits a positive value for a single string and a negative value for all other field values.
BinaryResponseProcessor(List<String>, List<String>, OutputFactory<T>, boolean) - Constructor for class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Constructs a binary response processor which emits a positive value for a single string and a negative value for all other field values.
BinaryResponseProcessor(List<String>, List<String>, OutputFactory<T>, String, String, boolean) - Constructor for class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Constructs a binary response processor which emits a positive value for a single string and a negative value for all other field values.
binarySearch(List<? extends Comparable<? super T>>, T) - Static method in class org.tribuo.util.Util
A binary search function.
binarySearch(List<? extends Comparable<? super T>>, T, int, int) - Static method in class org.tribuo.util.Util
A binary search function.
binarySearch(List<? extends T>, int, ToIntFunction<T>) - Static method in class org.tribuo.util.Util
A binary search function.
binarySparseTrainTest() - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates a pair of datasets with sparse features and unknown features in the test data.
binarySparseTrainTest(double) - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates a pair of datasets with sparse features and unknown features in the test data.
BinningTransformation - Class in org.tribuo.transform.transformations
A Transformation which bins values.
BinningTransformation.BinningTransformationProvenance - Class in org.tribuo.transform.transformations
Provenance for BinningTransformation.
BinningTransformation.BinningType - Enum Class in org.tribuo.transform.transformations
The allowed binning types.
BinningTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
Deserialization constructor.
BOOL - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
bool
BOOL_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
bool
BREAK_ITERATOR - Enum constant in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
breakIteratorOptions - Variable in class org.tribuo.util.tokens.options.CoreTokenizerOptions
Options for the break iterator tokenizer.
BreakIteratorTokenizer - Class in org.tribuo.util.tokens.impl
A tokenizer wrapping a BreakIterator instance.
BreakIteratorTokenizer(Locale) - Constructor for class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
Constructs a BreakIteratorTokenizer using the specified locale.
BreakIteratorTokenizerOptions - Class in org.tribuo.util.tokens.options
CLI options for a BreakIteratorTokenizer.
BreakIteratorTokenizerOptions() - Constructor for class org.tribuo.util.tokens.options.BreakIteratorTokenizerOptions
 
broadcastIntersectAndAddInPlace(SGDVector, boolean) - Method in class org.tribuo.math.la.DenseMatrix
Broadcasts the input vector and adds it to each row/column of the matrix.
buff - Variable in class org.tribuo.util.tokens.universal.Range
The character buffer.
build() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
build() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
build(Object) - Method in class org.tribuo.util.onnx.ONNXAttribute
Builds the attribute proto using the supplied value.
build(ONNXContext, String[], String) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied inputs and output.
build(ONNXContext, String[], String[]) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied inputs and outputs.
build(ONNXContext, String[], String[], Map<String, Object>) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied inputs and outputs.
build(ONNXContext, String[], String, Map<String, Object>) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied inputs and output.
build(ONNXContext, String, String) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied inputs and output.
build(ONNXContext, String, String[]) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied input and outputs.
build(ONNXContext, String, String[], Map<String, Object>) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied input and outputs.
build(ONNXContext, String, String, Map<String, Object>) - Method in enum class org.tribuo.util.onnx.ONNXOperators
Builds this node based on the supplied inputs and output.
BUILD_TIMESTAMP - Static variable in class org.tribuo.Tribuo
The build timestamp.
buildGraph() - Method in class org.tribuo.util.onnx.ONNXContext
Builds the ONNX graph represented by this context.
buildLeNetGraph(String, int, int, int) - Static method in class org.tribuo.interop.tensorflow.example.CNNExamples
Builds a LeNet 5 style CNN (usually used for MNIST).
buildMLPGraph(String, int, int[], int) - Static method in class org.tribuo.interop.tensorflow.example.MLPExamples
Builds an MLP which expects the supplied number of inputs, has hiddenSizes.length hidden layers, before emitting numOutput outputs.
buildModel(ONNXContext, String, long, M) - Static method in interface org.tribuo.ONNXExportable
Creates an ONNX model protobuf for the supplied context.
buildPartial() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
buildPartial() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
buildRandomTree(int[], SplittableRandom) - Method in class org.tribuo.classification.dtree.impl.ClassifierTrainingNode
Builds a CART tree with randomly chosen split points.
buildRuntimeYaml(String, String) - Static method in class org.tribuo.interop.oci.OCIUtil
Builds the runtime.yaml String from the supplied arguments, throwing IllegalArgumentException if they are invalid.
buildTensorTypeNode(ONNXShape, OnnxMl.TensorProto.DataType) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a type proto for the specified shape and tensor type.
buildTree(int[], SplittableRandom, boolean) - Method in class org.tribuo.classification.dtree.impl.ClassifierTrainingNode
Builds a tree according to CART (as it does not do multi-way splits on categorical values like C4.5).
buildTree(int[], SplittableRandom, boolean) - Method in class org.tribuo.common.tree.AbstractTrainingNode
Builds next level of a tree.
buildTree(int[], SplittableRandom, boolean) - Method in class org.tribuo.regression.rtree.impl.JointRegressorTrainingNode
Builds a tree according to CART (as it does not do multi-way splits on categorical values like C4.5).
buildTree(int[], SplittableRandom, boolean) - Method in class org.tribuo.regression.rtree.impl.RegressorTrainingNode
Builds a tree according to CART (as it does not do multi-way splits on categorical values like C4.5).
BYTE - Enum constant in enum class org.tribuo.datasource.IDXDataSource.IDXType
A signed byte.

C

c - Variable in class org.tribuo.util.infotheory.impl.CachedTriple
 
C_SVC - Enum constant in enum class org.tribuo.classification.libsvm.SVMClassificationType.SVMMode
Original SVM algorithm.
CachedPair<T1,T2> - Class in org.tribuo.util.infotheory.impl
A pair of things with a cached hashcode.
CachedPair(T1, T2) - Constructor for class org.tribuo.util.infotheory.impl.CachedPair
Constructs a CachedPair.
CachedTriple<T1,T2,T3> - Class in org.tribuo.util.infotheory.impl
A triple of things.
CachedTriple(T1, T2, T3) - Constructor for class org.tribuo.util.infotheory.impl.CachedTriple
Constructs a CachedTriple.
cacheProvenance() - Method in class org.tribuo.data.text.impl.SimpleStringDataSource
 
cacheProvenance() - Method in class org.tribuo.data.text.impl.SimpleTextDataSource
 
calculateCountDist(List<T>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Generate the counts for a single vector.
calculateEntropy(DoubleStream) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon entropy of a stream, assuming each element of the stream is an element of the same probability distribution.
calculateEntropy(Stream<Double>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon entropy of a stream, assuming each element of the stream is an element of the same probability distribution.
calculateHashCode() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
Overridden hashcode.
calculateWeightedCountDist(ArrayList<T>, ArrayList<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Generate the counts for a single vector.
CALENDAR_QUARTER - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The calendar quarter of the year.
canonicalise(FeatureMap) - Method in class org.tribuo.sequence.SequenceExample
Reassigns feature name Strings in each Example inside this SequenceExample to point to those in the FeatureMap.
canonicalize(FeatureMap) - Method in class org.tribuo.Example
Reassigns feature name Strings in the Example to point to those in the FeatureMap.
canonicalize(FeatureMap) - Method in class org.tribuo.impl.ArrayExample
 
canonicalize(FeatureMap) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
canonicalize(FeatureMap) - Method in class org.tribuo.impl.ListExample
 
CART - Enum constant in enum class org.tribuo.classification.dtree.CARTClassificationOptions.TreeType
Builds a CART model.
CART - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
CART_INDEPENDENT - Enum constant in enum class org.tribuo.regression.rtree.TrainTest.TreeType
Creates a CARTRegressionTrainer which treats each regression dimension independently.
CART_JOINT - Enum constant in enum class org.tribuo.regression.rtree.TrainTest.TreeType
Creates a CARTJointRegressionTrainer which jointly minimises the impurity across all output dimensions.
CARTClassificationOptions - Class in org.tribuo.classification.dtree
Options for building a classification tree trainer.
CARTClassificationOptions() - Constructor for class org.tribuo.classification.dtree.CARTClassificationOptions
 
CARTClassificationOptions.ImpurityType - Enum Class in org.tribuo.classification.dtree
The impurity algorithm.
CARTClassificationOptions.TreeType - Enum Class in org.tribuo.classification.dtree
Type of decision tree algorithm.
CARTClassificationTrainer - Class in org.tribuo.classification.dtree
A Trainer that uses an approximation of the CART algorithm to build a decision tree.
CARTClassificationTrainer() - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART Trainer.
CARTClassificationTrainer(int) - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART trainer.
CARTClassificationTrainer(int, float, boolean, long) - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART Trainer.
CARTClassificationTrainer(int, float, float, float, boolean, LabelImpurity, long) - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART Trainer.
CARTClassificationTrainer(int, float, float, float, LabelImpurity, long) - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART Trainer.
CARTClassificationTrainer(int, float, long) - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART Trainer.
cartImpurity - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Impurity measure to use.
CARTJointRegressionTrainer - Class in org.tribuo.regression.rtree
A Trainer that uses an approximation of the CART algorithm to build a decision tree.
CARTJointRegressionTrainer() - Constructor for class org.tribuo.regression.rtree.CARTJointRegressionTrainer
Creates a CART Trainer.
CARTJointRegressionTrainer(int) - Constructor for class org.tribuo.regression.rtree.CARTJointRegressionTrainer
Creates a CART Trainer.
CARTJointRegressionTrainer(int, boolean) - Constructor for class org.tribuo.regression.rtree.CARTJointRegressionTrainer
Creates a CART Trainer.
CARTJointRegressionTrainer(int, float, float, float, boolean, RegressorImpurity, boolean, long) - Constructor for class org.tribuo.regression.rtree.CARTJointRegressionTrainer
Creates a CART Trainer.
CARTJointRegressionTrainer(int, float, float, float, RegressorImpurity, boolean, long) - Constructor for class org.tribuo.regression.rtree.CARTJointRegressionTrainer
Creates a CART Trainer.
cartMaxDepth - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Maximum depth in the decision tree.
cartMinChildWeight - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Minimum child weight.
cartMinImpurityDecrease - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Minimum impurity decrease.
cartOptions - Variable in class org.tribuo.classification.dtree.TrainTest.TrainTestOptions
The CART trainer options.
cartOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for CART trainers.
cartPrintTree - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Prints the decision tree.
cartRandomSplit - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Whether to choose split points for features at random.
CARTRegressionTrainer - Class in org.tribuo.regression.rtree
A Trainer that uses an approximation of the CART algorithm to build a decision tree.
CARTRegressionTrainer() - Constructor for class org.tribuo.regression.rtree.CARTRegressionTrainer
Creates a CART trainer.
CARTRegressionTrainer(int) - Constructor for class org.tribuo.regression.rtree.CARTRegressionTrainer
Creates a CART trainer.
CARTRegressionTrainer(int, float, float, float, boolean, RegressorImpurity, long) - Constructor for class org.tribuo.regression.rtree.CARTRegressionTrainer
Creates a CART Trainer.
CARTRegressionTrainer(int, float, float, float, RegressorImpurity, long) - Constructor for class org.tribuo.regression.rtree.CARTRegressionTrainer
Creates a CART Trainer.
cartSeed - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
RNG seed.
cartSplitFraction - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Fraction of features in split.
cartTreeAlgorithm - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
Tree algorithm to use (options are CART).
CasingPreprocessor - Class in org.tribuo.data.text.impl
A document preprocessor which uppercases or lowercases the input.
CasingPreprocessor(CasingPreprocessor.CasingOperation) - Constructor for class org.tribuo.data.text.impl.CasingPreprocessor
Construct a casing preprocessor.
CasingPreprocessor.CasingOperation - Enum Class in org.tribuo.data.text.impl
The possible casing operations.
cast(Class<?>) - Method in class org.tribuo.util.onnx.ONNXRef
Casts this ONNXRef to a different type using the ONNXOperators.CAST operation, and returning the output node of that op.
CAST - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Cast input to specified type.
castDataset(Dataset<?>, Class<T>) - Static method in class org.tribuo.Dataset
Casts the dataset to the specified output type, assuming it is valid.
castModel(Class<U>) - Method in class org.tribuo.Model
Casts the model to the specified output type, assuming it is valid.
CATEGORICAL - Enum constant in enum class org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Unordered categorical features with the values converted into doubles.
CategoricalIDInfo - Class in org.tribuo
Same as a CategoricalInfo, but with an additional int id field.
CategoricalIDInfo(CategoricalInfo, int) - Constructor for class org.tribuo.CategoricalIDInfo
Constructs a categorical id info copying the information from the supplied info, with the specified id.
CategoricalInfo - Class in org.tribuo
Stores information about Categorical features.
CategoricalInfo(String) - Constructor for class org.tribuo.CategoricalInfo
Constructs a new empty categorical info for the supplied feature name.
CategoricalInfo(CategoricalInfo) - Constructor for class org.tribuo.CategoricalInfo
Constructs a deep copy of the supplied categorical info.
CategoricalInfo(CategoricalInfo, String) - Constructor for class org.tribuo.CategoricalInfo
Constructs a deep copy of the supplied categorical info, with the new feature name.
CC_NEGATIVE - Static variable in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
The string used in the feature name for negative labels.
CC_POSITIVE - Static variable in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
The string used in the feature name for positive labels.
CC_PREFIX - Static variable in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
The prefix for classifier chain added features.
CC_SEPARATOR - Static variable in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
The joiner character for classifier chain added features.
CCEnsembleTrainer - Class in org.tribuo.multilabel.ensemble
A trainer for an ensemble of randomly ordered Classifier Chains.
CCEnsembleTrainer(Trainer<Label>, int, long) - Constructor for class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
Constructs a classifier chain ensemble trainer.
cdf - Variable in class org.tribuo.CategoricalInfo
The CDF to sample from.
centroids - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
Number of centroids in K-Means.
centroids - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
Number of clusters to infer.
ChainHelper - Class in org.tribuo.classification.sgd.crf
A collection of helper methods for performing training and inference in a CRF.
ChainHelper.ChainBPResults - Class in org.tribuo.classification.sgd.crf
Belief Propagation results.
ChainHelper.ChainCliqueValues - Class in org.tribuo.classification.sgd.crf
Clique scores within a chain.
ChainHelper.ChainViterbiResults - Class in org.tribuo.classification.sgd.crf
Viterbi output from a linear chain.
charAt(int) - Method in class org.tribuo.util.tokens.universal.Range
 
CheckerboardDataSource - Class in org.tribuo.classification.example
Creates a data source using a 2d checkerboard of alternating classes.
CheckerboardDataSource(int, long, int, double, double) - Constructor for class org.tribuo.classification.example.CheckerboardDataSource
Creates a checkboard with the required number of squares per dimension, where each feature value lies between min and max.
checkIsBinary(Feature) - Static method in class org.tribuo.impl.BinaryFeaturesExample
Checks if the supplied feature is binary, if not throw an IllegalArgumentException.
CHECKPOINT - Enum constant in enum class org.tribuo.interop.tensorflow.TensorFlowTrainer.TFModelFormat
Saves the model state inside a TensorFlow checkpoint, emits a TensorFlowCheckpointModel.
checkpointPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Path to the checkpoint base directory.
Chunk - Class in org.tribuo.classification.sgd.crf
Chunk class used for chunk level confidence prediction in the CRFModel.
Chunk(int, int[]) - Constructor for class org.tribuo.classification.sgd.crf.Chunk
Constructs a chunk.
Classifiable<T extends Classifiable<T>> - Interface in org.tribuo.classification
A tag interface for multi-class and multi-label classification tasks.
CLASSIFICATION_TOKEN - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Default classification token name.
ClassificationEnsembleOptions - Class in org.tribuo.classification.ensemble
Options for building a classification ensemble.
ClassificationEnsembleOptions() - Constructor for class org.tribuo.classification.ensemble.ClassificationEnsembleOptions
 
ClassificationEnsembleOptions.EnsembleType - Enum Class in org.tribuo.classification.ensemble
The type of ensemble.
ClassificationOptions<TRAINER extends Trainer<Label>> - Interface in org.tribuo.classification
An Options that can produce a classification Trainer based on the provided arguments.
ClassifierChainModel - Class in org.tribuo.multilabel.baseline
A Classifier Chain Model.
ClassifierChainTrainer - Class in org.tribuo.multilabel.baseline
A trainer for a Classifier Chain.
ClassifierChainTrainer(Trainer<Label>, long) - Constructor for class org.tribuo.multilabel.baseline.ClassifierChainTrainer
Builds a classifier chain trainer using the specified member trainer and seed.
ClassifierChainTrainer(Trainer<Label>, List<String>) - Constructor for class org.tribuo.multilabel.baseline.ClassifierChainTrainer
Builds a classifier chain trainer using the specified member trainer and seed.
ClassifierEvaluation<T extends Classifiable<T>> - Interface in org.tribuo.classification.evaluation
Defines methods that calculate classification performance, used for both multi-class and multi-label classification.
ClassifierTrainingNode - Class in org.tribuo.classification.dtree.impl
A decision tree node used at training time.
ClassifierTrainingNode(LabelImpurity, Dataset<Label>, AbstractTrainingNode.LeafDeterminer) - Constructor for class org.tribuo.classification.dtree.impl.ClassifierTrainingNode
Constructor which creates the inverted file.
className - Variable in class org.tribuo.interop.tensorflow.TensorFlowUtil.TensorTuple
The tensor class name.
className - Variable in class org.tribuo.provenance.ModelProvenance
 
clear() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
clear() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
clear() - Method in class org.tribuo.anomaly.MutableAnomalyInfo
 
clear() - Method in class org.tribuo.classification.MutableLabelInfo
 
clear() - Method in class org.tribuo.clustering.MutableClusteringInfo
 
clear() - Method in class org.tribuo.impl.ListExample
Clears the features from this example.
clear() - Method in class org.tribuo.multilabel.MutableMultiLabelInfo
 
clear() - Method in class org.tribuo.MutableDataset
Clears all the examples out of this dataset, and flushes the FeatureMap, OutputInfo, and transform provenances.
clear() - Method in class org.tribuo.MutableFeatureMap
Clears all the feature observations.
clear() - Method in interface org.tribuo.MutableOutputInfo
Clears the OutputInfo, removing all things it's observed.
clear() - Method in class org.tribuo.regression.MutableRegressionInfo
 
clear() - Method in class org.tribuo.sequence.MutableSequenceDataset
Clears all the examples out of this dataset, and flushes the FeatureMap, OutputInfo, and transform provenances.
clear() - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
clearAlgorithm() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
clearAttribute() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
clearBegin() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 begin = 1;
clearDataLocation() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
clearDataType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The data type of the tensor.
clearDenotation() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
clearDenotation() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
clearDim() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
clearDimParam() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
namespace Shape
clearDims() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
clearDims() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The shape of the tensor.
clearDimValue() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
int64 dim_value = 1;
clearDocString() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
A human-readable documentation for this attribute.
clearDocString() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A human-readable documentation for this graph.
clearDocString() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
A human-readable documentation for this model.
clearDocString() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
A human-readable documentation for this node.
clearDocString() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
A human-readable documentation for this tensor.
clearDocString() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
A human-readable documentation for this value.
clearDomain() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Domain name of the model.
clearDomain() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The domain of the OperatorSet that specifies the operator named by op_type.
clearDomain() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The domain of the operator set being identified.
clearDomain() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
When missing, the domain is the same as the model's.
clearDoubleData() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
clearElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
clearElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
clearElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
clearEnd() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 end = 2;
clearExternalData() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
clearF() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
Exactly ONE of the following fields must be present for this version of the IR
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
clearField(Descriptors.FieldDescriptor) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
clearFloatData() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
clearFloats() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of floats
clearG() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
clearGraph() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
clearGraphs() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
clearI() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
int
clearIndices() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
clearInitialization() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
clearInitializationBinding() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
clearInitializer() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
clearInput() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
clearInput() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
clearInt32Data() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
clearInt64Data() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int64.
clearInts() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of ints
clearIrVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the IR this model targets.
clearKey() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string key = 1;
clearKeyType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
clearMapType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
clearMetadataProps() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
clearModelVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the graph encoded.
clearName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The name field MUST be present for this version of the IR.
clearName() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The name of the graph.
clearName() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
An optional identifier for this node in a graph.
clearName() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Optionally, a name for the tensor.
clearName() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
The name is optional but significant when provided.
clearName() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR.
clearNode() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
clearOneof(Descriptors.OneofDescriptor) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
clearOpaqueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
clearOpsetImport() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
clearOpType() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The symbolic identifier of the Operator to execute.
clearOutput() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
clearOutput() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
clearProducerName() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The name of the framework or tool used to generate this model.
clearProducerVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the framework or tool used to generate this model.
clearQuantizationAnnotation() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
clearQuantParameterTensorNames() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
clearRawData() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Serializations can either use one of the fields above, or use this raw bytes field.
clearRefAttrName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
clearS() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
UTF-8 string
clearSegment() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
clearSequenceType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
clearShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
clearShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
clearSparseInitializer() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
clearSparseTensor() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
clearSparseTensors() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
clearSparseTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
clearStringData() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For strings.
clearStrings() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of UTF-8 strings
clearT() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
clearTensorName() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
optional string tensor_name = 1;
clearTensors() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
clearTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
clearTrainingInfo() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
clearType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The type field MUST be present for this version of the IR.
clearType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
clearUint64Data() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
clearUpdateBinding() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
clearValue() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string value = 2;
clearValue() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
clearValue() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
clearValueInfo() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
clearValues() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
clearValueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
clearVersion() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The version of the operator set being identified.
clone() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
clone() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
clone() - Method in class org.tribuo.Feature
 
clone() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.WhitespaceTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
 
clone() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
clone() - Method in interface org.tribuo.util.tokens.Tokenizer
Clones a tokenizer with it's configuration.
clone() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
close() - Method in class org.tribuo.data.csv.CSVIterator
 
close() - Method in class org.tribuo.data.sql.SQLDataSource
 
close() - Method in class org.tribuo.interop.oci.OCIModel
 
close() - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
close() - Method in class org.tribuo.interop.onnx.ONNXExternalModel
 
close() - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceModel
Close the session and graph if they exist.
close() - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
 
close() - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
 
close() - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
 
close() - Method in class org.tribuo.interop.tensorflow.TensorMap
 
close() - Method in class org.tribuo.json.JsonFileIterator
 
closed - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
closeTensorCollection(Collection<Tensor>) - Static method in class org.tribuo.interop.tensorflow.TensorFlowUtil
Closes a collection of Tensors.
CLS - Enum constant in enum class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.OutputPooling
Returns the CLS embedding.
CLS_AND_MEAN - Enum constant in enum class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.OutputPooling
Takes the average of the token embeddings and the CLS token.
CLS_OUTPUT - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Output name for the classification token output.
clusterCounts - Variable in class org.tribuo.clustering.ClusteringInfo
 
ClusterID - Class in org.tribuo.clustering
A clustering id.
ClusterID(int) - Constructor for class org.tribuo.clustering.ClusterID
Creates a ClusterID with the sentinel score of Double.NaN.
ClusterID(int, double) - Constructor for class org.tribuo.clustering.ClusterID
Creates a ClusterID with the specified id number and score.
CLUSTERING - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Clustering, maps to Tribuo's ClusterID.
ClusteringDataGenerator - Class in org.tribuo.clustering.example
Generates three example train and test datasets, used for unit testing.
ClusteringDataGenerator() - Constructor for class org.tribuo.clustering.example.ClusteringDataGenerator
 
ClusteringEvaluation - Interface in org.tribuo.clustering.evaluation
An Evaluation for clustering tasks.
ClusteringEvaluator - Class in org.tribuo.clustering.evaluation
A Evaluator for clustering using ClusterIDs.
ClusteringEvaluator() - Constructor for class org.tribuo.clustering.evaluation.ClusteringEvaluator
 
ClusteringFactory - Class in org.tribuo.clustering
A factory for making ClusterID related classes.
ClusteringFactory() - Constructor for class org.tribuo.clustering.ClusteringFactory
ClusteringFactory is stateless and immutable, but we need to be able to construct them via the config system.
ClusteringFactory.ClusteringFactoryProvenance - Class in org.tribuo.clustering
Provenance for ClusteringFactory.
ClusteringFactoryProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.clustering.ClusteringFactory.ClusteringFactoryProvenance
Rebuilds a clustering factory provenance from the marshalled form.
ClusteringInfo - Class in org.tribuo.clustering
The base class for a ClusterID OutputInfo.
ClusteringMetric - Class in org.tribuo.clustering.evaluation
A metric for evaluating clustering problems.
ClusteringMetric(MetricTarget<ClusterID>, String, BiFunction<MetricTarget<ClusterID>, ClusteringMetric.Context, Double>) - Constructor for class org.tribuo.clustering.evaluation.ClusteringMetric
Constructs a clustering metric using the supplied parameters.
ClusteringMetrics - Enum Class in org.tribuo.clustering.evaluation
Default metrics for evaluating clusterings.
cmi(List<T1>, List<T2>, Set<List<T3>>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the conditional mutual information between first and second conditioned on the set.
CNNExamples - Class in org.tribuo.interop.tensorflow.example
Static factory methods which produce Convolutional Neural Network architectures.
coeff - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
Intercept in kernel function.
COLUMNAR - Enum constant in enum class org.tribuo.data.DataOptions.InputFormat
A CSV file parsed using a configured RowProcessor.
ColumnarDataSource<T extends Output<T>> - Class in org.tribuo.data.columnar
A ConfigurableDataSource base class which takes columnar data (e.g., csv or DB table rows) and generates Examples.
ColumnarDataSource() - Constructor for class org.tribuo.data.columnar.ColumnarDataSource
For OLCUT.
ColumnarDataSource(OutputFactory<T>, RowProcessor<T>, boolean) - Constructor for class org.tribuo.data.columnar.ColumnarDataSource
Constructs a columnar data source with the specified parameters.
ColumnarExplainer<T extends Output<T>> - Interface in org.tribuo.classification.explanations
An explainer for data using Tribuo's columnar data package.
ColumnarFeature - Class in org.tribuo.data.columnar
A Feature with extra bookkeeping for use inside the columnar package.
ColumnarFeature(String, double) - Constructor for class org.tribuo.data.columnar.ColumnarFeature
Constructs a ColumnarFeature from the field name.
ColumnarFeature(String, String, double) - Constructor for class org.tribuo.data.columnar.ColumnarFeature
Constructs a ColumnarFeature from the field name, column entry and value.
ColumnarFeature(String, String, String, double) - Constructor for class org.tribuo.data.columnar.ColumnarFeature
Constructs a ColumnarFeature which is the conjunction of features from two fields.
ColumnarIterator - Class in org.tribuo.data.columnar
An abstract class for iterators that read data in to a columnar format, usually from a file of some kind.
ColumnarIterator() - Constructor for class org.tribuo.data.columnar.ColumnarIterator
Constructs a ColumnarIterator wrapped around a buffering spliterator.
ColumnarIterator(int, int, long) - Constructor for class org.tribuo.data.columnar.ColumnarIterator
Constructs a ColumnarIterator wrapped around a buffering spliterator.
ColumnarIterator.Row - Class in org.tribuo.data.columnar
A representation of a row of untyped data from a columnar data source.
columnSum() - Method in class org.tribuo.math.la.DenseMatrix
Returns the dense vector containing each column sum.
columnSum(int) - Method in class org.tribuo.math.la.DenseMatrix
Calculates the sum of the specified column.
combine(ImmutableOutputInfo<Label>, List<Prediction<Label>>) - Method in class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
 
combine(ImmutableOutputInfo<Label>, List<Prediction<Label>>) - Method in class org.tribuo.classification.ensemble.VotingCombiner
 
combine(ImmutableOutputInfo<Label>, List<Prediction<Label>>, float[]) - Method in class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
 
combine(ImmutableOutputInfo<Label>, List<Prediction<Label>>, float[]) - Method in class org.tribuo.classification.ensemble.VotingCombiner
 
combine(ImmutableOutputInfo<MultiLabel>, List<Prediction<MultiLabel>>) - Method in class org.tribuo.multilabel.ensemble.MultiLabelVotingCombiner
 
combine(ImmutableOutputInfo<MultiLabel>, List<Prediction<MultiLabel>>, float[]) - Method in class org.tribuo.multilabel.ensemble.MultiLabelVotingCombiner
 
combine(ImmutableOutputInfo<Regressor>, List<Prediction<Regressor>>) - Method in class org.tribuo.regression.ensemble.AveragingCombiner
 
combine(ImmutableOutputInfo<Regressor>, List<Prediction<Regressor>>, float[]) - Method in class org.tribuo.regression.ensemble.AveragingCombiner
 
combine(ImmutableOutputInfo<T>, List<Prediction<T>>) - Method in interface org.tribuo.ensemble.EnsembleCombiner
Combine the predictions.
combine(ImmutableOutputInfo<T>, List<Prediction<T>>, float[]) - Method in interface org.tribuo.ensemble.EnsembleCombiner
Combine the supplied predictions.
combiner - Variable in class org.tribuo.ensemble.BaggingTrainer
 
combiner - Variable in class org.tribuo.ensemble.WeightedEnsembleModel
 
COMMA - Enum constant in enum class org.tribuo.data.DataOptions.Delimiter
Comma separator.
compareTo(Feature) - Method in class org.tribuo.Feature
 
compareTo(MatrixIterator) - Method in interface org.tribuo.math.la.MatrixIterator
 
compareTo(VectorIterator) - Method in interface org.tribuo.math.la.VectorIterator
 
compareTo(InvertedFeature) - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
 
compartmentID - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Compartment ID.
compartmentID - Variable in class org.tribuo.interop.oci.OCIUtil.OCIDSConfig
OCI compartment ID.
CompletelyConfigurableTrainTest - Class in org.tribuo.data
Build and run a predictor for a standard dataset.
CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions - Class in org.tribuo.data
Command line options.
COMPLEX128 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
complex with float64 real and imaginary components
COMPLEX128_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
complex with float64 real and imaginary components
COMPLEX64 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
complex with float32 real and imaginary components
COMPLEX64_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
complex with float32 real and imaginary components
compute(C) - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
Compute the result of this metric from the input context.
compute(AnomalyMetric.Context) - Method in class org.tribuo.anomaly.evaluation.AnomalyMetric
 
compute(LabelMetric.Context) - Method in class org.tribuo.classification.evaluation.LabelMetric
 
compute(ClusteringMetric.Context) - Method in class org.tribuo.clustering.evaluation.ClusteringMetric
 
compute(MultiLabelMetric.Context) - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
 
compute(RegressionMetric.Context) - Method in class org.tribuo.regression.evaluation.RegressionMetric
 
computeDepth(int, Node<T>) - Static method in class org.tribuo.common.tree.TreeModel
 
computeResults(C, Set<? extends EvaluationMetric<T, C>>) - Method in class org.tribuo.evaluation.AbstractEvaluator
Computes each metric given the context.
computeResults(C, Set<? extends EvaluationMetric<T, C>>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Computes each metric given the context.
CONCAT - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Concatenates tensors.
ConcentricCirclesDataSource - Class in org.tribuo.classification.example
A data source for two concentric circles, one per class.
ConcentricCirclesDataSource(int, long, double, double) - Constructor for class org.tribuo.classification.example.ConcentricCirclesDataSource
Constructs a data source for two concentric circles, one per class.
condaName - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
OCI DS conda environment name.
condaName - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
The Conda environment name.
condaPath - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
OCI DS conda environment path in object storage.
condaPath - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
The Conda environment path in object storage.
conditionalEntropy(List<T1>, List<T2>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon conditional entropy of two arrays, using histogram probability estimators.
conditionalMI(List<T1>, List<T2>, List<T3>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon conditional mutual information, using histogram probability estimators.
conditionalMI(List<T1>, List<T2>, List<T3>, List<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted conditional mutual information, using histogram probability estimators.
conditionalMI(TripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon conditional mutual information, using histogram probability estimators.
conditionalMI(TripleDistribution<T1, T2, T3>, Map<?, Double>, WeightedInformationTheory.VariableSelector) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted conditional mutual information, using histogram probability estimators.
conditionalMI(WeightedTripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted conditional mutual information, using histogram probability estimators.
conditionalMIFlipped(TripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon conditional mutual information, using histogram probability estimators.
ConfidencePredictingSequenceModel - Class in org.tribuo.classification.sequence
A Sequence model which can provide confidence predictions for subsequence predictions.
ConfidencePredictingSequenceModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>) - Constructor for class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel
Constructs a ConfidencePredictingSequenceModel with the supplied parameters.
ConfidencePredictingSequenceModel.Subsequence - Class in org.tribuo.classification.sequence
A range class used to define a subsequence of a SequenceExample.
ConfigurableDataSource<T extends Output<T>> - Interface in org.tribuo
It's a DataSource that's also Configurable.
ConfigurableTestOptions() - Constructor for class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
ConfigurableTrainTest - Class in org.tribuo.classification.experiments
Build and run a classifier for a standard dataset.
ConfigurableTrainTest - Class in org.tribuo.data
Build and run a predictor for a standard dataset.
ConfigurableTrainTest() - Constructor for class org.tribuo.classification.experiments.ConfigurableTrainTest
 
ConfigurableTrainTest.ConfigurableTrainTestOptions - Class in org.tribuo.classification.experiments
Command line options.
ConfigurableTrainTest.ConfigurableTrainTestOptions - Class in org.tribuo.data
Command line options.
ConfigurableTrainTestOptions() - Constructor for class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
ConfigurableTrainTestOptions() - Constructor for class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
ConfigurableTrainTestOptions() - Constructor for class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
configured - Variable in class org.tribuo.data.columnar.RowProcessor
 
ConfiguredDataSourceProvenance - Interface in org.tribuo.provenance
A tag interface for configurable data source provenance.
confusion(Label, Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
confusion(Label, Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Note: confusion is not stored in the underlying map, so it won't show up in aggregation.
confusion(MultiLabel, MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
confusion(MultiLabel, MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
confusion(T, T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the number of times label truth was predicted as label predicted.
confusion(T, T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of times the supplied predicted label was returned for the supplied true class.
ConfusionMatrix<T extends Classifiable<T>> - Interface in org.tribuo.classification.evaluation
A confusion matrix for Classifiables.
ConfusionMetrics - Class in org.tribuo.classification.evaluation
Static functions for computing classification metrics based on a ConfusionMatrix.
confusionString() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns a confusion matrix formatted String for display.
CONJUNCTION - Static variable in class org.tribuo.data.columnar.ColumnarFeature
The string used as the field name of conjunction features.
connString - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
Connection string to the SQL database
constant(String, float) - Method in class org.tribuo.util.onnx.ONNXContext
Creates a float scalar constant for this ONNXContext.
constant(String, long) - Method in class org.tribuo.util.onnx.ONNXContext
Creates a long scalar constant for this ONNXContext.
CONSTANT - Enum constant in enum class org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Returns the supplied label for all inputs.
CONSTANT - Enum constant in enum class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns the specified constant value.
CONSTANT_OF_SHAPE - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
 
CONSTANTSGD - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
SGD with a constant learning rate.
CONSTRAINED_BP - Enum constant in enum class org.tribuo.classification.sgd.crf.CRFModel.ConfidenceType
Constrained Belief Propagation from "Confidence Estimation for Information Extraction" Culotta and McCallum 2004.
constrainedBeliefPropagation(ChainHelper.ChainCliqueValues, int[]) - Static method in class org.tribuo.classification.sgd.crf.ChainHelper
Runs constrained belief propagation on a linear chain CRF.
constructFromLists(List<T1>, List<T2>) - Static method in class org.tribuo.util.infotheory.impl.PairDistribution
Generates the counts for two vectors.
constructFromLists(List<T1>, List<T2>, List<Double>) - Static method in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
Generates the counts for two vectors.
constructFromLists(List<T1>, List<T2>, List<T3>) - Static method in class org.tribuo.util.infotheory.impl.TripleDistribution
Constructs a TripleDistribution from three lists of the same length.
constructFromLists(List<T1>, List<T2>, List<T3>, List<Double>) - Static method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
Constructs a WeightedTripleDistribution from three lists of the same length and a list of weights of the same length.
constructFromMap(Map<CachedPair<T1, T2>, MutableLong>) - Static method in class org.tribuo.util.infotheory.impl.PairDistribution
Constructs a distribution from a joint count.
constructFromMap(Map<CachedPair<T1, T2>, MutableLong>, int, int) - Static method in class org.tribuo.util.infotheory.impl.PairDistribution
Constructs a distribution from a joint count.
constructFromMap(Map<CachedPair<T1, T2>, MutableLong>, Map<T1, MutableLong>, Map<T2, MutableLong>) - Static method in class org.tribuo.util.infotheory.impl.PairDistribution
Constructs a joint distribution from the counts.
constructFromMap(Map<CachedPair<T1, T2>, WeightCountTuple>) - Static method in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
Generates a WeightedPairDistribution by generating the marginal distributions for the first and second elements.
constructFromMap(Map<CachedTriple<T1, T2, T3>, MutableLong>) - Static method in class org.tribuo.util.infotheory.impl.TripleDistribution
Constructs a TripleDistribution by marginalising the supplied joint distribution.
constructFromMap(Map<CachedTriple<T1, T2, T3>, MutableLong>, int, int, int, int, int, int) - Static method in class org.tribuo.util.infotheory.impl.TripleDistribution
Constructs a TripleDistribution by marginalising the supplied joint distribution.
constructFromMap(Map<CachedTriple<T1, T2, T3>, MutableLong>, Map<CachedPair<T1, T2>, MutableLong>, Map<CachedPair<T1, T3>, MutableLong>, Map<CachedPair<T2, T3>, MutableLong>, Map<T1, MutableLong>, Map<T2, MutableLong>, Map<T3, MutableLong>) - Static method in class org.tribuo.util.infotheory.impl.TripleDistribution
Constructs a TripleDistribution by marginalising the supplied joint distribution.
constructFromMap(Map<CachedTriple<T1, T2, T3>, WeightCountTuple>) - Static method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
Constructs a WeightedTripleDistribution by marginalising the supplied joint distribution.
constructInfoForExternalModel(Map<Event, Integer>) - Method in class org.tribuo.anomaly.AnomalyFactory
 
constructInfoForExternalModel(Map<Label, Integer>) - Method in class org.tribuo.classification.LabelFactory
 
constructInfoForExternalModel(Map<ClusterID, Integer>) - Method in class org.tribuo.clustering.ClusteringFactory
Unlike the other info types, clustering directly uses the integer IDs as the stored value, so this mapping discards the cluster IDs and just uses the supplied integers.
constructInfoForExternalModel(Map<MultiLabel, Integer>) - Method in class org.tribuo.multilabel.MultiLabelFactory
 
constructInfoForExternalModel(Map<Regressor, Integer>) - Method in class org.tribuo.regression.RegressionFactory
 
constructInfoForExternalModel(Map<T, Integer>) - Method in interface org.tribuo.OutputFactory
Creates an ImmutableOutputInfo from the supplied mapping.
contains(int) - Method in class org.tribuo.impl.IndexedArrayExample
Does this example contain a feature with id i.
contains(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
 
contains(String) - Method in class org.tribuo.multilabel.MultiLabel
Does this MultiLabel contain this string?
contains(Label) - Method in class org.tribuo.multilabel.MultiLabel
Does this MultiLabel contain this Label?
containsAll(Collection<?>) - Method in class org.tribuo.util.infotheory.impl.RowList
 
containsMetadata(String) - Method in class org.tribuo.Example
Test if the metadata contains the supplied key.
context - Variable in class org.tribuo.util.onnx.ONNXRef
 
Context(Model<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelMetric.Context
Constructs a context and compute the confusion matrix using the specified model and predictions.
Context(SequenceModel<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelMetric.Context
Constructs a context and compute the confusion matrix using the specified model and predictions.
convert(byte) - Static method in enum class org.tribuo.datasource.IDXDataSource.IDXType
Converts the byte into the enum.
convert(List<? extends Example<?>>, ImmutableFeatureMap) - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
convert(List<? extends Example<?>>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.FeatureConverter
Converts a batch of Examples into a single TensorMap suitable for supplying as an input to a graph.
convert(List<? extends Example<?>>, ImmutableFeatureMap) - Method in class org.tribuo.interop.tensorflow.ImageConverter
Transform implicitly pads unseen values with zero.
convert(List<? extends SGDVector>) - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
convert(List<? extends SGDVector>) - Method in interface org.tribuo.interop.tensorflow.FeatureConverter
Converts a list of SGDVectors representing a batch of features into a TensorMap.
convert(List<? extends SGDVector>) - Method in class org.tribuo.interop.tensorflow.ImageConverter
 
convert(Example<?>, ImmutableFeatureMap) - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
convert(Example<?>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.FeatureConverter
Converts an Example into a TensorMap suitable for supplying as an input to a graph.
convert(Example<?>, ImmutableFeatureMap) - Method in class org.tribuo.interop.tensorflow.ImageConverter
Transform implicitly pads unseen values with zero.
convert(SGDVector) - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
convert(SGDVector) - Method in interface org.tribuo.interop.tensorflow.FeatureConverter
Converts a SGDVector representing the features into a TensorMap.
convert(SGDVector) - Method in class org.tribuo.interop.tensorflow.ImageConverter
 
convert(SequenceExample<Label>, ImmutableFeatureMap, ImmutableOutputInfo<Label>) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
convert(SequenceExample<T>, ImmutableFeatureMap) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
convertBatchOutput(ImmutableOutputInfo<Label>, List<float[][]>, int[], Example<Label>[]) - Method in class org.tribuo.classification.xgboost.XGBoostClassificationConverter
 
convertBatchOutput(ImmutableOutputInfo<Regressor>, List<float[][]>, int[], Example<Regressor>[]) - Method in class org.tribuo.regression.xgboost.XGBoostRegressionConverter
 
convertBatchOutput(ImmutableOutputInfo<T>, List<float[][]>, int[], Example<T>[]) - Method in interface org.tribuo.common.xgboost.XGBoostOutputConverter
Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.
convertDataset(Dataset<T>) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
 
convertDataset(Dataset<T>, Function<T, Float>) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
 
convertExample(Example<T>, ImmutableFeatureMap) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
 
convertExample(Example<T>, ImmutableFeatureMap, Function<T, Float>) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
Converts an examples into a DMatrix.
convertExamples(Iterable<Example<T>>, ImmutableFeatureMap) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
 
convertExamples(Iterable<Example<T>>, ImmutableFeatureMap, Function<T, Float>) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
Converts an iterable of examples into a DMatrix.
convertFeatures(SparseVector) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
convertFeatures(SparseVector) - Method in class org.tribuo.interop.ExternalModel
Converts from a SparseVector using the external model's indices into the ingestion format for the external model.
convertFeatures(SparseVector) - Method in class org.tribuo.interop.oci.OCIModel
 
convertFeatures(SparseVector) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
 
convertFeatures(SparseVector) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
 
convertFeatures(SparseVector) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
 
convertFeaturesList(List<SparseVector>) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
convertFeaturesList(List<SparseVector>) - Method in class org.tribuo.interop.ExternalModel
Converts from a list of SparseVector using the external model's indices into the ingestion format for the external model.
convertFeaturesList(List<SparseVector>) - Method in class org.tribuo.interop.oci.OCIModel
 
convertFeaturesList(List<SparseVector>) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
 
convertFeaturesList(List<SparseVector>) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
 
convertFeaturesList(List<SparseVector>) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
 
convertOutput(float[][], int[], List<Example<T>>) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
convertOutput(float[][], int, Example<T>) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
convertOutput(List<OnnxValue>, int[], List<Example<T>>) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
Converts a tensor into a prediction.
convertOutput(List<OnnxValue>, int, Example<T>) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
Converts a tensor into a prediction.
convertOutput(Tensor, int[], List<Example<T>>) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
Converts a tensor into a prediction.
convertOutput(Tensor, int, Example<T>) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
Converts a tensor into a prediction.
convertOutput(ImmutableOutputInfo<Label>, List<float[]>, int, Example<Label>) - Method in class org.tribuo.classification.xgboost.XGBoostClassificationConverter
 
convertOutput(ImmutableOutputInfo<Regressor>, List<float[]>, int, Example<Regressor>) - Method in class org.tribuo.regression.xgboost.XGBoostRegressionConverter
 
convertOutput(ImmutableOutputInfo<T>, List<float[]>, int, Example<T>) - Method in interface org.tribuo.common.xgboost.XGBoostOutputConverter
Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.
convertOutput(TensorMap, int[], List<Example<T>>) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
Converts a tensor into a prediction.
convertOutput(TensorMap, int, Example<T>) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
Converts a tensor into a prediction.
convertOutput(DenseMatrix, int[], List<Example<Label>>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.oci.OCILabelConverter
 
convertOutput(DenseMatrix, int[], List<Example<MultiLabel>>, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
 
convertOutput(DenseMatrix, int[], List<Example<Regressor>>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.oci.OCIRegressorConverter
 
convertOutput(DenseMatrix, int[], List<Example<T>>) - Method in class org.tribuo.interop.oci.OCIModel
 
convertOutput(DenseMatrix, int[], List<Example<T>>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.oci.OCIOutputConverter
Converts a dense matrix into a list of predictions of the appropriate type.
convertOutput(DenseMatrix, int, Example<T>) - Method in class org.tribuo.interop.oci.OCIModel
 
convertOutput(DenseVector, int, Example<Label>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.oci.OCILabelConverter
 
convertOutput(DenseVector, int, Example<MultiLabel>, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
 
convertOutput(DenseVector, int, Example<Regressor>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.oci.OCIRegressorConverter
 
convertOutput(DenseVector, int, Example<T>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.oci.OCIOutputConverter
Converts a dense vector into a single prediction of the appropriate type.
convertOutput(V, int[], List<Example<T>>) - Method in class org.tribuo.interop.ExternalModel
Converts the output of the external model into a list of Predictions.
convertOutput(V, int, Example<T>) - Method in class org.tribuo.interop.ExternalModel
Converts the output of the external model into a Prediction.
convertSingleExample(Example<T>, ImmutableFeatureMap, ArrayList<Float>, ArrayList<Integer>, ArrayList<Long>, long) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
Writes out the features from an example into the three supplied ArrayLists.
convertSparseVector(SparseVector) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
Used when predicting with an externally trained XGBoost model.
convertSparseVectors(List<SparseVector>) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
Used when predicting with an externally trained XGBoost model.
convertToBatchOutput(Tensor, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToBatchOutput(Tensor, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToBatchOutput(Tensor, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToBatchOutput(Tensor, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor containing multiple outputs into a list of Outputs.
convertToBatchPrediction(Tensor, ImmutableOutputInfo<Label>, int[], List<Example<Label>>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToBatchPrediction(Tensor, ImmutableOutputInfo<MultiLabel>, int[], List<Example<MultiLabel>>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToBatchPrediction(Tensor, ImmutableOutputInfo<Regressor>, int[], List<Example<Regressor>>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToBatchPrediction(Tensor, ImmutableOutputInfo<T>, int[], List<Example<T>>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor containing multiple outputs into a list of Predictions.
convertToCheckpointModel(String, String) - Method in class org.tribuo.interop.tensorflow.TensorFlowNativeModel
Creates a TensorFlowCheckpointModel version of this model.
convertToDense() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
convertToDense() - Method in interface org.tribuo.math.optimisers.util.ShrinkingTensor
Converts the tensor into a dense tensor.
convertToDense() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
convertToDenseVector(ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.multilabel.MultiLabel
Converts this MultiLabel into a DenseVector using the indices from the output info.
convertToMap(ObjectNode) - Static method in class org.tribuo.json.JsonUtil
Converts a Json node into a Map from String to String for use in downstream processing by RowProcessor.
convertToNativeModel() - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Creates a TensorFlowNativeModel version of this model.
convertToOutput(Tensor, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToOutput(Tensor, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToOutput(Tensor, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToOutput(Tensor, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor into the specified output type.
convertToPrediction(Tensor, ImmutableOutputInfo<Label>, int, Example<Label>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToPrediction(Tensor, ImmutableOutputInfo<MultiLabel>, int, Example<MultiLabel>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToPrediction(Tensor, ImmutableOutputInfo<Regressor>, int, Example<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToPrediction(Tensor, ImmutableOutputInfo<T>, int, Example<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor into a Prediction.
convertToSparseVector(ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.multilabel.MultiLabel
Converts this MultiLabel into a SparseVector using the indices from the output info.
convertToTensor(List<Example<Label>>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToTensor(List<Example<MultiLabel>>, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToTensor(List<Example<Regressor>>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToTensor(List<Example<T>>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a list of Example into a Tensor representing all the outputs in the list.
convertToTensor(Label, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToTensor(MultiLabel, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToTensor(Regressor, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToTensor(T, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts an Output into a Tensor representing it's output.
convertToVector(SequenceExample<Label>, ImmutableFeatureMap, ImmutableOutputInfo<Label>) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
Converts a SequenceExample into an array of SGDVectors and labels suitable for CRF prediction.
convertToVector(SequenceExample<T>, ImmutableFeatureMap) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
Converts a SequenceExample into an array of SGDVectors suitable for CRF prediction.
convertTree() - Method in class org.tribuo.classification.dtree.impl.ClassifierTrainingNode
Generates a test time tree (made of SplitNode and LeafNode) from the tree rooted at this node.
convertTree() - Method in class org.tribuo.common.tree.AbstractTrainingNode
Converts a tree from a training representation to the final inference time representation.
convertTree() - Method in class org.tribuo.regression.rtree.impl.JointRegressorTrainingNode
Generates a test time tree (made of SplitNode and LeafNode) from the tree rooted at this node.
convertTree() - Method in class org.tribuo.regression.rtree.impl.RegressorTrainingNode
Generates a test time tree (made of SplitNode and LeafNode) from the tree rooted at this node.
copy() - Method in class org.tribuo.anomaly.AnomalyInfo
 
copy() - Method in class org.tribuo.anomaly.Event
 
copy() - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
copy() - Method in class org.tribuo.anomaly.MutableAnomalyInfo
 
copy() - Method in class org.tribuo.CategoricalIDInfo
 
copy() - Method in class org.tribuo.CategoricalInfo
 
copy() - Method in class org.tribuo.classification.ImmutableLabelInfo
 
copy() - Method in class org.tribuo.classification.Label
 
copy() - Method in class org.tribuo.classification.LabelInfo
 
copy() - Method in class org.tribuo.classification.MutableLabelInfo
 
copy() - Method in class org.tribuo.clustering.ClusterID
 
copy() - Method in class org.tribuo.clustering.ClusteringInfo
 
copy() - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
copy() - Method in class org.tribuo.clustering.MutableClusteringInfo
 
copy() - Method in class org.tribuo.common.sgd.FMParameters
 
copy() - Method in class org.tribuo.common.tree.AbstractTrainingNode
 
copy() - Method in class org.tribuo.common.tree.impl.IntArrayContainer
Returns a copy of the elements in use.
copy() - Method in class org.tribuo.common.tree.LeafNode
 
copy() - Method in interface org.tribuo.common.tree.Node
Copies the node and it's children.
copy() - Method in class org.tribuo.common.tree.SplitNode
 
copy() - Method in class org.tribuo.data.columnar.RowProcessor
Deprecated.
In a future release this API will change, in the meantime this is the correct way to get a row processor with clean state.

When using regexMappingProcessors, RowProcessor is stateful in a way that can sometimes make it fail the second time it is used. Concretely:

     RowProcessor rp;
     Dataset ds1 = new MutableDataset(new CSVDataSource(csvfile1, rp));
     Dataset ds2 = new MutableDataset(new CSVDataSource(csvfile2, rp)); // this may fail due to state in rp
 
This method returns a RowProcessor with clean state and the same configuration as this row processor.
copy() - Method in class org.tribuo.Example
Returns a deep copy of this Example.
copy() - Method in class org.tribuo.impl.ArrayExample
 
copy() - Method in class org.tribuo.impl.BinaryFeaturesExample
 
copy() - Method in class org.tribuo.impl.IndexedArrayExample
 
copy() - Method in class org.tribuo.impl.ListExample
 
copy() - Method in interface org.tribuo.math.FeedForwardParameters
Returns a copy of the parameters.
copy() - Method in class org.tribuo.math.la.DenseMatrix
Copies the matrix.
copy() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
copy() - Method in class org.tribuo.math.la.DenseVector
 
copy() - Method in interface org.tribuo.math.la.Matrix
Copies the matrix.
copy() - Method in interface org.tribuo.math.la.SGDVector
Returns a deep copy of this vector.
copy() - Method in class org.tribuo.math.la.SparseVector
 
copy() - Method in interface org.tribuo.math.la.Tensor
Returns a copy of this Tensor.
copy() - Method in class org.tribuo.math.LinearParameters
 
copy() - Method in class org.tribuo.math.optimisers.AdaDelta
 
copy() - Method in class org.tribuo.math.optimisers.AdaGrad
 
copy() - Method in class org.tribuo.math.optimisers.AdaGradRDA
 
copy() - Method in class org.tribuo.math.optimisers.Adam
 
copy() - Method in class org.tribuo.math.optimisers.ParameterAveraging
 
copy() - Method in class org.tribuo.math.optimisers.Pegasos
 
copy() - Method in class org.tribuo.math.optimisers.RMSProp
 
copy() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
copy() - Method in interface org.tribuo.math.StochasticGradientOptimiser
Copies a gradient optimiser with it's configuration.
copy() - Method in class org.tribuo.Model
Copies a model, returning a deep copy of any mutable state, and a shallow copy otherwise.
copy() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
copy() - Method in class org.tribuo.multilabel.MultiLabel
 
copy() - Method in class org.tribuo.multilabel.MultiLabelInfo
 
copy() - Method in class org.tribuo.multilabel.MutableMultiLabelInfo
 
copy() - Method in interface org.tribuo.Output
Deep copy of the output up to it's immutable state.
copy() - Method in interface org.tribuo.OutputInfo
Generates a copy of this OutputInfo, including it's mutability.
copy() - Method in class org.tribuo.RealIDInfo
 
copy() - Method in class org.tribuo.RealInfo
 
copy() - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
copy() - Method in class org.tribuo.regression.MutableRegressionInfo
 
copy() - Method in class org.tribuo.regression.RegressionInfo
 
copy() - Method in class org.tribuo.regression.Regressor
 
copy() - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
copy() - Method in class org.tribuo.sequence.SequenceExample
Returns a deep copy of this SequenceExample.
copy() - Method in class org.tribuo.SparseModel
 
copy() - Method in interface org.tribuo.VariableInfo
Returns a copy of this variable info.
copy(String) - Method in interface org.tribuo.data.columnar.FieldProcessor
Returns a copy of this FieldProcessor bound to the supplied newFieldName.
copy(String) - Method in class org.tribuo.data.columnar.processors.field.DateFieldProcessor
 
copy(String) - Method in class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
 
copy(String) - Method in class org.tribuo.data.columnar.processors.field.IdentityProcessor
 
copy(String) - Method in class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
 
copy(String) - Method in class org.tribuo.data.columnar.processors.field.TextFieldProcessor
Note: the copy shares the text pipeline with the original.
copy(String, EnsembleModelProvenance, List<Model<T>>) - Method in class org.tribuo.ensemble.EnsembleModel
Copies this ensemble model.
copy(String, EnsembleModelProvenance, List<Model<T>>) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.baseline.DummyClassifierModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.sgd.fm.FMClassificationModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.sgd.linear.LinearSGDModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.clustering.hdbscan.HdbscanModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.clustering.kmeans.KMeansModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.common.nearest.KNNModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.common.tree.TreeModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.common.xgboost.XGBoostModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.ensemble.EnsembleModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.interop.oci.OCIModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.interop.tensorflow.TensorFlowNativeModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.Model
Copies a model, replacing its provenance and name with the supplied values.
copy(String, ModelProvenance) - Method in class org.tribuo.multilabel.baseline.ClassifierChainModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.baseline.DummyRegressionModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.sgd.fm.FMRegressionModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.sgd.linear.LinearSGDModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.slm.SparseLinearModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.transform.TransformedModel
 
copyDataset(Dataset<T>) - Static method in class org.tribuo.ImmutableDataset
Creates an immutable deep copy of the supplied dataset.
copyDataset(Dataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Static method in class org.tribuo.ImmutableDataset
Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
copyDataset(Dataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, Merger) - Static method in class org.tribuo.ImmutableDataset
Creates an immutable deep copy of the supplied dataset.
copyDataset(SequenceDataset<T>) - Static method in class org.tribuo.sequence.ImmutableSequenceDataset
Creates an immutable deep copy of the supplied dataset.
copyDataset(SequenceDataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Static method in class org.tribuo.sequence.ImmutableSequenceDataset
Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
copyDataset(SequenceDataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, Merger) - Static method in class org.tribuo.sequence.ImmutableSequenceDataset
Creates an immutable deep copy of the supplied dataset.
copyModel(Model) - Static method in class org.tribuo.common.liblinear.LibLinearModel
Copies the model by writing it out to a String and loading it back in.
copyModel(svm_model) - Static method in class org.tribuo.common.libsvm.LibSVMModel
Copies an svm_model, as it does not provide a copy method.
copyParameters(svm_parameter) - Static method in class org.tribuo.common.libsvm.SVMParameters
Deep copy of the svm_parameters including the arrays.
copyParams(Map<String, ?>) - Method in class org.tribuo.common.xgboost.XGBoostTrainer
Returns a copy of the supplied parameter map which has the appropriate type for passing to XGBoost.train.
copyResourceToTmp(String) - Static method in class org.tribuo.tests.Resources
Copies a classpath resource to a temporary file.
copyValues(int) - Method in class org.tribuo.impl.ArrayExample
Returns a copy of the feature values array at the specific size.
CoreTokenizerOptions - Class in org.tribuo.util.tokens.options
CLI Options for all the tokenizers in the core package.
CoreTokenizerOptions() - Constructor for class org.tribuo.util.tokens.options.CoreTokenizerOptions
 
CoreTokenizerOptions.CoreTokenizerType - Enum Class in org.tribuo.util.tokens.options
Tokenizer type.
coreTokenizerType - Variable in class org.tribuo.util.tokens.options.CoreTokenizerOptions
Type of tokenizer
CORRELATED - Enum constant in enum class org.tribuo.util.infotheory.example.InformationTheoryDemo.DistributionType
Correlated data.
COSINE - Enum constant in enum class org.tribuo.clustering.hdbscan.HdbscanTrainer.Distance
Cosine similarity as a distance measure.
COSINE - Enum constant in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Distance
Cosine similarity as a distance measure.
COSINE - Enum constant in enum class org.tribuo.common.nearest.KNNTrainer.Distance
Cosine similarity used as a distance measure.
cosineDistance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Calculates the cosine distance of two vectors.
cosineSimilarity(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Calculates the cosine similarity of two vectors.
cost - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
cost - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
Cost penalty for SVM.
count - Variable in class org.tribuo.SkeletalVariableInfo
How often the feature occurs in the dataset.
count - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
The number of samples this distribution has seen.
count - Variable in class org.tribuo.util.infotheory.impl.TripleDistribution
The number of samples in this distribution.
count - Variable in class org.tribuo.util.infotheory.impl.WeightCountTuple
The current count.
count - Variable in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
The sample count.
count - Variable in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The sample count.
countMap - Variable in class org.tribuo.regression.RegressionInfo
 
CREATE_AND_DEPLOY - Enum constant in enum class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions.Mode
Create a Model artifact, upload it to OCI and create a Model Deployment.
createBootstrapView(Dataset<T>, int, long) - Static method in class org.tribuo.dataset.DatasetView
Generates a DatasetView bootstrapped from the supplied Dataset.
createBootstrapView(Dataset<T>, int, long, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Static method in class org.tribuo.dataset.DatasetView
Generates a DatasetView bootstrapped from the supplied Dataset.
createConstantTrainer(double) - Static method in class org.tribuo.regression.baseline.DummyRegressionTrainer
Creates a trainer which create models which return a fixed value.
createConstantTrainer(String) - Static method in class org.tribuo.classification.baseline.DummyClassifierTrainer
Creates a trainer which creates models which return a fixed label.
createContext(Model<Event>, List<Prediction<Event>>) - Method in class org.tribuo.anomaly.evaluation.AnomalyEvaluator
 
createContext(Model<Event>, List<Prediction<Event>>) - Method in class org.tribuo.anomaly.evaluation.AnomalyMetric
 
createContext(Model<Label>, List<Prediction<Label>>) - Method in class org.tribuo.classification.evaluation.LabelEvaluator
 
createContext(Model<Label>, List<Prediction<Label>>) - Method in class org.tribuo.classification.evaluation.LabelMetric
 
createContext(Model<ClusterID>, List<Prediction<ClusterID>>) - Method in class org.tribuo.clustering.evaluation.ClusteringEvaluator
 
createContext(Model<ClusterID>, List<Prediction<ClusterID>>) - Method in class org.tribuo.clustering.evaluation.ClusteringMetric
 
createContext(Model<MultiLabel>, List<Prediction<MultiLabel>>) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluator
 
createContext(Model<MultiLabel>, List<Prediction<MultiLabel>>) - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
 
createContext(Model<Regressor>, List<Prediction<Regressor>>) - Method in class org.tribuo.regression.evaluation.RegressionEvaluator
 
createContext(Model<Regressor>, List<Prediction<Regressor>>) - Method in class org.tribuo.regression.evaluation.RegressionMetric
 
createContext(Model<T>, List<Prediction<T>>) - Method in class org.tribuo.evaluation.AbstractEvaluator
Create the context needed for evaluation.
createContext(Model<T>, List<Prediction<T>>) - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
Creates the context this metric uses to compute it's value.
createContext(Model<T>, Dataset<T>) - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
Creates the metric context used to compute this metric's value, generating Predictions for each Example in the supplied dataset.
createContext(SequenceModel<Label>, List<List<Prediction<Label>>>) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluator
 
createContext(SequenceModel<T>, List<List<Prediction<T>>>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Create the context needed for evaluation.
createDeepCopy(Dataset<T>) - Static method in class org.tribuo.MutableDataset
Creates a deep copy of the supplied Dataset which is mutable.
createDenseMatrix(double[][]) - Static method in class org.tribuo.math.la.DenseMatrix
Defensively copies the values before construction.
createDenseVector(double[]) - Static method in class org.tribuo.math.la.DenseVector
Defensively copies the values before construction.
createDenseVector(Example<T>, ImmutableFeatureMap, boolean) - Static method in class org.tribuo.math.la.DenseVector
Builds a DenseVector from an Example.
createEnsembleFromExistingModels(String, List<Model<T>>, EnsembleCombiner<T>) - Static method in class org.tribuo.ensemble.WeightedEnsembleModel
Creates an ensemble from existing models.
createEnsembleFromExistingModels(String, List<Model<T>>, EnsembleCombiner<T>, float[]) - Static method in class org.tribuo.ensemble.WeightedEnsembleModel
Creates an ensemble from existing models.
createEvaluation(C, Map<MetricID<T>, Double>, EvaluationProvenance) - Method in class org.tribuo.evaluation.AbstractEvaluator
Create an evaluation for the given results
createEvaluation(C, Map<MetricID<T>, Double>, EvaluationProvenance) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Create an evaluation for the given results
createEvaluation(AnomalyMetric.Context, Map<MetricID<Event>, Double>, EvaluationProvenance) - Method in class org.tribuo.anomaly.evaluation.AnomalyEvaluator
 
createEvaluation(LabelMetric.Context, Map<MetricID<Label>, Double>, EvaluationProvenance) - Method in class org.tribuo.classification.evaluation.LabelEvaluator
 
createEvaluation(LabelMetric.Context, Map<MetricID<Label>, Double>, EvaluationProvenance) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluator
 
createEvaluation(ClusteringMetric.Context, Map<MetricID<ClusterID>, Double>, EvaluationProvenance) - Method in class org.tribuo.clustering.evaluation.ClusteringEvaluator
 
createEvaluation(MultiLabelMetric.Context, Map<MetricID<MultiLabel>, Double>, EvaluationProvenance) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluator
 
createEvaluation(RegressionMetric.Context, Map<MetricID<Regressor>, Double>, EvaluationProvenance) - Method in class org.tribuo.regression.evaluation.RegressionEvaluator
 
createFeatureMap(Set<String>) - Static method in class org.tribuo.interop.ExternalModel
Creates an immutable feature map from a set of feature names.
createFeatures(Example<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionModel
Creates the feature vector.
createFeatures(Example<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseModel
Creates the feature vector.
createFeatures(Example<Regressor>) - Method in class org.tribuo.regression.slm.SparseLinearModel
Creates the feature vector.
createFromPairList(List<Pair<String, Boolean>>) - Static method in class org.tribuo.multilabel.MultiLabel
Creates a MultiLabel from a list of dimensions.
createFromPairList(List<Pair<String, Double>>) - Static method in class org.tribuo.regression.Regressor
Creates a Regressor from a list of dimension tuples.
createFromSparseVectors(SparseVector[]) - Static method in class org.tribuo.math.la.DenseSparseMatrix
Defensively copies the values.
createGaussianTrainer(long) - Static method in class org.tribuo.regression.baseline.DummyRegressionTrainer
Creates a trainer which create models which sample the output from a gaussian distribution fit to the training data.
createIDXData(IDXDataSource.IDXType, int[], double[]) - Static method in class org.tribuo.datasource.IDXDataSource.IDXData
Constructs an IDXData, validating the input and defensively copying it.
createLabel(Label) - Method in class org.tribuo.multilabel.MultiLabel
Creates a binary label from this multilabel.
createMeanTrainer() - Static method in class org.tribuo.regression.baseline.DummyRegressionTrainer
Creates a trainer which create models which return the mean of the training data.
createMedianTrainer() - Static method in class org.tribuo.regression.baseline.DummyRegressionTrainer
Creates a trainer which create models which return the median of the training data.
createMetrics(Model<Event>) - Method in class org.tribuo.anomaly.evaluation.AnomalyEvaluator
 
createMetrics(Model<Label>) - Method in class org.tribuo.classification.evaluation.LabelEvaluator
 
createMetrics(Model<ClusterID>) - Method in class org.tribuo.clustering.evaluation.ClusteringEvaluator
 
createMetrics(Model<MultiLabel>) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluator
 
createMetrics(Model<Regressor>) - Method in class org.tribuo.regression.evaluation.RegressionEvaluator
 
createMetrics(Model<T>) - Method in class org.tribuo.evaluation.AbstractEvaluator
Creates the appropriate set of metrics for this model, by querying for it's OutputInfo.
createMetrics(SequenceModel<Label>) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluator
 
createMetrics(SequenceModel<T>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Creates the appropriate set of metrics for this model, by querying for it's OutputInfo.
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>, FMParameters) - Method in class org.tribuo.classification.sgd.fm.FMClassificationTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>, LinearParameters) - Method in class org.tribuo.classification.sgd.linear.LinearSGDTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<MultiLabel>, FMParameters) - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<MultiLabel>, LinearParameters) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>, FMParameters) - Method in class org.tribuo.regression.sgd.fm.FMRegressionTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>, LinearParameters) - Method in class org.tribuo.regression.sgd.linear.LinearSGDTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Booster>, XGBoostOutputConverter<T>) - Method in class org.tribuo.common.xgboost.XGBoostTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, X) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Creates the appropriate model subclass for this subclass of AbstractSGDTrainer.
createModel(Path, ModelProvenance, OCIUtil.OCIModelType, DataScienceClient, ObjectMapper, OCIUtil.OCIModelArtifactConfig) - Static method in class org.tribuo.interop.oci.OCIUtil
Creates an OCI DS model and uploads the model artifact.
createModel(Map<String, T>, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
Constructs the appropriate subclass of SkeletalIndependentRegressionModel for this trainer.
createModel(Map<String, T>, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
Constructs the appropriate subclass of SkeletalIndependentRegressionModel for this trainer.
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Event>, List<Model>) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
 
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Event>, List<svm_model>) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
 
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>, List<Model>) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
 
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>, List<svm_model>) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
 
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>, List<Model>) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionTrainer
 
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>, List<svm_model>) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
 
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Model>) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
Construct the appropriate subtype of LibLinearModel for the prediction task.
createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<svm_model>) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
Construct the appropriate subtype of LibSVMModel for the prediction task.
createModel(U, DataScienceClient, ObjectMapper, OCIUtil.OCIModelArtifactConfig) - Static method in class org.tribuo.interop.oci.OCIUtil
Creates an OCI DS model and uploads the model artifact.
createModelArtifact(Path, OCIUtil.OCIModelArtifactConfig) - Static method in class org.tribuo.interop.oci.OCIUtil
Creates the OCI DS model artifact zip file.
createMostFrequentTrainer() - Static method in class org.tribuo.classification.baseline.DummyClassifierTrainer
Creates a trainer which creates models which return a fixed label, the one which was most frequent in the training data.
createObjectMapper() - Static method in class org.tribuo.interop.oci.OCIUtil
Creates an ObjectMapper capable of parsing the OCI DS json.
createOCIModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, Path, String, String, OCIOutputConverter<T>) - Static method in class org.tribuo.interop.oci.OCIModel
Creates an OCIModel by wrapping an OCI DS Model Deployment endpoint.
createOCIModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, Path, String, OCIOutputConverter<T>) - Static method in class org.tribuo.interop.oci.OCIModel
Creates an OCIModel by wrapping an OCI DS Model Deployment endpoint.
createOnlineEvaluator(Model<T>, DataProvenance) - Method in interface org.tribuo.evaluation.Evaluator
Creates an online evaluator that maintains a list of all the predictions it has seen and can evaluate them upon request.
createOnnxModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, ExampleTransformer, OutputTransformer<T>, OrtSession.SessionOptions, String, String) - Static method in class org.tribuo.interop.onnx.ONNXExternalModel
Creates an ONNXExternalModel by loading the model from disk.
createOnnxModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, ExampleTransformer, OutputTransformer<T>, OrtSession.SessionOptions, Path, String) - Static method in class org.tribuo.interop.onnx.ONNXExternalModel
Creates an ONNXExternalModel by loading the model from disk.
createOutputInfo(OutputFactory<T>, Map<T, Integer>) - Static method in class org.tribuo.interop.ExternalModel
Creates an output info from a set of outputs.
createParameters(int, int, SplittableRandom) - Method in class org.tribuo.common.sgd.AbstractFMTrainer
Constructs the trainable parameters object, in this case a FMParameters containing a weight matrix for the feature weights and a series of weight matrices for the factorized feature representation.
createParameters(int, int, SplittableRandom) - Method in class org.tribuo.common.sgd.AbstractLinearSGDTrainer
Constructs the trainable parameters object, in this case a LinearParameters containing a single weight matrix.
createParameters(int, int, SplittableRandom) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Constructs the trainable parameters object.
createQuartileTrainer(double) - Static method in class org.tribuo.regression.baseline.DummyRegressionTrainer
Creates a trainer which create models which return the value at the specified fraction of the sorted training data.
createSparseVector(int, int[], double[]) - Static method in class org.tribuo.math.la.SparseVector
Defensively copies the input, and checks that the indices are sorted.
createSparseVector(int, Map<Integer, Double>) - Static method in class org.tribuo.math.la.SparseVector
Builds a SparseVector from a map.
createSparseVector(Example<T>, ImmutableFeatureMap, boolean) - Static method in class org.tribuo.math.la.SparseVector
Builds a SparseVector from an Example.
createSplitFunction(boolean) - Static method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Creates a SplitFunctionTokenizer.SplitFunction that is used by the super class SplitFunctionTokenizer to determine how and where the tokenizer splits the input.
createSplitNode() - Method in class org.tribuo.common.tree.AbstractTrainingNode
Transforms an AbstractTrainingNode into a SplitNode
createStats() - Method in interface org.tribuo.transform.Transformation
Creates the statistics object for this Transformation.
createStats() - Method in class org.tribuo.transform.transformations.BinningTransformation
 
createStats() - Method in class org.tribuo.transform.transformations.IDFTransformation
 
createStats() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation
 
createStats() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation
 
createStats() - Method in class org.tribuo.transform.transformations.SimpleTransform
Returns itself.
createStratifiedTrainer(long) - Static method in class org.tribuo.classification.baseline.DummyClassifierTrainer
Creates a trainer which creates models which return random labels sampled from the training label distribution.
createSupplier(Tokenizer) - Static method in interface org.tribuo.util.tokens.Tokenizer
Creates a supplier from the specified tokenizer by cloning it.
createTensorflowModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, String, String, FeatureConverter, OutputConverter<T>, String) - Static method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
Creates a TensorflowFrozenExternalModel by loading in a frozen graph.
createTensorflowModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, String, FeatureConverter, OutputConverter<T>, String) - Static method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
Creates a TensorflowSavedModelExternalModel by loading in a SavedModelBundle.
createThreadLocal(Tokenizer) - Static method in interface org.tribuo.util.tokens.Tokenizer
Creates a thread local source of tokenizers by making a Tokenizer supplier using Tokenizer.createSupplier(Tokenizer).
createTransformers(TransformationMap) - Method in class org.tribuo.Dataset
Takes a TransformationMap and converts it into a TransformerMap by observing all the values in this dataset.
createTransformers(TransformationMap, boolean) - Method in class org.tribuo.Dataset
Takes a TransformationMap and converts it into a TransformerMap by observing all the values in this dataset.
createUniformTrainer(long) - Static method in class org.tribuo.classification.baseline.DummyClassifierTrainer
Creates a trainer which creates models which return random labels sampled uniformly from the labels seen at training time.
createView(Dataset<T>, Predicate<Example<T>>, String) - Static method in class org.tribuo.dataset.DatasetView
Creates a view from the supplied dataset, using the specified predicate to test if each example should be in this view.
createWeightedBootstrapView(Dataset<T>, int, long, float[]) - Static method in class org.tribuo.dataset.DatasetView
Generates a DatasetView bootstrapped from the supplied Dataset using the supplied example weights.
createWeightedBootstrapView(Dataset<T>, int, long, float[], ImmutableFeatureMap, ImmutableOutputInfo<T>) - Static method in class org.tribuo.dataset.DatasetView
Generates a DatasetView bootstrapped from the supplied Dataset using the supplied example weights.
createWhitespaceTokenizer() - Static method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
Creates a tokenizer that splits on whitespace.
createWithEmptyOutputs(List<? extends List<? extends Feature>>, OutputFactory<T>) - Static method in class org.tribuo.sequence.SequenceExample
Creates a SequenceExample using OutputFactory.getUnknownOutput() as the output for each sequence element.
createXGBoostModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, XGBoostOutputConverter<T>, String) - Static method in class org.tribuo.common.xgboost.XGBoostExternalModel
Creates an XGBoostExternalModel from the supplied model on disk.
createXGBoostModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, XGBoostOutputConverter<T>, Path) - Static method in class org.tribuo.common.xgboost.XGBoostExternalModel
Creates an XGBoostExternalModel from the supplied model on disk.
createXGBoostModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, XGBoostOutputConverter<T>, Booster, URL) - Static method in class org.tribuo.common.xgboost.XGBoostExternalModel
Deprecated.
As the URL argument must always be valid. To wrap an in-memory booster use XGBoostExternalModel.createXGBoostModel(OutputFactory, Map, Map, XGBoostOutputConverter, Booster, Map).
createXGBoostModel(OutputFactory<T>, Map<String, Integer>, Map<T, Integer>, XGBoostOutputConverter<T>, Booster, Map<String, Provenance>) - Static method in class org.tribuo.common.xgboost.XGBoostExternalModel
Creates an XGBoostExternalModel from the supplied in-memory XGBoost Booster.
CREATION_TIME - Static variable in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
The name of the provenance field storing the model creation time.
CRFModel - Class in org.tribuo.classification.sgd.crf
An inference time model for a linear chain CRF trained using SGD.
CRFModel.ConfidenceType - Enum Class in org.tribuo.classification.sgd.crf
The type of subsequence level confidence to predict.
CRFOptions - Class in org.tribuo.classification.sgd.crf
CLI options for training a linear chain CRF model.
CRFOptions() - Constructor for class org.tribuo.classification.sgd.crf.CRFOptions
 
CRFOptions() - Constructor for class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
CRFParameters - Class in org.tribuo.classification.sgd.crf
A Parameters for training a CRF using SGD.
CRFTrainer - Class in org.tribuo.classification.sgd.crf
A trainer for CRFs using SGD.
CRFTrainer(StochasticGradientOptimiser, int, int, int, long) - Constructor for class org.tribuo.classification.sgd.crf.CRFTrainer
Creates a CRFTrainer which uses SGD to learn the parameters.
CRFTrainer(StochasticGradientOptimiser, int, int, long) - Constructor for class org.tribuo.classification.sgd.crf.CRFTrainer
Sets the minibatch size to 1.
CRFTrainer(StochasticGradientOptimiser, int, long) - Constructor for class org.tribuo.classification.sgd.crf.CRFTrainer
Sets the minibatch size to 1 and the logging interval to 100.
crossValidation - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
Cross-validate the output metrics.
CrossValidation<T extends Output<T>,E extends Evaluation<T>> - Class in org.tribuo.evaluation
A class that does k-fold cross-validation.
CrossValidation(Trainer<T>, Dataset<T>, Evaluator<T, E>, int) - Constructor for class org.tribuo.evaluation.CrossValidation
Builds a k-fold cross-validation loop.
CrossValidation(Trainer<T>, Dataset<T>, Evaluator<T, E>, int, long) - Constructor for class org.tribuo.evaluation.CrossValidation
Builds a k-fold cross-validation loop.
CSV - Enum constant in enum class org.tribuo.data.DataOptions.InputFormat
Simple numeric CSV file.
CSVDataSource<T extends Output<T>> - Class in org.tribuo.data.csv
A DataSource for loading separable data from a text file (e.g., CSV, TSV) and applying FieldProcessors to it.
CSVDataSource(URI, RowProcessor<T>, boolean) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data.
CSVDataSource(URI, RowProcessor<T>, boolean, char) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data.
CSVDataSource(URI, RowProcessor<T>, boolean, char, char) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data, and the supplied separator and quote characters to read the input data file.
CSVDataSource(URI, RowProcessor<T>, boolean, char, char, List<String>) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data, and the supplied separator and quote characters to read the input data file.
CSVDataSource(Path, RowProcessor<T>, boolean) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data.
CSVDataSource(Path, RowProcessor<T>, boolean, char) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data.
CSVDataSource(Path, RowProcessor<T>, boolean, char, char) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data, and the supplied separator and quote characters to read the input data file.
CSVDataSource(Path, RowProcessor<T>, boolean, char, char, List<String>) - Constructor for class org.tribuo.data.csv.CSVDataSource
Creates a CSVDataSource using the specified RowProcessor to process the data, and the supplied separator and quote characters to read the input data file.
CSVDataSource.CSVDataSourceProvenance - Class in org.tribuo.data.csv
Provenance for CSVDataSource.
CSVDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.csv.CSVDataSource.CSVDataSourceProvenance
Deserialization constructor.
CSVIterator - Class in org.tribuo.data.csv
An iterator over a CSV file.
CSVIterator(Reader) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied Reader.
CSVIterator(Reader, char, char) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied Reader.
CSVIterator(Reader, char, char, String[]) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied Reader.
CSVIterator(Reader, char, char, List<String>) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied Reader.
CSVIterator(URI) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied URI.
CSVIterator(URI, char, char) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied URI.
CSVIterator(URI, char, char, String[]) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied URI.
CSVIterator(URI, char, char, List<String>) - Constructor for class org.tribuo.data.csv.CSVIterator
Builds a CSVIterator for the supplied URI.
CSVLoader<T extends Output<T>> - Class in org.tribuo.data.csv
Load a DataSource/Dataset from a CSV file.
CSVLoader(char, char, OutputFactory<T>) - Constructor for class org.tribuo.data.csv.CSVLoader
Creates a CSVLoader using the supplied separator, quote and output factory.
CSVLoader(char, OutputFactory<T>) - Constructor for class org.tribuo.data.csv.CSVLoader
Creates a CSVLoader using the supplied separator and output factory.
CSVLoader(OutputFactory<T>) - Constructor for class org.tribuo.data.csv.CSVLoader
Creates a CSVLoader using the supplied output factory.
CSVLoader.CSVLoaderProvenance - Class in org.tribuo.data.csv
Deprecated.
Deprecated in 4.2 as CSVLoader now returns a CSVDataSource. This provenance is kept so older models can still load correctly.
CSVLoaderProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
Deprecated.
Deserialization constructor.
csvQuoteChar - Variable in class org.tribuo.data.DataOptions
Quote character in the CSV file.
csvResponseName - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Response name in the csv file.
csvResponseName - Variable in class org.tribuo.data.DataOptions
Response name in the csv file.
CSVSaver - Class in org.tribuo.data.csv
Saves a Dataset in CSV format suitable for loading by CSVLoader.
CSVSaver() - Constructor for class org.tribuo.data.csv.CSVSaver
Builds a CSV saver using the default separator and quote from CSVIterator.
CSVSaver(char, char) - Constructor for class org.tribuo.data.csv.CSVSaver
Builds a CSV saver using the supplied separator and quote.
cumulativeSum(boolean[]) - Static method in class org.tribuo.util.Util
Produces a cumulative sum array.
cumulativeSum(double[]) - Static method in class org.tribuo.util.Util
Produces a cumulative sum array.
currentRow - Variable in class org.tribuo.data.columnar.ColumnarIterator
The current row.

D

DART - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
A gradient boosted decision tree using dropout.
data - Variable in class org.tribuo.common.xgboost.XGBoostTrainer.DMatrixTuple
 
data - Variable in class org.tribuo.data.text.TextDataSource
The actual data read out of the text file.
data - Variable in class org.tribuo.Dataset
The data in this data set.
data - Variable in class org.tribuo.interop.tensorflow.TensorFlowUtil.TensorTuple
The tensor data.
data - Variable in class org.tribuo.sequence.SequenceDataset
The data in this data set.
DATA_LOCATION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
DATA_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
DataOptions - Class in org.tribuo.data
Options for working with training and test data in a CLI.
DataOptions() - Constructor for class org.tribuo.data.DataOptions
 
DataOptions.Delimiter - Enum Class in org.tribuo.data
The delimiters supported by CSV files in this options object.
DataOptions.InputFormat - Enum Class in org.tribuo.data
The input formats supported by this options object.
DataProvenance - Interface in org.tribuo.provenance
Tag interface for data sources provenances.
Dataset<T extends Output<T>> - Class in org.tribuo
A class for sets of data, which are used to train and evaluate classifiers.
Dataset(DataSource<T>) - Constructor for class org.tribuo.Dataset
Creates a dataset.
Dataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.Dataset
Creates a dataset.
DATASET - Enum constant in enum class org.tribuo.json.StripProvenance.ProvenanceTypes
Select the dataset provenance.
DATASET - Static variable in class org.tribuo.provenance.ModelProvenance
 
DatasetExplorer - Class in org.tribuo.data
A CLI for exploring a serialised Dataset.
DatasetExplorer() - Constructor for class org.tribuo.data.DatasetExplorer
Constructs a dataset explorer.
DatasetExplorer.DatasetExplorerOptions - Class in org.tribuo.data
Command line options.
DatasetExplorerOptions() - Constructor for class org.tribuo.data.DatasetExplorer.DatasetExplorerOptions
 
datasetName - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
Name of the example dataset, options are {gorilla}.
datasetName - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Name of the example dataset, options are {gorilla}.
datasetPath - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Path to the serialized dataset to score.
datasetProvenance - Variable in class org.tribuo.provenance.ModelProvenance
 
DatasetProvenance - Class in org.tribuo.provenance
Base class for dataset provenance.
DatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.DatasetProvenance
Deserialization constructor.
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, String, boolean, boolean, int, int, int) - Constructor for class org.tribuo.provenance.DatasetProvenance
Constructs a dataset provenance using the supplied information.
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, Dataset<T>) - Constructor for class org.tribuo.provenance.DatasetProvenance
Creates a dataset provenance from the supplied dataset.
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, SequenceDataset<T>) - Constructor for class org.tribuo.provenance.DatasetProvenance
Creates a dataset provenance from the supplied sequence dataset.
DatasetView<T extends Output<T>> - Class in org.tribuo.dataset
DatasetView provides an immutable view on another Dataset that only exposes selected examples.
DatasetView(Dataset<T>, int[], String) - Constructor for class org.tribuo.dataset.DatasetView
Creates a DatasetView which includes the supplied indices from the dataset.
DatasetView(Dataset<T>, int[], ImmutableFeatureMap, ImmutableOutputInfo<T>, String) - Constructor for class org.tribuo.dataset.DatasetView
Creates a DatasetView which includes the supplied indices from the dataset.
DatasetView.DatasetViewProvenance - Class in org.tribuo.dataset
Provenance for the DatasetView.
DatasetViewProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.dataset.DatasetView.DatasetViewProvenance
Deserialization constructor.
dataSource - Variable in class org.tribuo.data.PreprocessAndSerialize.PreprocessAndSerializeOptions
Datasource to load from a config file
DataSource<T extends Output<T>> - Interface in org.tribuo
A interface for things that can be given to a Dataset's constructor.
DATASOURCE_CREATION_TIME - Static variable in interface org.tribuo.provenance.DataSourceProvenance
The name of the provenance field for the datasource timestamp.
DataSourceProvenance - Interface in org.tribuo.provenance
Data source provenance.
DateExtractor - Class in org.tribuo.data.columnar.extractors
Extracts the field value and translates it to a LocalDate based on the specified DateTimeFormatter.
DateExtractor(String, String, String) - Constructor for class org.tribuo.data.columnar.extractors.DateExtractor
Constructs a date extractor that emits a LocalDate by applying the supplied format to the specified field.
DateExtractor(String, String, String, String, String) - Constructor for class org.tribuo.data.columnar.extractors.DateExtractor
Constructs a date extractor that emits a LocalDate by applying the supplied format to the specified field.
DateExtractor(String, String, DateTimeFormatter) - Constructor for class org.tribuo.data.columnar.extractors.DateExtractor
Deprecated.
DateFieldProcessor - Class in org.tribuo.data.columnar.processors.field
Processes a column that contains a date value.
DateFieldProcessor(String, EnumSet<DateFieldProcessor.DateFeatureType>, String) - Constructor for class org.tribuo.data.columnar.processors.field.DateFieldProcessor
Constructs a field processor which parses a date from the specified field name using the supplied format string then extracts date features according to the supplied EnumSet.
DateFieldProcessor(String, EnumSet<DateFieldProcessor.DateFeatureType>, String, String, String) - Constructor for class org.tribuo.data.columnar.processors.field.DateFieldProcessor
Constructs a field processor which parses a date from the specified field name using the supplied format string then extracts date features according to the supplied EnumSet.
DateFieldProcessor.DateFeatureType - Enum Class in org.tribuo.data.columnar.processors.field
The types of date features which can be extracted.
DAY - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The day.
DAY_OF_QUARTER - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The day of the quarter.
DAY_OF_WEEK - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The day of the week in ISO 8601.
DAY_OF_YEAR - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The day of the year.
dbConfig - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
Name of the DBConfig to use
DEBUG - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
All the logging.
DecisionTreeTrainer<T extends Output<T>> - Interface in org.tribuo.common.tree
A tag interface for a Trainer so the random forests trainer can check if it's actually a tree.
decode(Tensor, List<SequenceExample<T>>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceOutputConverter
Decode graph output tensors corresponding to a batch of input sequences.
decode(Tensor, SequenceExample<T>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceOutputConverter
Decode a tensor of graph output into a list of predictions for the input sequence.
deepCopy() - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
Copies this inverted feature.
deepCopy() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Returns a deep copy of this tree feature.
DEFAULT - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
DEFAULT = 0;
DEFAULT - Enum constant in enum class org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions.ViterbiLabelFeatures
The default label features.
DEFAULT_BATCH_SIZE - Static variable in class org.tribuo.interop.ExternalModel
Default batch size for external model batch predictions.
DEFAULT_COST - Static variable in class org.tribuo.regression.sgd.objectives.Huber
The default cost beyond which the function is linear.
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.impl.TripleDistribution
The default map size to initialise the marginalised count maps with.
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The default map size.
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.InformationTheory
The initial size of the various maps.
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
The initial size of the various maps.
DEFAULT_METADATA_SIZE - Static variable in class org.tribuo.Example
The default initial size of the metadata map.
DEFAULT_NAME - Static variable in class org.tribuo.regression.Regressor
Default name used for dimensions which are unnamed when parsed from Strings.
DEFAULT_RESPONSE - Static variable in class org.tribuo.data.csv.CSVSaver
The default response column name.
DEFAULT_SCORE - Static variable in class org.tribuo.anomaly.Event
The default score of events.
DEFAULT_SEED - Static variable in interface org.tribuo.Trainer
Default seed used to initialise RNGs.
DEFAULT_SIZE - Static variable in class org.tribuo.common.tree.AbstractTrainingNode
Default buffer size used in the split operation.
DEFAULT_SIZE - Static variable in class org.tribuo.impl.ArrayExample
Default initial size of the backing arrays.
DEFAULT_SIZE - Static variable in class org.tribuo.impl.BinaryFeaturesExample
Default initial size of the backing arrays.
DEFAULT_SPLIT_CHAR - Static variable in class org.tribuo.regression.RegressionFactory
The default character to split the string form of a multidimensional regressor.
DEFAULT_SPLIT_CHARACTERS - Static variable in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
The default split characters.
DEFAULT_SPLIT_EXCEPTING_IN_DIGITS_CHARACTERS - Static variable in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
The default characters which don't cause splits inside digits.
DEFAULT_THRESHOLD - Static variable in class org.tribuo.interop.oci.OCIMultiLabelConverter
The default threshold for conversion into a label.
DEFAULT_THRESHOLD - Static variable in class org.tribuo.interop.onnx.MultiLabelTransformer
The default threshold for conversion into a label.
DEFAULT_UNKNOWN_TOKEN - Static variable in class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
The default unknown token string.
DEFAULT_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
DEFAULT = 0;
DEFAULT_WEIGHT - Static variable in class org.tribuo.Example
The default weight.
DEFAULT_WEIGHT - Static variable in class org.tribuo.sequence.SequenceExample
The default sequence example weight.
DefaultFeatureExtractor - Class in org.tribuo.classification.sequence.viterbi
A label feature extractor that produces several kinds of label-based features.
DefaultFeatureExtractor() - Constructor for class org.tribuo.classification.sequence.viterbi.DefaultFeatureExtractor
Constructs a default feature extractor for bigrams and trigrams using the past 3 outcomes.
DefaultFeatureExtractor(int, int, boolean, boolean, boolean) - Constructor for class org.tribuo.classification.sequence.viterbi.DefaultFeatureExtractor
Constructs a default feature extractor using the supplied parameters.
degree - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
Degree in polynomial kernel.
delimiter - Variable in class org.tribuo.data.DataOptions
Delimiter
DELTA - Static variable in class org.tribuo.math.la.VectorTuple
The tolerance for equality in value comparisons.
DemoLabelDataSource - Class in org.tribuo.classification.example
The base class for the 2d binary classification data sources in org.tribuo.classification.example.
DemoLabelDataSource.DemoLabelDataSourceProvenance - Class in org.tribuo.classification.example
Provenance for DemoLabelDataSource.
DemoLabelDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.classification.example.DemoLabelDataSource.DemoLabelDataSourceProvenance
Constructs a provenance from the marshalled form.
DemoOptions() - Constructor for class org.tribuo.util.infotheory.example.InformationTheoryDemo.DemoOptions
 
DENOTATION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
DENOTATION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto
 
dense - Variable in class org.tribuo.MutableDataset
Denotes if this dataset contains implicit zeros or not.
dense - Variable in class org.tribuo.sequence.MutableSequenceDataset
Does this dataset have a dense feature space.
DENSE - Enum constant in enum class org.tribuo.interop.tensorflow.TrainTest.InputType
Dense feature extractor.
DenseFeatureConverter - Class in org.tribuo.interop.tensorflow
Converts a sparse example into a dense float vector, then wraps it in a TFloat32.
DenseFeatureConverter(String) - Constructor for class org.tribuo.interop.tensorflow.DenseFeatureConverter
Builds a DenseFeatureConverter, setting the input name.
DenseMatrix - Class in org.tribuo.math.la
A dense matrix, backed by a primitive array.
DenseMatrix(int, int) - Constructor for class org.tribuo.math.la.DenseMatrix
Creates a dense matrix full of zeros.
DenseMatrix(DenseMatrix) - Constructor for class org.tribuo.math.la.DenseMatrix
Copies the supplied matrix.
DenseMatrix(Matrix) - Constructor for class org.tribuo.math.la.DenseMatrix
Copies the supplied matrix, densifying it if it's sparse.
DenseSparseMatrix - Class in org.tribuo.math.la
A matrix which is dense in the first dimension and sparse in the second.
DenseSparseMatrix(int, int) - Constructor for class org.tribuo.math.la.DenseSparseMatrix
Creates a DenseSparseMatrix with no values or indices.
DenseSparseMatrix(List<SparseVector>) - Constructor for class org.tribuo.math.la.DenseSparseMatrix
Constructs a DenseSparseMatrix out of the supplied sparse vector list.
DenseSparseMatrix(DenseSparseMatrix) - Constructor for class org.tribuo.math.la.DenseSparseMatrix
Creates a new DenseSparseMatrix by deep copying the supplied DenseSparseMatrix.
denseTrainTest() - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Makes a simple dataset for training and testing.
denseTrainTest() - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}, and there are 4 classes, {Foo,Bar,Baz,Quux}.
denseTrainTest() - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}, and there are 4 clusters, {0,1,2,3}.
denseTrainTest() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}.
denseTrainTest(double) - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}, and there are 4 clusters, {0,1,2,3}.
denseTrainTest(double) - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}, and there are 4 classes, {Foo,Bar,Baz,Quux}.
denseTrainTest(double) - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}, and there are 4 clusters, {0,1,2,3}.
denseTrainTest(double) - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}.
DenseTransformer - Class in org.tribuo.interop.onnx
Converts a sparse Tribuo example into a dense float vector, then wraps it in an OnnxTensor.
DenseTransformer() - Constructor for class org.tribuo.interop.onnx.DenseTransformer
 
DenseVector - Class in org.tribuo.math.la
A dense vector, backed by a double array.
DenseVector(double[]) - Constructor for class org.tribuo.math.la.DenseVector
Does not defensively copy the input, used internally.
DenseVector(int) - Constructor for class org.tribuo.math.la.DenseVector
Creates an empty dense vector of the specified size.
DenseVector(int, double) - Constructor for class org.tribuo.math.la.DenseVector
Creates a dense vector of the specified size where each element is initialised to the specified value.
DenseVector(DenseVector) - Constructor for class org.tribuo.math.la.DenseVector
Copy constructor.
densify() - Method in class org.tribuo.math.la.SparseVector
Returns a dense vector copying this sparse vector.
densify() - Method in class org.tribuo.MutableDataset
Iterates through the examples, converting implicit zeros into explicit zeros.
densify() - Method in class org.tribuo.sequence.MutableSequenceDataset
Iterates through the examples, converting implicit zeros into explicit zeros.
densify(List<String>) - Method in class org.tribuo.Example
Converts all implicit zeros into explicit zeros based on the supplied feature names.
densify(List<String>) - Method in class org.tribuo.impl.ArrayExample
 
densify(List<String>) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
densify(List<String>) - Method in class org.tribuo.impl.IndexedArrayExample
 
densify(List<String>) - Method in class org.tribuo.impl.ListExample
 
densify(FeatureMap) - Method in class org.tribuo.Example
Converts all implicit zeros into explicit zeros based on the supplied feature map.
densify(FeatureMap) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
densify(FeatureMap) - Method in class org.tribuo.sequence.SequenceExample
Converts all implicit zeros into explicit zeros based on the supplied feature map.
deploy(OCIUtil.OCIModelDeploymentConfig, DataScienceClient, ObjectMapper) - Static method in class org.tribuo.interop.oci.OCIUtil
Creates a Model deployment from an uploaded model.
DEPLOY - Enum constant in enum class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions.Mode
Create a Model deployment.
deploymentName - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelDeploymentConfig
The deployment name.
depth - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
depth - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Maximum depth in the decision tree.
depth - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Max tree depth (default 6, range (0,inf]).
depth - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Max tree depth (default 6, range (0,inf]).
DESCRIPTION - Static variable in class org.tribuo.provenance.SimpleDataSourceProvenance
The description field in the provenance.
DescriptiveStats - Class in org.tribuo.evaluation
Descriptive statistics calculated across a list of doubles.
DescriptiveStats() - Constructor for class org.tribuo.evaluation.DescriptiveStats
Create an empty DescriptiveStats.
DescriptiveStats(List<Double>) - Constructor for class org.tribuo.evaluation.DescriptiveStats
Create a DescriptiveStats initialized with the supplied values.
difference(SparseVector) - Method in class org.tribuo.math.la.SparseVector
Generates an array of the indices that are active in this vector but are not present in other.
differencesIndices(double[]) - Static method in class org.tribuo.util.Util
Returns an array containing the indices where values are different.
differencesIndices(double[], double) - Static method in class org.tribuo.util.Util
Returns an array containing the indices where values are different.
diffProvenance(ModelProvenance, ModelProvenance) - Static method in class org.tribuo.reproducibility.ReproUtil
Creates a JSON String diff of two ModelProvenance objects.
DIM_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
DIM_PARAM - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
 
DIM_PARAM_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
DIM_VALUE - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
 
DIM_VALUE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
dim1 - Variable in class org.tribuo.math.la.DenseMatrix
 
dim2 - Variable in class org.tribuo.math.la.DenseMatrix
 
DIMENSIONALITY_REDUCTION - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Dimensionality reduction, no Tribuo mapping.
dimensions - Variable in class org.tribuo.regression.impl.SkeletalIndependentRegressionModel
 
dimensions - Variable in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseModel
 
DimensionTuple(String, double) - Constructor for class org.tribuo.regression.Regressor.DimensionTuple
Creates a dimension tuple from the supplied name and value.
DimensionTuple(String, double, double) - Constructor for class org.tribuo.regression.Regressor.DimensionTuple
Creates a dimension tuple from the supplied name, value and variance.
DIMS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
DIMS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
directory - Variable in class org.tribuo.classification.experiments.RunAll.RunAllOptions
Directory to write out the models and test reports.
DirectoryFileSource<T extends Output<T>> - Class in org.tribuo.data.text
A data source for a somewhat-common format for text classification datasets: a top level directory that contains a number of subdirectories.
DirectoryFileSource() - Constructor for class org.tribuo.data.text.DirectoryFileSource
for olcut
DirectoryFileSource(Path, OutputFactory<T>, TextFeatureExtractor<T>, DocumentPreprocessor...) - Constructor for class org.tribuo.data.text.DirectoryFileSource
Creates a data source that will use the given feature extractor and document preprocessors on the data read from the files in the directories representing classes.
DirectoryFileSource.DirectoryFileSourceProvenance - Class in org.tribuo.data.text
Provenance for DirectoryFileSource.
DirectoryFileSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.text.DirectoryFileSource.DirectoryFileSourceProvenance
Deserialization constructor.
distance - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
Distance function in K-Means.
distance - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
Distance function to use in the e step.
distance(SGDVector, DoubleUnaryOperator, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
Computes the distance between this vector and the other vector.
DISTANCE_DELTA - Static variable in class org.tribuo.classification.explanations.lime.LIMEBase
Delta to consider two distances equal.
distanceType - Variable in class org.tribuo.clustering.hdbscan.HdbscanOptions
Distance function in HDBSCAN*.
distributionEquals(Prediction<T>) - Method in class org.tribuo.Prediction
Checks that the other prediction has the same distribution as this prediction, using the Output.fullEquals(T) method.
div - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Divides by the specified constant.
div(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that divides each value by the operand.
DIV - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Element-wise division with broadcasting.
DMatrixTuple(DMatrix, int[], Example<T>[]) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer.DMatrixTuple
 
DOC_STRING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
DOC_STRING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
DOC_STRING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
DOC_STRING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
 
DOC_STRING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
DOC_STRING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
DocumentPreprocessor - Interface in org.tribuo.data.text
An interface for things that can pre-process documents before they are broken into features.
domain - Variable in enum class org.tribuo.util.onnx.ONNXOperators
The operator domain (used for the ML operators).
DOMAIN_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
DOMAIN_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
 
DOMAIN_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
DOMAIN_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
domainAndIDEquals(ImmutableOutputInfo<Event>) - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
domainAndIDEquals(ImmutableOutputInfo<Label>) - Method in class org.tribuo.classification.ImmutableLabelInfo
 
domainAndIDEquals(ImmutableOutputInfo<ClusterID>) - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
domainAndIDEquals(ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
domainAndIDEquals(ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
domainAndIDEquals(ImmutableOutputInfo<T>) - Method in interface org.tribuo.ImmutableOutputInfo
Checks if the domain is the same as the other output info's domain, and that each element is mapped to the same id number.
domainEquals(FeatureMap) - Method in class org.tribuo.FeatureMap
Check if this feature map contains the same features as the supplied one.
dot(SGDVector) - Method in class org.tribuo.math.la.DenseVector
 
dot(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Calculates the dot product between this vector and other.
dot(SGDVector) - Method in class org.tribuo.math.la.SparseVector
 
dot(SGDVector) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
DOUBLE - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
DOUBLE = 11;
DOUBLE - Enum constant in enum class org.tribuo.datasource.IDXDataSource.IDXType
A 64-bit float.
DOUBLE_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
DOUBLE_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
DOUBLE = 11;
DoubleExtractor - Class in org.tribuo.data.columnar.extractors
Extracts the field value and converts it to a double.
DoubleExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.DoubleExtractor
Extracts a double value from the supplied field name.
DoubleExtractor(String, String) - Constructor for class org.tribuo.data.columnar.extractors.DoubleExtractor
Extracts a double value from the supplied field name.
DoubleFieldProcessor - Class in org.tribuo.data.columnar.processors.field
Processes a column that contains a real value.
DoubleFieldProcessor(String) - Constructor for class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
Constructs a field processor which extracts a single double valued feature from the specified field name.
DoubleFieldProcessor(String, boolean) - Constructor for class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
Constructs a field processor which extracts a single double valued feature from the specified field name.
DoubleFieldProcessor(String, boolean, boolean) - Constructor for class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
Constructs a field processor which extracts a single double valued feature from the specified field name.
doubleTensorBuilder(ONNXContext, String, List<Integer>, Consumer<DoubleBuffer>) - Static method in class org.tribuo.util.onnx.ONNXUtils
Generic method to create double OnnxMl.TensorProto instances.
dropInvalidExamples - Variable in class org.tribuo.ImmutableDataset
If true, instead of throwing an exception when an invalid Example is encountered, this Dataset will log a warning and drop it.
dsConfig - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
The OCI Data Science config.
dsConfig - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelDeploymentConfig
The OCI Data Science config.
DTYPE - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
The name of the data type.
DummyClassifierModel - Class in org.tribuo.classification.baseline
A model which performs dummy classifications (e.g., constant output, uniform sampled labels, stratified sampled labels).
DummyClassifierTrainer - Class in org.tribuo.classification.baseline
A trainer for simple baseline classifiers.
DummyClassifierTrainer.DummyType - Enum Class in org.tribuo.classification.baseline
Types of dummy classifier.
DummyRegressionModel - Class in org.tribuo.regression.baseline
A model which performs dummy regressions (e.g., constant output, gaussian sampled output, mean value, median, quartile).
DummyRegressionTrainer - Class in org.tribuo.regression.baseline
A trainer for simple baseline regressors.
DummyRegressionTrainer.DummyRegressionTrainerProvenance - Class in org.tribuo.regression.baseline
Deprecated.
DummyRegressionTrainer.DummyType - Enum Class in org.tribuo.regression.baseline
Types of dummy regression model.
DummyRegressionTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
Constructs a provenance from the marshalled form.
DummyRegressionTrainerProvenance(DummyRegressionTrainer) - Constructor for class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
Constructs a provenance from the host.

E

ELASTICNET - Enum constant in enum class org.tribuo.regression.slm.TrainTest.SLMType
ElasticNetCDTrainer - Class in org.tribuo.regression.slm
An ElasticNet trainer that uses co-ordinate descent.
ElasticNetCDTrainer(double, double) - Constructor for class org.tribuo.regression.slm.ElasticNetCDTrainer
Constructs an elastic net trainer using the supplied parameters, with a tolerance of 1e-4, max iterations of 500, randomising the feature choice and using Trainer.DEFAULT_SEED as the RNG seed.
ElasticNetCDTrainer(double, double, double, int, boolean, long) - Constructor for class org.tribuo.regression.slm.ElasticNetCDTrainer
Constructs an elastic net trainer using the supplied parameters.
ElasticNetCDTrainer(double, double, long) - Constructor for class org.tribuo.regression.slm.ElasticNetCDTrainer
Constructs an elastic net trainer using the supplied parameters, with a tolerance of 1e-4, max iterations of 500, and randomising the feature choice.
ELEM_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
ELEM_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
ELEM_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
elements - Variable in class org.tribuo.math.la.DenseVector
 
EmptyDatasetProvenance - Class in org.tribuo.provenance.impl
An empty DatasetProvenance, should not be used except by the provenance removal system.
EmptyDatasetProvenance() - Constructor for class org.tribuo.provenance.impl.EmptyDatasetProvenance
An empty dataset provenance.
EmptyDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyDatasetProvenance
Deserialization constructor.
EmptyDataSourceProvenance - Class in org.tribuo.provenance.impl
An empty DataSourceProvenance, should not be used except by the provenance removal system.
EmptyDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyDataSourceProvenance
Deserialization constructor.
emptyExample() - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Generates an example with no features.
emptyExample() - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates an example with no features.
emptyExample() - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
Generates an example with no features.
emptyExample() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator
Generates an example with no features.
emptyExample() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates an example with no features.
emptyMultiDimExample() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates an example with no features.
EmptyResponseProcessor<T extends Output<T>> - Class in org.tribuo.data.columnar.processors.response
A ResponseProcessor that always emits an empty optional.
EmptyResponseProcessor(OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
Constructs a response processor which never emits a response.
EmptyTrainerProvenance - Class in org.tribuo.provenance.impl
An empty TrainerProvenance, should not be used except by the provenance removal system.
EmptyTrainerProvenance() - Constructor for class org.tribuo.provenance.impl.EmptyTrainerProvenance
Constructs an empty trainer provenance.
EmptyTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyTrainerProvenance
Deserialization constructor.
encode(List<? extends SequenceExample<?>>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceFeatureConverter
Encodes a batch of examples as a feed dict.
encode(List<SequenceExample<T>>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceOutputConverter
Encodes a batch of labels as a feed dict.
encode(SequenceExample<?>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceFeatureConverter
Encodes an example as a feed dict.
encode(SequenceExample<T>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceOutputConverter
Encodes an example's label as a feed dict.
end - Variable in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
The subsequence end index.
end - Variable in class org.tribuo.util.tokens.Token
The end index.
end - Variable in class org.tribuo.util.tokens.universal.Range
The end index.
END_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
endpointDomain - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
The OCI endpoint domain.
ensemble - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for classifier ensembles.
EnsembleCombiner<T extends Output<T>> - Interface in org.tribuo.ensemble
An interface for combining predictions.
EnsembleExcuse<T extends Output<T>> - Class in org.tribuo.ensemble
An Excuse which has a List of excuses for each of the ensemble members.
EnsembleExcuse(Example<T>, Prediction<T>, Map<String, List<Pair<String, Double>>>, List<Excuse<T>>) - Constructor for class org.tribuo.ensemble.EnsembleExcuse
Constructs an ensemble excuse, comprising the excuses from each ensemble member, along with the feature weights.
EnsembleModel<T extends Output<T>> - Class in org.tribuo.ensemble
A model which contains a list of other Models.
EnsembleModel(String, EnsembleModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Model<T>>) - Constructor for class org.tribuo.ensemble.EnsembleModel
Builds an EnsembleModel from the supplied model list.
EnsembleModelProvenance - Class in org.tribuo.provenance
Model provenance for ensemble models.
EnsembleModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, ListProvenance<? extends ModelProvenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance
Creates a provenance for an ensemble model tracking the class name, creation time, dataset provenance and trainer provenance along with the individual model provenances for each ensemble member.
EnsembleModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>, boolean, ListProvenance<? extends ModelProvenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance
Creates a provenance for an ensemble model tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance along with the individual model provenances for each ensemble member.
EnsembleModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>, ListProvenance<? extends ModelProvenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance
Creates a provenance for an ensemble model tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance along with the individual model provenances for each ensemble member.
EnsembleModelProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance
Used by the provenance unmarshalling system.
ensembleName() - Method in class org.tribuo.common.tree.ExtraTreesTrainer
 
ensembleName() - Method in class org.tribuo.common.tree.RandomForestTrainer
 
ensembleName() - Method in class org.tribuo.ensemble.BaggingTrainer
Default name of the generated ensemble.
ensembleOptions - Variable in class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
The ensemble options.
ensembleOptions - Variable in class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
The ensemble options.
ensembleOptions - Variable in class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
The ensemble options.
ensembleOptions - Variable in class org.tribuo.classification.sgd.fm.TrainTest.TrainTestOptions
 
ensembleOptions - Variable in class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
The ensemble options.
ensembleSize - Variable in class org.tribuo.classification.ensemble.ClassificationEnsembleOptions
Number of base learners in the ensemble.
ensembleSize - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Number of trees in the ensemble.
ensembleSize - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Number of trees in the ensemble.
entropy(List<T>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon entropy, using histogram probability estimators.
Entropy - Class in org.tribuo.classification.dtree.impurity
A log_e entropy impurity measure.
Entropy() - Constructor for class org.tribuo.classification.dtree.impurity.Entropy
 
ENTROPY - Enum constant in enum class org.tribuo.classification.dtree.CARTClassificationOptions.ImpurityType
Uses Entropy.
entrySet() - Method in class org.tribuo.transform.TransformerMap
Get the feature names and associated list of transformers.
epochs - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Number of SGD epochs.
epochs - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
epochs - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
epochs - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Number of gradient descent epochs.
epochs - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Number of SGD epochs.
epochs - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
Number of SGD epochs.
epsilon - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
epsilon - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
Epsilon for AdaDelta, AdaGrad, AdaGradRDA, Adam.
epsilon - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
Regression value insensitivity for margin.
EPSILON - Static variable in class org.tribuo.transform.transformations.SimpleTransform
Epsilon for determining when two double values are the same.
EPSILON_SVR - Enum constant in enum class org.tribuo.regression.libsvm.SVMRegressionType.SVMMode
epsilon-insensitive SVR.
EQUAL_FREQUENCY - Enum constant in enum class org.tribuo.transform.transformations.BinningTransformation.BinningType
Creates bins of equal frequency (i.e., equal numbers of data points).
EQUAL_WIDTH - Enum constant in enum class org.tribuo.transform.transformations.BinningTransformation.BinningType
Creates bins of equal width over the data range.
equalFrequency(int) - Static method in class org.tribuo.transform.transformations.BinningTransformation
Returns a BinningTransformation which generates bins which contain the same amount of training data that is, each bin has an equal probability of occurrence in the training data.
equals(Object) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
equals(Object) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
equals(Object) - Method in class org.tribuo.anomaly.AnomalyFactory.AnomalyFactoryProvenance
 
equals(Object) - Method in class org.tribuo.anomaly.Event
 
equals(Object) - Method in class org.tribuo.classification.evaluation.LabelMetric
 
equals(Object) - Method in class org.tribuo.classification.Label
 
equals(Object) - Method in class org.tribuo.classification.LabelFactory
 
equals(Object) - Method in class org.tribuo.classification.LabelFactory.LabelFactoryProvenance
 
equals(Object) - Method in class org.tribuo.clustering.ClusterID
 
equals(Object) - Method in class org.tribuo.clustering.ClusteringFactory.ClusteringFactoryProvenance
 
equals(Object) - Method in class org.tribuo.clustering.ClusteringFactory
 
equals(Object) - Method in class org.tribuo.common.tree.LeafNode
 
equals(Object) - Method in class org.tribuo.common.tree.SplitNode
 
equals(Object) - Method in class org.tribuo.data.csv.CSVDataSource.CSVDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
Deprecated.
 
equals(Object) - Method in class org.tribuo.data.sql.SQLDataSource.SQLDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.data.text.DirectoryFileSource.DirectoryFileSourceProvenance
 
equals(Object) - Method in class org.tribuo.data.text.impl.SimpleStringDataSource.SimpleStringDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.data.text.impl.SimpleTextDataSource.SimpleTextDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
 
equals(Object) - Method in class org.tribuo.dataset.MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance
 
equals(Object) - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.evaluation.DescriptiveStats
 
equals(Object) - Method in class org.tribuo.evaluation.metrics.MetricTarget
 
equals(Object) - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.Feature
 
equals(Object) - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
 
equals(Object) - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
 
equals(Object) - Method in class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
 
equals(Object) - Method in class org.tribuo.impl.ArrayExample
 
equals(Object) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
equals(Object) - Method in class org.tribuo.impl.IndexedArrayExample
 
equals(Object) - Method in class org.tribuo.impl.ListExample
 
equals(Object) - Method in class org.tribuo.interop.ExternalTrainerProvenance
 
equals(Object) - Method in class org.tribuo.interop.oci.OCILabelConverter
 
equals(Object) - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
 
equals(Object) - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
 
equals(Object) - Method in class org.tribuo.json.JsonDataSource.JsonDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.math.la.DenseMatrix
 
equals(Object) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
equals(Object) - Method in class org.tribuo.math.la.DenseVector
Equals is defined mathematically, that is two SGDVectors are equal iff they have the same indices and the same values at those indices.
equals(Object) - Method in class org.tribuo.math.la.MatrixTuple
 
equals(Object) - Method in class org.tribuo.math.la.SparseVector
Equals is defined mathematically, that is two SGDVectors are equal iff they have the same indices and the same values at those indices.
equals(Object) - Method in class org.tribuo.math.la.VectorTuple
 
equals(Object) - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
 
equals(Object) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
equals(Object) - Method in class org.tribuo.multilabel.MultiLabel
 
equals(Object) - Method in class org.tribuo.multilabel.MultiLabelFactory
 
equals(Object) - Method in class org.tribuo.multilabel.MultiLabelFactory.MultiLabelFactoryProvenance
 
equals(Object) - Method in class org.tribuo.multilabel.MultiLabelInfo
 
equals(Object) - Method in class org.tribuo.provenance.DatasetProvenance
 
equals(Object) - Method in class org.tribuo.provenance.EnsembleModelProvenance
 
equals(Object) - Method in class org.tribuo.provenance.EvaluationProvenance
 
equals(Object) - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
 
equals(Object) - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
 
equals(Object) - Method in class org.tribuo.provenance.ModelProvenance
 
equals(Object) - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
 
equals(Object) - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
 
equals(Object) - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
 
equals(Object) - Method in class org.tribuo.regression.RegressionFactory
 
equals(Object) - Method in class org.tribuo.regression.RegressionFactory.RegressionFactoryProvenance
 
equals(Object) - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
equals(Object) - Method in class org.tribuo.regression.Regressor
Regressors are equal if they have the same number of dimensions and equal dimension names.
equals(Object) - Method in record class org.tribuo.reproducibility.ReproUtil.FeatureDiff
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.tribuo.reproducibility.ReproUtil.OutputDiff
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
 
equals(Object) - Method in class org.tribuo.SkeletalVariableInfo
 
equals(Object) - Method in class org.tribuo.transform.TransformationMap.TransformationList
 
equals(Object) - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
 
equals(Object) - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
 
equals(Object) - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
 
equals(Object) - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
 
equals(Object) - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
 
equals(Object) - Method in class org.tribuo.util.infotheory.impl.CachedPair
 
equals(Object) - Method in class org.tribuo.util.infotheory.impl.CachedTriple
 
equals(Object) - Method in class org.tribuo.util.infotheory.impl.Row
 
equals(Object) - Method in class org.tribuo.util.infotheory.impl.WeightCountTuple
 
equals(Object) - Method in class org.tribuo.util.IntDoublePair
 
equals(Object) - Method in class org.tribuo.util.MeanVarianceAccumulator
 
equalWidth(int) - Static method in class org.tribuo.transform.transformations.BinningTransformation
Returns a BinningTransformation which generates fixed equal width bins between the observed min and max values.
eta - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Step size shrinkage parameter (default 0.3, range [0,1]).
eta - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Step size shrinkage parameter (default 0.3, range [0,1]).
EUCLIDEAN - Enum constant in enum class org.tribuo.clustering.hdbscan.HdbscanTrainer.Distance
Euclidean (or l2) distance.
EUCLIDEAN - Enum constant in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Distance
Euclidean (or l2) distance.
euclideanDistance(SGDVector) - Method in class org.tribuo.math.la.DenseVector
The l2 or euclidean distance between this vector and the other vector.
euclideanDistance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
The l2 or euclidean distance between this vector and the other vector.
euclideanDistance(SGDVector) - Method in class org.tribuo.math.la.SparseVector
 
EV - Enum constant in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the Explained Variance of the predictions.
evaluate() - Method in class org.tribuo.evaluation.CrossValidation
Performs k fold cross validation, returning the k evaluations.
evaluate() - Method in class org.tribuo.evaluation.OnlineEvaluator
Creates an Evaluation containing all the current predictions.
evaluate(Model<T>, List<Prediction<T>>, List<T>, DataProvenance) - Method in interface org.tribuo.evaluation.Evaluator
Evaluates the model performance using the supplied predictions, returning an immutable Evaluation of the appropriate type.
evaluate(Model<T>, List<Prediction<T>>, DataProvenance) - Method in class org.tribuo.evaluation.AbstractEvaluator
Produces an evaluation for the supplied model and predictions by aggregating the appropriate statistics.
evaluate(Model<T>, List<Prediction<T>>, DataProvenance) - Method in interface org.tribuo.evaluation.Evaluator
Evaluates the model performance using the supplied predictions, returning an immutable Evaluation of the appropriate type.
evaluate(Model<T>, Dataset<T>) - Method in class org.tribuo.evaluation.AbstractEvaluator
Produces an evaluation for the supplied model and dataset, by calling Model.predict(org.tribuo.Example<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(Model<T>, Dataset<T>) - Method in interface org.tribuo.evaluation.Evaluator
Evaluates the dataset using the supplied model, returning an immutable Evaluation of the appropriate type.
evaluate(Model<T>, DataSource<T>) - Method in class org.tribuo.evaluation.AbstractEvaluator
Produces an evaluation for the supplied model and datasource, by calling Model.predict(org.tribuo.Example<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(Model<T>, DataSource<T>) - Method in interface org.tribuo.evaluation.Evaluator
Evaluates the dataset using the supplied model, returning an immutable Evaluation of the appropriate type.
evaluate(SequenceModel<T>, List<List<Prediction<T>>>, DataProvenance) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Produces an evaluation for the supplied model and predictions by aggregating the appropriate statistics.
evaluate(SequenceModel<T>, List<List<Prediction<T>>>, DataProvenance) - Method in interface org.tribuo.sequence.SequenceEvaluator
Evaluates the supplied model and predictions by aggregating the appropriate statistics.
evaluate(SequenceModel<T>, SequenceDataset<T>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Produces an evaluation for the supplied model and dataset, by calling SequenceModel.predict(org.tribuo.sequence.SequenceExample<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(SequenceModel<T>, SequenceDataset<T>) - Method in interface org.tribuo.sequence.SequenceEvaluator
Evaluates the dataset using the supplied model, returning an immutable evaluation.
evaluate(SequenceModel<T>, SequenceDataSource<T>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Produces an evaluation for the supplied model and datasource, by calling SequenceModel.predict(org.tribuo.sequence.SequenceExample<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(SequenceModel<T>, SequenceDataSource<T>) - Method in interface org.tribuo.sequence.SequenceEvaluator
Evaluates the datasource using the supplied model, returning an immutable evaluation.
Evaluation<T extends Output<T>> - Interface in org.tribuo.evaluation
An immutable evaluation of a specific model and dataset.
EvaluationAggregator - Class in org.tribuo.evaluation
Aggregates metrics from a list of evaluations, or a list of models and datasets.
EvaluationMetric<T extends Output<T>,C extends MetricContext<T>> - Interface in org.tribuo.evaluation.metrics
A metric that can be calculated for the specified output type.
EvaluationMetric.Average - Enum Class in org.tribuo.evaluation.metrics
Specifies what form of average to use for a EvaluationMetric.
EvaluationProvenance - Class in org.tribuo.provenance
Provenance for evaluations.
EvaluationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.EvaluationProvenance
Deserialization constructor.
EvaluationProvenance(ModelProvenance, DataProvenance) - Constructor for class org.tribuo.provenance.EvaluationProvenance
Constructs an evaluation provenance from the supplied provenances.
EvaluationRenderer<T extends Output<T>,E extends Evaluation<T>> - Interface in org.tribuo.evaluation
Renders an Evaluation into a String.
evaluator - Static variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
Evaluator<T extends Output<T>,E extends Evaluation<T>> - Interface in org.tribuo.evaluation
An evaluation factory which produces immutable Evaluations of a given Dataset using the given Model.
EVEN_OR_ODD_DAY - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The parity of the day of the year.
EVEN_OR_ODD_MONTH - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The parity of the month.
EVEN_OR_ODD_WEEK - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The parity of the week of the year as defined by ISO 8601.
EVEN_OR_ODD_YEAR - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The parity of the year.
Event - Class in org.tribuo.anomaly
An Output representing either an Event.EventType.ANOMALOUS or an Event.EventType.EXPECTED event.
Event(Event.EventType) - Constructor for class org.tribuo.anomaly.Event
Constructs a new event of the specified type with the default score of Event.DEFAULT_SCORE.
Event(Event.EventType, double) - Constructor for class org.tribuo.anomaly.Event
Constructs a new event of the specified type and score.
Event.EventType - Enum Class in org.tribuo.anomaly
The type of event.
EXACT - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
Exact greedy algorithm, enumerates all split candidates.
Example<T extends Output<T>> - Class in org.tribuo
An example used for training and evaluation.
Example(Example<T>) - Constructor for class org.tribuo.Example
Copies the output, weight and metadata into this example.
Example(T) - Constructor for class org.tribuo.Example
Construct an empty example using the supplied output and Example.DEFAULT_WEIGHT as the weight.
Example(T, float) - Constructor for class org.tribuo.Example
Construct an empty example using the supplied output and weight.
Example(T, float, Map<String, Object>) - Constructor for class org.tribuo.Example
Construct an empty example using the supplied output, weight and metadata.
Example(T, Map<String, Object>) - Constructor for class org.tribuo.Example
Construct an empty example using the supplied output, metadata and Example.DEFAULT_WEIGHT as the weight.
ExampleArray(SparseVector[], int[], double[]) - Constructor for class org.tribuo.classification.sgd.Util.ExampleArray
Constructs an example array.
examples - Variable in class org.tribuo.classification.example.DemoLabelDataSource
 
examples - Variable in class org.tribuo.common.xgboost.XGBoostTrainer.DMatrixTuple
 
exampleToNodes(Example<T>, ImmutableFeatureMap, List<FeatureNode>) - Static method in class org.tribuo.common.liblinear.LibLinearTrainer
Converts a Tribuo Example into a liblinear FeatureNode array, including a bias feature.
exampleToNodes(Example<T>, ImmutableFeatureMap, List<svm_node>) - Static method in class org.tribuo.common.libsvm.LibSVMTrainer
Convert the example into an array of svm_node which represents a sparse feature vector.
ExampleTransformer - Interface in org.tribuo.interop.onnx
Transforms a SparseVector, extracting the features from it as a OnnxTensor.
excuse(String) - Method in class org.tribuo.Excuse
Returns the features involved in this excuse.
Excuse<T extends Output<T>> - Class in org.tribuo
Holds an Example, a Prediction and a Map from String to List of Pairs that contains the per output explanation.
Excuse(Example<T>, Prediction<T>, Map<String, List<Pair<String, Double>>>) - Constructor for class org.tribuo.Excuse
Constructs an excuse for the prediction of the supplied example, using the feature weights.
exp - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Exponentiates the inputs
exp() - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that applies Math.exp(double).
expandRegexMapping(Collection<String>) - Method in class org.tribuo.data.columnar.RowProcessor
Uses similar logic to TransformationMap.validateTransformations(org.tribuo.FeatureMap) to check the regexes against the supplied list of field names.
expandRegexMapping(ImmutableFeatureMap) - Method in class org.tribuo.data.columnar.RowProcessor
Uses similar logic to TransformationMap.validateTransformations(org.tribuo.FeatureMap) to check the regexes against the supplied feature map.
expandRegexMapping(Model<T>) - Method in class org.tribuo.data.columnar.RowProcessor
Uses similar logic to TransformationMap.validateTransformations(org.tribuo.FeatureMap) to check the regexes against the ImmutableFeatureMap contained in the supplied Model.
EXPECTED - Enum constant in enum class org.tribuo.anomaly.Event.EventType
An expected event, with id 0.
EXPECTED_EVENT - Static variable in class org.tribuo.anomaly.AnomalyFactory
The expected event.
expectedCount - Variable in class org.tribuo.anomaly.AnomalyInfo
The number of expected events observed.
explain(CommandInterpreter, String[]) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Explains a text classification.
explain(String) - Method in class org.tribuo.classification.explanations.lime.LIMEText
 
explain(String) - Method in interface org.tribuo.classification.explanations.TextExplainer
Converts the supplied text into an Example, and generates an explanation of the contained Model's prediction.
explain(Map<String, String>) - Method in interface org.tribuo.classification.explanations.ColumnarExplainer
Explains the supplied data.
explain(Map<String, String>) - Method in class org.tribuo.classification.explanations.lime.LIMEColumnar
 
explain(Example<Label>) - Method in class org.tribuo.classification.explanations.lime.LIMEBase
 
explain(Example<Label>) - Method in interface org.tribuo.classification.explanations.TabularExplainer
Explain why the supplied Example is classified a certain way.
explainedVariance() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculatest the explained variance for all dimensions.
explainedVariance(MetricTarget<Regressor>, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the explained variance based on the supplied statistics.
explainedVariance(Regressor) - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates the explained variance of the ground truth using the predictions for the supplied dimension.
explainedVariance(Regressor, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the explained variance based on the supplied statistics for a single dimension.
explainWithSamples(Map<String, String>) - Method in class org.tribuo.classification.explanations.lime.LIMEColumnar
 
explainWithSamples(Example<Label>) - Method in class org.tribuo.classification.explanations.lime.LIMEBase
 
Explanation<T extends Output<T>> - Interface in org.tribuo.classification.explanations
An explanation knows what features are used, what the explaining Model is and what the original Model's prediction is.
explanationTrainer - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
expNormalize(double) - Method in class org.tribuo.math.la.DenseVector
An optimisation for the exponential normalizer when you already know the normalization constant.
ExpNormalizer - Class in org.tribuo.math.util
Normalizes the exponential values of the input array.
ExpNormalizer() - Constructor for class org.tribuo.math.util.ExpNormalizer
 
exportCombiner(ONNXNode) - Method in class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
Exports this voting combiner to ONNX.
exportCombiner(ONNXNode) - Method in class org.tribuo.classification.ensemble.VotingCombiner
Exports this voting combiner to ONNX.
exportCombiner(ONNXNode) - Method in interface org.tribuo.ensemble.EnsembleCombiner
Exports this ensemble combiner into the ONNX context of its input.
exportCombiner(ONNXNode) - Method in class org.tribuo.multilabel.ensemble.MultiLabelVotingCombiner
Exports this voting combiner to ONNX.
exportCombiner(ONNXNode) - Method in class org.tribuo.regression.ensemble.AveragingCombiner
Exports this averaging combiner, writing constructed nodes into the ONNXContext governing input and returning the leaf node of the combiner.
exportCombiner(ONNXNode, T) - Method in class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
Exports this voting combiner to ONNX.
exportCombiner(ONNXNode, T) - Method in class org.tribuo.classification.ensemble.VotingCombiner
Exports this voting combiner to ONNX
exportCombiner(ONNXNode, T) - Method in class org.tribuo.multilabel.ensemble.MultiLabelVotingCombiner
Exports this voting combiner to ONNX
exportCombiner(ONNXNode, T) - Method in class org.tribuo.regression.ensemble.AveragingCombiner
Exports this averaging combiner, writing constructed nodes into the ONNXContext governing input and returning the leaf node of the combiner.
exportCombiner(ONNXNode, U) - Method in interface org.tribuo.ensemble.EnsembleCombiner
Exports this ensemble combiner into the ONNX context of its input.
exportModel(String) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Exports this model as a SavedModelBundle, writing to the supplied directory.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.ExpNormalizer
Returns the ONNX softmax node over the 2nd dimension.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.NoopNormalizer
Returns its input.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.Normalizer
Applies ONNX ReduceMin, Sub, ReduceSum, and Div operations to input.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.SigmoidNormalizer
Returns the ONNX sigmoid node, operating independently over each element.
exportNormalizer(ONNXNode) - Method in interface org.tribuo.math.util.VectorNormalizer
Exports this normalizer to ONNX, returning the leaf of the appended graph and writing the nodes needed for normalization into the ONNXContext that input belongs to.
exportONNXModel(String, long) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel
 
exportONNXModel(String, long) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationModel
 
exportONNXModel(String, long) - Method in class org.tribuo.common.sgd.AbstractFMModel
Exports this Model as an ONNX protobuf.
exportONNXModel(String, long) - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
Exports this Model as an ONNX protobuf.
exportONNXModel(String, long) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
Exports this EnsembleModel as an ONNX model.
exportONNXModel(String, long) - Method in interface org.tribuo.ONNXExportable
Exports this Model as an ONNX protobuf.
exportONNXModel(String, long) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
 
exportONNXModel(String, long) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
 
exportONNXModel(String, long) - Method in class org.tribuo.regression.slm.SparseLinearModel
 
EXTERNAL - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
EXTERNAL = 1;
EXTERNAL_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
EXTERNAL_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
EXTERNAL = 1;
ExternalDatasetProvenance - Class in org.tribuo.interop
A dummy provenance used to describe the dataset of external models.
ExternalDatasetProvenance(String, OutputFactory<T>, boolean, int, int) - Constructor for class org.tribuo.interop.ExternalDatasetProvenance
An empty provenance used as a placeholder for externally trained models.
ExternalDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.interop.ExternalDatasetProvenance
Deserialization constructor.
ExternalModel<T extends Output<T>,U,V> - Class in org.tribuo.interop
This is the base class for third party models which are trained externally and loaded into Tribuo for prediction.
ExternalModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, Map<String, Integer>) - Constructor for class org.tribuo.interop.ExternalModel
Constructs an external model from a model trained outside of Tribuo.
ExternalModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, int[], int[], boolean) - Constructor for class org.tribuo.interop.ExternalModel
Constructs an external model from a model trained outside of Tribuo.
externalPrediction(OnnxTensor) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
Runs the session to make a prediction.
externalPrediction(DMatrix) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
externalPrediction(TensorMap) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
Runs the session to make a prediction.
externalPrediction(TensorMap) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
Runs the session to make a prediction.
externalPrediction(DenseMatrix) - Method in class org.tribuo.interop.oci.OCIModel
 
externalPrediction(U) - Method in class org.tribuo.interop.ExternalModel
Runs the external model's prediction function.
ExternalTrainerProvenance - Class in org.tribuo.interop
A dummy provenance for a model trained outside Tribuo.
ExternalTrainerProvenance(byte[]) - Constructor for class org.tribuo.interop.ExternalTrainerProvenance
Creates an external trainer provenance, computing the hash from the byte array and storing this instant as the timestamp, and the current working directory as the location.
ExternalTrainerProvenance(URL) - Constructor for class org.tribuo.interop.ExternalTrainerProvenance
Creates an external trainer provenance, storing the location and pulling in the timestamp and file hash.
ExternalTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.interop.ExternalTrainerProvenance
Used by the provenance serialization system.
EXTRA_TREES - Enum constant in enum class org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
Creates an ExtraTreesTrainer.
extract(LocalDate) - Method in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
Applies this enum's extraction function to the supplied date.
extract(ColumnarIterator.Row) - Method in class org.tribuo.data.columnar.extractors.IndexExtractor
 
extract(ColumnarIterator.Row) - Method in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
 
extract(ColumnarIterator.Row) - Method in interface org.tribuo.data.columnar.FieldExtractor
Returns Optional which is filled if extraction succeeded.
extract(T, String) - Method in class org.tribuo.data.text.impl.TextFeatureExtractorImpl
 
extract(T, String) - Method in interface org.tribuo.data.text.TextFeatureExtractor
Extracts an example from the supplied input text and output object.
extract(T, String) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Tokenizes the input using the loaded tokenizer, truncates the token list if it's longer than maxLength - 2 (to account for [CLS] and [SEP] tokens), and then passes the token list to BERTFeatureExtractor.extractExample(java.util.List<java.lang.String>).
extractData(Dataset<Event>, ImmutableOutputInfo<Event>, ImmutableFeatureMap) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
 
extractData(Dataset<Event>, ImmutableOutputInfo<Event>, ImmutableFeatureMap) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
 
extractData(Dataset<Label>, ImmutableOutputInfo<Label>, ImmutableFeatureMap) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
 
extractData(Dataset<Label>, ImmutableOutputInfo<Label>, ImmutableFeatureMap) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
 
extractData(Dataset<Regressor>, ImmutableOutputInfo<Regressor>, ImmutableFeatureMap) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionTrainer
 
extractData(Dataset<Regressor>, ImmutableOutputInfo<Regressor>, ImmutableFeatureMap) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
 
extractData(Dataset<T>, ImmutableOutputInfo<T>, ImmutableFeatureMap) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
Extracts the features and Outputs in LibLinear's format.
extractData(Dataset<T>, ImmutableOutputInfo<T>, ImmutableFeatureMap) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
Extracts the features and Outputs in LibSVM's format.
extractExample(List<String>) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Passes the tokens through BERT, replacing any unknown tokens with the [UNK] token.
extractExample(List<String>, T) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Passes the tokens through BERT, replacing any unknown tokens with the [UNK] token.
extractFeatures(List<Label>, double) - Method in class org.tribuo.classification.sequence.viterbi.DefaultFeatureExtractor
 
extractFeatures(List<Label>, double) - Method in interface org.tribuo.classification.sequence.viterbi.LabelFeatureExtractor
Generates features based on the previously produced labels.
extractFeatures(List<Label>, double) - Method in class org.tribuo.classification.sequence.viterbi.NoopFeatureExtractor
 
extractField(String) - Method in class org.tribuo.data.columnar.extractors.DateExtractor
 
extractField(String) - Method in class org.tribuo.data.columnar.extractors.DoubleExtractor
 
extractField(String) - Method in class org.tribuo.data.columnar.extractors.FloatExtractor
 
extractField(String) - Method in class org.tribuo.data.columnar.extractors.IdentityExtractor
 
extractField(String) - Method in class org.tribuo.data.columnar.extractors.IntExtractor
 
extractField(String) - Method in class org.tribuo.data.columnar.extractors.OffsetDateTimeExtractor
 
extractField(String) - Method in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
Extracts the field value, or returns Optional.empty() if it failed to parse.
extractMarshalledVariables(Graph, Session) - Static method in class org.tribuo.interop.tensorflow.TensorFlowUtil
Extracts a Map containing the name of each Tensorflow VariableV2 and the associated parameter array.
extractNames(OutputInfo<Regressor>) - Static method in class org.tribuo.regression.Regressor
Extracts the names from the supplied Regressor domain in their canonical order.
extractor - Variable in class org.tribuo.data.text.DirectoryFileSource
The extractor that we'll use to turn text into examples.
extractor - Variable in class org.tribuo.data.text.TextDataSource
The extractor that we'll use to turn text into examples.
extractOutput(Event) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
Converts an output into a double for use in training.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.anomaly.example.GaussianAnomalyDataSource.GaussianAnomalyDataSourceProvenance
Extracts the relevant provenance information fields for this class.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.clustering.example.GaussianClusterDataSource.GaussianClusterDataSourceProvenance
Extracts the relevant provenance information fields for this class.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.data.csv.CSVDataSource.CSVDataSourceProvenance
Separates this class's non-configurable fields from the configurable fields.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.data.sql.SQLDataSource.SQLDataSourceProvenance
 
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.data.text.DirectoryFileSource.DirectoryFileSourceProvenance
Splits the provenance into configured and non-configured values.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.data.text.impl.SimpleStringDataSource.SimpleStringDataSourceProvenance
 
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.data.text.impl.SimpleTextDataSource.SimpleTextDataSourceProvenance
 
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.datasource.AggregateConfigurableDataSource.AggregateConfigurableDataSourceProvenance
Extracts the class name and host type fields from the provenance map.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
Separates out the configured and non-configured provenance values.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance
 
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.json.JsonDataSource.JsonDataSourceProvenance
Splits the provenance into configurable and non-configurable provenances.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.multilabel.example.MultiLabelGaussianDataSource.MultiLabelGaussianDataSourceProvenance
Extracts the relevant provenance information fields for this class.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.provenance.SkeletalTrainerProvenance
 
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.regression.example.GaussianDataSource.GaussianDataSourceProvenance
Extracts the relevant provenance information fields for this class.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.regression.example.NonlinearGaussianDataSource.NonlinearGaussianDataSourceProvenance
Extracts the relevant provenance information fields for this class.
extractSequenceExample(List<String>, boolean) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Passes the tokens through BERT, replacing any unknown tokens with the [UNK] token.
extractSequenceExample(List<String>, List<T>, boolean) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Passes the tokens through BERT, replacing any unknown tokens with the [UNK] token.
extractTFProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance
 
extractTFProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
 
ExtraTreesTrainer<T extends Output<T>> - Class in org.tribuo.common.tree
A trainer which produces an Extremely Randomized Tree Ensemble.
ExtraTreesTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int) - Constructor for class org.tribuo.common.tree.ExtraTreesTrainer
Constructs an ExtraTreesTrainer with the default seed Trainer.DEFAULT_SEED.
ExtraTreesTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int, long) - Constructor for class org.tribuo.common.tree.ExtraTreesTrainer
Constructs an ExtraTreesTrainer with the supplied seed, trainer, combining function and number of members.

F

F_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
f1(double, double, double, double) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Computes the F_1 score.
f1(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The F1 for this label.
f1(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Computes the F_1 score.
f1(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
f1(T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the F_1 score, i.e., the harmonic mean of the precision and recall.
F1 - Enum constant in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
The F_1 score, i.e., the harmonic mean of the precision and the recall.
F1 - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The F_1 score, i.e., the harmonic mean of the precision and the recall.
F1 - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The F_1 score, i.e., the harmonic mean of the precision and the recall.
factorizedDimSize - Variable in class org.tribuo.common.sgd.AbstractFMTrainer
 
factorSize - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Factor size.
factory - Static variable in class org.tribuo.classification.example.DemoLabelDataSource
 
Feature - Class in org.tribuo
A class for features.
Feature(String, double) - Constructor for class org.tribuo.Feature
Creates an immutable feature.
FEATURE_TYPE - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
The name of the provenance field for the idx feature type.
FEATURE_VALUE - Static variable in class org.tribuo.data.columnar.processors.field.IdentityProcessor
The value of the emitted features.
FeatureAggregator - Interface in org.tribuo.data.text
An interface for aggregating feature values into other values.
featureBackwardMapping - Variable in class org.tribuo.interop.ExternalModel
 
featureConverter - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceModel
 
featureConverter - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
featureConverter - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
FeatureConverter - Interface in org.tribuo.interop.tensorflow
Transforms an Example or SGDVector, extracting the features from it as a TensorMap.
featureDiff() - Method in record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Returns the value of the featureDiff record component.
FeatureDiff(Set<String>, Set<String>) - Constructor for record class org.tribuo.reproducibility.ReproUtil.FeatureDiff
Creates an instance of a FeatureDiff record class.
featureForwardMapping - Variable in class org.tribuo.interop.ExternalModel
 
FeatureHasher - Class in org.tribuo.data.text.impl
Hashes the feature names to reduce the dimensionality.
FeatureHasher(int) - Constructor for class org.tribuo.data.text.impl.FeatureHasher
Constructs a feature hasher using the supplied hash dimension.
featureIDMap - Variable in class org.tribuo.ImmutableDataset
A map from feature names to IDs for the features found in this dataset.
featureIDMap - Variable in class org.tribuo.Model
The features this model knows about.
featureIDMap - Variable in class org.tribuo.sequence.ImmutableSequenceDataset
A map from feature names to IDs for the features found in this dataset.
featureIDMap - Variable in class org.tribuo.sequence.SequenceModel
 
featureIDs - Variable in class org.tribuo.impl.IndexedArrayExample
Feature id numbers from the internal featureMap.
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Shows information on a particular feature.
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.data.DatasetExplorer
Shows information on a particular feature.
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.ModelExplorer
Shows a specific feature's information.
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.sequence.SequenceModelExplorer
Shows information on a particular feature.
featureIterator() - Method in class org.tribuo.sequence.SequenceExample
Creates an iterator over every feature in this sequence.
featureMap - Variable in class org.tribuo.MutableDataset
A map from feature names to feature info objects.
featureMap - Variable in class org.tribuo.sequence.MutableSequenceDataset
A map from feature names to IDs for the features found in this dataset.
FeatureMap - Class in org.tribuo
A map from Strings to VariableInfo objects storing information about a feature.
FeatureMap() - Constructor for class org.tribuo.FeatureMap
Constructs an empty feature map.
FeatureMap(Map<String, ? extends VariableInfo>) - Constructor for class org.tribuo.FeatureMap
Constructs a feature map wrapping the supplied map.
FeatureMap(FeatureMap) - Constructor for class org.tribuo.FeatureMap
Constructs a deep copy of the supplied feature map.
featureNameComparator() - Static method in class org.tribuo.Feature
A comparator using the lexicographic ordering of feature names.
featureNames - Variable in class org.tribuo.impl.ArrayExample
Feature names array.
featureNames - Variable in class org.tribuo.impl.BinaryFeaturesExample
Feature names array.
FeatureProcessor - Interface in org.tribuo.data.columnar
Takes a list of columnar features and adds new features or removes existing features.
features - Variable in class org.tribuo.classification.sgd.Util.ExampleArray
The examples encoded as sparse vectors.
features - Variable in class org.tribuo.classification.sgd.Util.SequenceExampleArray
The array of sequence example features.
FEATURES_FILE_MODIFIED_TIME - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
The name of the features file modified time provenance field.
FEATURES_RESOURCE_HASH - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
The name of the provenance field for the feature file hash.
FeatureTransformer - Interface in org.tribuo.data.text
A feature transformer maps a list of features to a new list of features Useful for example to apply the hashing trick to a set of features
FeatureTuple() - Constructor for class org.tribuo.impl.IndexedArrayExample.FeatureTuple
Constructs an empty feature tuple.
FeatureTuple(String, int, double) - Constructor for class org.tribuo.impl.IndexedArrayExample.FeatureTuple
Constructs a feature tuple using the specified values.
featureValues - Variable in class org.tribuo.impl.ArrayExample
Feature values array.
FeedForwardParameters - Interface in org.tribuo.math
A Parameters for models which make a single prediction like logistic regressions and neural networks.
feedInto(Session.Runner) - Method in class org.tribuo.interop.tensorflow.TensorMap
Feeds the tensors in this FeedDict into the runner.
FIELD_NAME - Static variable in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
The field name this response processor looks for, which is ignored anyway as this processor always returns Optional.empty().
FieldExtractor<T> - Interface in org.tribuo.data.columnar
Extracts a value from a field to be placed in an Example's metadata field.
fieldName - Variable in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
 
FieldProcessor - Interface in org.tribuo.data.columnar
An interface for things that process the columns in a data set.
FieldProcessor.GeneratedFeatureType - Enum Class in org.tribuo.data.columnar
The types of generated features.
fieldProcessorMap - Variable in class org.tribuo.data.columnar.RowProcessor
 
FieldResponseProcessor<T extends Output<T>> - Class in org.tribuo.data.columnar.processors.response
A response processor that returns the value(s) in a given (set of) fields.
FieldResponseProcessor(String, String, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Constructs a response processor which passes the field value through the output factory.
FieldResponseProcessor(List<String>, String, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Constructs a response processor which passes the field value through the output factory.
FieldResponseProcessor(List<String>, List<String>, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Constructs a response processor which passes the field value through the output factory.
FieldResponseProcessor(List<String>, List<String>, OutputFactory<T>, boolean) - Constructor for class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Constructs a response processor which passes the field value through the output factory.
FieldResponseProcessor(List<String>, List<String>, OutputFactory<T>, boolean, boolean) - Constructor for class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Constructs a response processor which passes the field value through the output factory.
fields - Variable in class org.tribuo.data.columnar.ColumnarIterator
The column headers for this iterator.
FILE_MODIFIED_TIME - Static variable in interface org.tribuo.provenance.DataSourceProvenance
The name of the provenance field for the file timestamp.
fileCompleter() - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Completers for filenames.
fileCompleter() - Method in class org.tribuo.data.DatasetExplorer
The filename completer.
fileCompleter() - Method in class org.tribuo.ModelExplorer
Completers for files.
fileCompleter() - Method in class org.tribuo.sequence.SequenceModelExplorer
Completers for files.
fill(double) - Method in class org.tribuo.math.la.DenseVector
Fills this DenseVector with value.
fill(int[]) - Method in class org.tribuo.common.tree.impl.IntArrayContainer
Overwrites values from the supplied array into this array.
fill(IntArrayContainer) - Method in class org.tribuo.common.tree.impl.IntArrayContainer
Overwrites values in this array with the supplied array.
finalise() - Method in class org.tribuo.math.optimisers.AdaGradRDA
 
finalise() - Method in class org.tribuo.math.optimisers.ParameterAveraging
This sets the parameters to their average value.
finalise() - Method in class org.tribuo.math.optimisers.Pegasos
 
finalise() - Method in interface org.tribuo.math.StochasticGradientOptimiser
Finalises the gradient optimisation, setting the parameters to their correct values.
FIRST - Enum constant in enum class org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Select the first feature value in the list.
FIRST - Enum constant in enum class org.tribuo.util.infotheory.WeightedInformationTheory.VariableSelector
The first variable is weighted.
FIRST_CLASS - Static variable in class org.tribuo.classification.example.DemoLabelDataSource
The first class.
firstCount - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
The first marginal distribution.
firstDimensionName - Static variable in class org.tribuo.regression.example.RegressionDataGenerator
Name of the first output dimension.
fixSize() - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
Fixes the size of the backing array.
fixSize() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Fixes the size of each InvertedFeature's inner arrays.
FLOAT - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
FLOAT = 1;
FLOAT - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Basic types.
FLOAT - Enum constant in enum class org.tribuo.datasource.IDXDataSource.IDXType
A 32-bit float.
FLOAT_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
FLOAT_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
FLOAT = 1;
FLOAT_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Basic types.
FLOAT16 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
IEEE754 half-precision floating-point format (16 bits wide).
FLOAT16_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
IEEE754 half-precision floating-point format (16 bits wide).
FloatExtractor - Class in org.tribuo.data.columnar.extractors
Extracts the field value and converts it to a float.
FloatExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.FloatExtractor
Extracts a float value from the supplied field name.
FloatExtractor(String, String) - Constructor for class org.tribuo.data.columnar.extractors.FloatExtractor
Extracts a float value from the supplied field name.
floatInput(int) - Method in class org.tribuo.util.onnx.ONNXContext
Creates an input node for this ONNXContext, with the name "input", of dimension [batch_size, featureDimension], and of type float32.
floatInput(String, int) - Method in class org.tribuo.util.onnx.ONNXContext
Creates an input node for this ONNXContext, with the given name, of dimension [batch_size, featureDimension], and of type float32.
floatMatrix(ONNXContext, String, Matrix, boolean) - Static method in class org.tribuo.math.onnx.ONNXMathUtils
Builds a ONNXInitializer containing the Matrix.
floatOutput(int) - Method in class org.tribuo.util.onnx.ONNXContext
Creates an output node for this ONNXContext, with the name "output", of dimension [batch_size, outputDimension], and of type float32.
floatOutput(String, int) - Method in class org.tribuo.util.onnx.ONNXContext
Creates an output node for this ONNXContext, with the given name, of dimension [batch_size, outputDimension], and of type float32.
FLOATS - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
FLOATS = 6;
FLOATS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
FLOATS_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
FLOATS = 6;
floatTensor(String, List<Integer>, Consumer<FloatBuffer>) - Method in class org.tribuo.util.onnx.ONNXContext
Creates a tensor for this ONNXContext, populated as ONNXUtils.floatTensorBuilder(ONNXContext, String, List, Consumer).
floatTensorBuilder(ONNXContext, String, List<Integer>, Consumer<FloatBuffer>) - Static method in class org.tribuo.util.onnx.ONNXUtils
Generic method to create float OnnxMl.TensorProto instances.
floatVector(ONNXContext, String, SGDVector) - Static method in class org.tribuo.math.onnx.ONNXMathUtils
Builds a ONNXInitializer containing the SGDVector.
FMClassificationModel - Class in org.tribuo.classification.sgd.fm
The inference time version of a factorization machine trained using SGD.
FMClassificationOptions - Class in org.tribuo.classification.sgd.fm
CLI options for training a factorization machine classifier.
FMClassificationOptions() - Constructor for class org.tribuo.classification.sgd.fm.FMClassificationOptions
 
FMClassificationOptions.LossEnum - Enum Class in org.tribuo.classification.sgd.fm
Available loss types.
FMClassificationTrainer - Class in org.tribuo.classification.sgd.fm
A trainer for a classification factorization machine using SGD.
FMClassificationTrainer(LabelObjective, StochasticGradientOptimiser, int, int, int, long, int, double) - Constructor for class org.tribuo.classification.sgd.fm.FMClassificationTrainer
Constructs an SGD trainer for a factorization machine.
FMClassificationTrainer(LabelObjective, StochasticGradientOptimiser, int, int, long, int, double) - Constructor for class org.tribuo.classification.sgd.fm.FMClassificationTrainer
Constructs an SGD trainer for a factorization machine.
FMClassificationTrainer(LabelObjective, StochasticGradientOptimiser, int, long, int, double) - Constructor for class org.tribuo.classification.sgd.fm.FMClassificationTrainer
Constructs an SGD trainer for a factorization machine.
fmEpochs - Variable in class org.tribuo.classification.sgd.fm.FMClassificationOptions
Number of SGD epochs.
fmEpochs - Variable in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Number of SGD epochs.
fmFactorSize - Variable in class org.tribuo.classification.sgd.fm.FMClassificationOptions
Factor size.
fmFactorSize - Variable in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Factor size.
fmix32(int) - Static method in class org.tribuo.util.MurmurHash3
32-bit mixing function.
fmix64(long) - Static method in class org.tribuo.util.MurmurHash3
64-bit mixing function.
fmLoggingInterval - Variable in class org.tribuo.classification.sgd.fm.FMClassificationOptions
Log the objective after n examples.
fmLoggingInterval - Variable in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Log the objective after n examples.
fmMinibatchSize - Variable in class org.tribuo.classification.sgd.fm.FMClassificationOptions
Minibatch size.
fmMinibatchSize - Variable in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Minibatch size.
FMMultiLabelModel - Class in org.tribuo.multilabel.sgd.fm
The inference time version of a multi-label factorization machine trained using SGD.
FMMultiLabelOptions - Class in org.tribuo.multilabel.sgd.fm
CLI options for training a linear classifier.
FMMultiLabelOptions() - Constructor for class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
 
FMMultiLabelOptions.LossEnum - Enum Class in org.tribuo.multilabel.sgd.fm
Available loss types.
FMMultiLabelTrainer - Class in org.tribuo.multilabel.sgd.fm
A trainer for a multi-label classification factorization machine using SGD.
FMMultiLabelTrainer(MultiLabelObjective, StochasticGradientOptimiser, int, int, int, long, int, double) - Constructor for class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
Constructs an SGD trainer for a multi-label factorization machine.
FMMultiLabelTrainer(MultiLabelObjective, StochasticGradientOptimiser, int, int, long, int, double) - Constructor for class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
Constructs an SGD trainer for a multi-label factorization machine.
FMMultiLabelTrainer(MultiLabelObjective, StochasticGradientOptimiser, int, long, int, double) - Constructor for class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
Constructs an SGD trainer for a multi-label factorization machine.
fmObjective - Variable in class org.tribuo.classification.sgd.fm.FMClassificationOptions
Loss function.
fmObjective - Variable in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Loss function.
FMParameters - Class in org.tribuo.common.sgd
A Parameters for factorization machines.
FMParameters(SplittableRandom, int, int, int, double) - Constructor for class org.tribuo.common.sgd.FMParameters
Constructor.
FMRegressionModel - Class in org.tribuo.regression.sgd.fm
The inference time model of a regression factorization machine trained using SGD.
FMRegressionOptions() - Constructor for class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
 
FMRegressionTrainer - Class in org.tribuo.regression.sgd.fm
A trainer for a regression factorization machine using SGD.
FMRegressionTrainer(RegressionObjective, StochasticGradientOptimiser, int, int, int, long, int, double, boolean) - Constructor for class org.tribuo.regression.sgd.fm.FMRegressionTrainer
Constructs an SGD trainer for a factorization machine.
FMRegressionTrainer(RegressionObjective, StochasticGradientOptimiser, int, int, long, int, double, boolean) - Constructor for class org.tribuo.regression.sgd.fm.FMRegressionTrainer
Constructs an SGD trainer for a factorization machine.
FMRegressionTrainer(RegressionObjective, StochasticGradientOptimiser, int, long, int, double, boolean) - Constructor for class org.tribuo.regression.sgd.fm.FMRegressionTrainer
Constructs an SGD trainer for a factorization machine.
fmVariance - Variable in class org.tribuo.classification.sgd.fm.FMClassificationOptions
Variance of the initialization gaussian.
fmVariance - Variable in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Variance of the initialization gaussian.
fn() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the micro averaged number of false negatives.
fn() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of false negatives.
fn() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the micro averaged false negative count.
fn() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
fn(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
fn(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The false negative count for this label.
fn(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Returns the number of false negatives, possibly averaged depending on the metric target.
fn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
fn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
fn(T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the number of false negatives, i.e., the number of times the true label was incorrectly predicted as another label.
fn(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of false negatives for the supplied label.
FN - Enum constant in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
The number of false negatives.
FN - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The number of false negatives.
FN - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The number of false negatives.
foreachIndexedInPlace(ToDoubleBiFunction<Integer, Double>) - Method in class org.tribuo.math.la.DenseVector
 
foreachIndexedInPlace(ToDoubleBiFunction<Integer, Double>) - Method in interface org.tribuo.math.la.SGDVector
Applies a ToDoubleBiFunction elementwise to this SGDVector.
foreachIndexedInPlace(ToDoubleBiFunction<Integer, Double>) - Method in class org.tribuo.math.la.SparseVector
Applies a ToDoubleBiFunction elementwise to this SGDVector.
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseMatrix
 
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
 
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
Applies a DoubleUnaryOperator elementwise to this SGDVector.
foreachInPlace(DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor
Applies a DoubleUnaryOperator elementwise to this Tensor.
forEachRemaining(Consumer<? super ColumnarIterator.Row>) - Method in class org.tribuo.data.columnar.ColumnarIterator
 
formatDuration(long, long) - Static method in class org.tribuo.util.Util
Formats a duration given two times in milliseconds.
forNumber(int) - Static method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
 
forNumber(int) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
 
forNumber(int) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
 
forNumber(int) - Static method in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
 
forNumber(int) - Static method in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
forNumber(int) - Static method in enum class ai.onnx.proto.OnnxMl.Version
 
forTarget(MetricTarget<Label>) - Method in enum class org.tribuo.classification.evaluation.LabelMetrics
Gets the LabelMetric wrapped around the supplied MetricTarget.
forTarget(MetricTarget<ClusterID>) - Method in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
Constructs the metric for the specified metric target.
forTarget(MetricTarget<MultiLabel>) - Method in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
Get the metric for the supplied target.
fp() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the micro average of the number of false positives across all the labels, i.e., the total number of false positives.
fp() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of false positives.
fp() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the micro averaged false positive count.
fp() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
fp(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
fp(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The false positive count for this label.
fp(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Returns the number of false positives, possibly averaged depending on the metric target.
fp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
fp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
fp(T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the number of false positives, i.e., the number of times this label was predicted but it was not the true label..
fp(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of false positives for the supplied label.
FP - Enum constant in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
The number of false positives.
FP - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The number of false positives.
FP - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The number of false positives.
fpr - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.ROC
The false positive rate at the corresponding threshold.
fraction - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Fraction of features in split.
fractionFeaturesInSplit - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
Number of features to sample per split.
frequencyBasedSample(Random, long) - Method in class org.tribuo.CategoricalInfo
Samples a value from this feature according to the frequency of observation.
frequencyBasedSample(SplittableRandom, long) - Method in class org.tribuo.CategoricalInfo
Samples a value from this feature according to the frequency of observation.
fscore(double, double, double, double, double) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Computes the Fscore.
fscore(MetricTarget<T>, ConfusionMatrix<T>, double) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Computes the Fscore.
FTRL - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The FTRL optimiser.
fullEquals(Event) - Method in class org.tribuo.anomaly.Event
 
fullEquals(Label) - Method in class org.tribuo.classification.Label
 
fullEquals(ClusterID) - Method in class org.tribuo.clustering.ClusterID
 
fullEquals(MultiLabel) - Method in class org.tribuo.multilabel.MultiLabel
 
fullEquals(Regressor) - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
fullEquals(Regressor) - Method in class org.tribuo.regression.Regressor
 
fullEquals(T) - Method in interface org.tribuo.Output
Compares other to this output.
FULLY_WEIGHTED_VOTING - Enum constant in enum class org.tribuo.common.nearest.KNNClassifierOptions.EnsembleCombinerType
FullyWeightedVotingCombiner - Class in org.tribuo.classification.ensemble
A combiner which performs a weighted or unweighted vote across the predicted labels.
FullyWeightedVotingCombiner() - Constructor for class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
Constructs a weighted voting combiner.

G

G_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
gamma - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
Gamma value in kernel function.
gamma - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Minimum loss reduction to make a split (default 0, range [0,inf]).
gamma - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Minimum loss reduction to make a split (default 0, range [0,inf]).
GAMMA - Enum constant in enum class org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Gamma loss function.
GATHER - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Gathers elements from the first argument (of rank r) indexed by the second argument (of rank q) producing a tensor of rank q + r - 1.
gatherAcrossDim1(int[]) - Method in class org.tribuo.math.la.DenseMatrix
Constructs a dense vector by gathering values across dimension 1.
gatherAcrossDim2(int[]) - Method in class org.tribuo.math.la.DenseMatrix
Constructs a dense vector by gathering values across dimension 2.
GAUSSIAN - Enum constant in enum class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Samples from a Gaussian using the means and variances from the training data.
gaussianAnomaly() - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Generates two datasets, one without anomalies drawn from a single gaussian and the second drawn from a mixture of two gaussians, with the second tagged anomalous.
gaussianAnomaly(long, double) - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Generates two datasets, one without anomalies drawn from a single gaussian and the second drawn from a mixture of two gaussians, with the second tagged anomalous.
GaussianAnomalyDataSource - Class in org.tribuo.anomaly.example
Generates an anomaly detection dataset sampling each feature uniformly from a univariate Gaussian.
GaussianAnomalyDataSource(int, double[], double[], double[], double[], float, long) - Constructor for class org.tribuo.anomaly.example.GaussianAnomalyDataSource
Generates anomaly detection examples sampling each feature uniformly from a univariate Gaussian.
GaussianAnomalyDataSource(int, float, long) - Constructor for class org.tribuo.anomaly.example.GaussianAnomalyDataSource
Generates anomaly detection examples sampling each feature uniformly from a univariate Gaussian.
GaussianAnomalyDataSource.GaussianAnomalyDataSourceProvenance - Class in org.tribuo.anomaly.example
GaussianAnomalyDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.anomaly.example.GaussianAnomalyDataSource.GaussianAnomalyDataSourceProvenance
Constructs a provenance from the marshalled form.
GaussianClusterDataSource - Class in org.tribuo.clustering.example
Generates a clustering dataset drawn from a mixture of 5 Gaussians.
GaussianClusterDataSource(int, double[], double[], double[], double[], double[], double[], double[], double[], double[], double[], double[], long) - Constructor for class org.tribuo.clustering.example.GaussianClusterDataSource
Generates a clustering dataset drawn from a mixture of 5 Gaussians.
GaussianClusterDataSource(int, long) - Constructor for class org.tribuo.clustering.example.GaussianClusterDataSource
Generates a clustering dataset drawn from a mixture of 5 Gaussians.
GaussianClusterDataSource.GaussianClusterDataSourceProvenance - Class in org.tribuo.clustering.example
GaussianClusterDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.clustering.example.GaussianClusterDataSource.GaussianClusterDataSourceProvenance
Constructs a provenance from the marshalled form.
gaussianClusters(long, long) - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
Generates a dataset drawn from a mixture of 5 2d gaussians.
GaussianDataSource - Class in org.tribuo.regression.example
Generates a single dimensional output drawn from N(slope*x + intercept,variance).
GaussianDataSource(int, float, float, float, float, float, long) - Constructor for class org.tribuo.regression.example.GaussianDataSource
Generates a single dimensional output drawn from N(slope*x + intercept,variance).
GaussianDataSource.GaussianDataSourceProvenance - Class in org.tribuo.regression.example
Provenance for GaussianDataSource.
GaussianDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.regression.example.GaussianDataSource.GaussianDataSourceProvenance
Constructs a provenance from the marshalled form.
GaussianLabelDataSource - Class in org.tribuo.classification.example
A data source for two classes generated from separate Gaussians.
GaussianLabelDataSource(int, long, double[], double[], double[], double[]) - Constructor for class org.tribuo.classification.example.GaussianLabelDataSource
Constructs a data source which contains two classes where each class is sampled from a 2d Gaussian with the specified parameters.
GBTREE - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
A gradient boosted decision tree.
GEMM - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
General Matrix Multiply: alpha*AB + beta*C.
general - Variable in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
Options for loading in data.
general - Variable in class org.tribuo.classification.experiments.RunAll.RunAllOptions
Options for loading in data.
general - Variable in class org.tribuo.classification.experiments.TrainTest.AllClassificationOptions
Options for loading in data.
general - Variable in class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
The data loading options.
general - Variable in class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
The data loading options.
general - Variable in class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
The data loading options.
general - Variable in class org.tribuo.classification.sgd.fm.TrainTest.TrainTestOptions
 
general - Variable in class org.tribuo.classification.sgd.kernel.TrainTest.TrainTestOptions
The data loading options.
general - Variable in class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
The data loading options.
general - Variable in class org.tribuo.classification.xgboost.TrainTest.TrainTestOptions
The data loading options.
general - Variable in class org.tribuo.clustering.hdbscan.TrainTest.HdbscanCLIOptions
The data loading options.
general - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
The data loading options.
general - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
Data loading options.
general - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
The data loading options.
general - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
The data loading options.
general - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
The data loading options.
general - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
The dataset loading options.
general - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
The dataset loading options.
general - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
The data loading options.
general - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
The data loading options.
generalOptions - Variable in class org.tribuo.classification.dtree.TrainTest.TrainTestOptions
The data loading options.
generate() - Method in class org.tribuo.classification.example.CheckerboardDataSource
 
generate() - Method in class org.tribuo.classification.example.ConcentricCirclesDataSource
 
generate() - Method in class org.tribuo.classification.example.DemoLabelDataSource
Generates the examples using the configured fields.
generate() - Method in class org.tribuo.classification.example.GaussianLabelDataSource
 
generate() - Method in class org.tribuo.classification.example.InterlockingCrescentsDataSource
 
generate() - Method in class org.tribuo.classification.example.NoisyInterlockingCrescentsDataSource
 
generateBootstrap() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
Generates the indices from this DatasetViewProvenance by rerunning the bootstrap sample.
generateBootstrapIndices(int, Random) - Static method in class org.tribuo.util.Util
Draws a bootstrap sample of indices.
generateBootstrapIndices(int, SplittableRandom) - Static method in class org.tribuo.util.Util
Draws a bootstrap sample of indices.
generateCDF(double[]) - Static method in class org.tribuo.util.Util
Generates a cumulative distribution function from the supplied probability mass function.
generateCDF(float[]) - Static method in class org.tribuo.util.Util
Generates a cumulative distribution function from the supplied probability mass function.
generateCDF(long[], long) - Static method in class org.tribuo.util.Util
Generates a cumulative distribution function from the supplied probability mass function.
generateCorrelated(int, int, double, double) - Static method in class org.tribuo.util.infotheory.example.InformationTheoryDemo
These correlations don't map to mutual information values, as if xyDraw is above xyCorrelation then the draw is completely random.
generateDataset() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator
Generate training and testing datasets.
generateDataset(int, double[], double[], double[], double[], double[], double[], double[], double[], double[], double[], double[], long) - Static method in class org.tribuo.clustering.example.GaussianClusterDataSource
Generates a clustering dataset drawn from a mixture of 5 Gaussians.
generateDataset(int, double[], double[], double[], double[], float, long) - Static method in class org.tribuo.anomaly.example.GaussianAnomalyDataSource
Generates an anomaly detection dataset sampling each feature uniformly from a univariate Gaussian.
generateDataset(int, float[], float[], float[], float[], boolean[], float, float[], float[], long) - Static method in class org.tribuo.multilabel.example.MultiLabelGaussianDataSource
Generates a multi-label output drawn from three gaussian functions.
generateDataset(int, float[], float, float, float, float, float, float, long) - Static method in class org.tribuo.regression.example.NonlinearGaussianDataSource
Generates a single dimensional output drawn from N(w_0*x_0 + w_1*x_1 + w_2*x_1*x_0 + w_3*x_1*x_1*x_1 + intercept,variance).
generateDataset(int, float, float, float, float, float, long) - Static method in class org.tribuo.regression.example.GaussianDataSource
Generates a single dimensional output drawn from N(slope*x + intercept,variance).
generateEmptyExample() - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
This generates a sequence example with no examples.
generateExample(long, Map<String, String>, boolean) - Method in class org.tribuo.data.columnar.RowProcessor
Generate an Example from the supplied row.
generateExample(Map<String, String>, boolean) - Method in class org.tribuo.data.columnar.RowProcessor
Generate an Example from the supplied row.
generateExample(ColumnarIterator.Row, boolean) - Method in class org.tribuo.data.columnar.RowProcessor
Generate an Example from the supplied row.
generateFeatureName(String, String) - Static method in class org.tribuo.data.columnar.ColumnarFeature
Generates a feature name based on the field name and the name.
generateFeatureName(String, String, String) - Static method in class org.tribuo.data.columnar.ColumnarFeature
Generates a feature name used for conjunction features.
generateFeatures(Map<String, String>) - Method in class org.tribuo.data.columnar.RowProcessor
Generates the features from the supplied row.
generateGorillaA() - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
Generates a sequence example with a mixture of features and three labels "O", "Status" and "Monkey".
generateGorillaB() - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
Generates a sequence example with a mixture of features and three labels "O", "Status" and "Monkey".
generateGorillaDataset(int) - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
Generates a simple dataset consisting of numCopies repeats of two sequences.
generateHashedFeatureMap(FeatureMap, Hasher) - Static method in class org.tribuo.hash.HashedFeatureMap
Converts a standard FeatureMap by hashing each entry using the supplied hash function Hasher.
generateIDs(List<? extends VariableInfo>) - Static method in class org.tribuo.ImmutableFeatureMap
Generates the feature ids by sorting the features with the String comparator, then sequentially numbering them.
generateIDs(FeatureMap) - Static method in class org.tribuo.ImmutableFeatureMap
Generates the feature ids by sorting the features with the String comparator, then sequentially numbering them.
generateImmutableOutputInfo() - Method in class org.tribuo.anomaly.AnomalyInfo
 
generateImmutableOutputInfo() - Method in class org.tribuo.classification.LabelInfo
 
generateImmutableOutputInfo() - Method in class org.tribuo.clustering.ClusteringInfo
 
generateImmutableOutputInfo() - Method in class org.tribuo.multilabel.MultiLabelInfo
 
generateImmutableOutputInfo() - Method in interface org.tribuo.OutputInfo
Generates an ImmutableOutputInfo which has a copy of the data in this OutputInfo, but also has id values and is immutable.
generateImmutableOutputInfo() - Method in class org.tribuo.regression.RegressionInfo
 
generateInfo() - Method in class org.tribuo.anomaly.AnomalyFactory
 
generateInfo() - Method in class org.tribuo.classification.LabelFactory
Generates an empty MutableLabelInfo.
generateInfo() - Method in class org.tribuo.clustering.ClusteringFactory
 
generateInfo() - Method in class org.tribuo.multilabel.MultiLabelFactory
 
generateInfo() - Method in interface org.tribuo.OutputFactory
Generates the appropriate MutableOutputInfo so the output values can be tracked by a Dataset or other aggregate.
generateInfo() - Method in class org.tribuo.regression.RegressionFactory
 
generateInvalidExample() - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
This generates a sequence example with features that are unused by the training data.
generateLabelString(Set<Label>) - Static method in class org.tribuo.multilabel.MultiLabelFactory
Generates a comma separated string of labels from a Set of Label.
generateMetadata(ColumnarIterator.Row) - Method in class org.tribuo.data.columnar.RowProcessor
Generates the example metadata from the supplied row and index.
generateMutableOutputInfo() - Method in class org.tribuo.anomaly.AnomalyInfo
 
generateMutableOutputInfo() - Method in class org.tribuo.classification.LabelInfo
 
generateMutableOutputInfo() - Method in class org.tribuo.clustering.ClusteringInfo
 
generateMutableOutputInfo() - Method in class org.tribuo.multilabel.MultiLabelInfo
 
generateMutableOutputInfo() - Method in interface org.tribuo.OutputInfo
Generates a mutable copy of this OutputInfo.
generateMutableOutputInfo() - Method in class org.tribuo.regression.RegressionInfo
 
generateOtherInvalidExample() - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
This generates a sequence example where the first example has no features.
generateOutput(V) - Method in class org.tribuo.anomaly.AnomalyFactory
 
generateOutput(V) - Method in class org.tribuo.classification.LabelFactory
Generates the Label string by calling toString on the input.
generateOutput(V) - Method in class org.tribuo.clustering.ClusteringFactory
Generates a ClusterID by calling toString on the input, then calling Integer.parseInt.
generateOutput(V) - Method in class org.tribuo.multilabel.MultiLabelFactory
Parses the MultiLabel value either by toStringing the input and calling MultiLabel.parseString(java.lang.String) or if it's a Collection iterating over the elements calling toString on each element in turn and using MultiLabel.parseElement(java.lang.String).
generateOutput(V) - Method in interface org.tribuo.OutputFactory
Parses the V and generates the appropriate Output value.
generateOutput(V) - Method in class org.tribuo.regression.RegressionFactory
Parses the Regressor value either by toStringing the input and calling Regressor.parseString(java.lang.String) or if it's a collection iterating over the elements calling toString on each element in turn and using Regressor.parseElement(int, java.lang.String).
generateOutputs(List<V>) - Method in interface org.tribuo.OutputFactory
Generate a list of outputs from the supplied list of inputs.
generatePlaceholderName(String) - Static method in class org.tribuo.interop.tensorflow.TensorFlowUtil
Creates a name for a placeholder based on the supplied variable name.
generatePRCurve(boolean[], double[]) - Static method in class org.tribuo.classification.evaluation.LabelEvaluationUtil
Calculates the Precision Recall curve for a single label.
generateRealInfo() - Method in class org.tribuo.CategoricalIDInfo
Generates a RealIDInfo that matches this CategoricalInfo and also contains an id number.
generateRealInfo() - Method in class org.tribuo.CategoricalInfo
Generates a RealInfo using the currently observed counts to calculate the min, max, mean and variance.
generateROCCurve(boolean[], double[]) - Static method in class org.tribuo.classification.evaluation.LabelEvaluationUtil
Calculates the binary ROC for a single label.
generatesProbabilities - Variable in class org.tribuo.interop.onnx.LabelTransformer
 
generatesProbabilities - Variable in class org.tribuo.Model
Does this model generate probability distributions in the output.
generatesProbabilities() - Method in class org.tribuo.classification.xgboost.XGBoostClassificationConverter
 
generatesProbabilities() - Method in interface org.tribuo.common.xgboost.XGBoostOutputConverter
Does this converter produce probabilities?
generatesProbabilities() - Method in class org.tribuo.interop.oci.OCILabelConverter
 
generatesProbabilities() - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
 
generatesProbabilities() - Method in interface org.tribuo.interop.oci.OCIOutputConverter
Does this OCIOutputConverter generate probabilities?
generatesProbabilities() - Method in class org.tribuo.interop.oci.OCIRegressorConverter
 
generatesProbabilities() - Method in class org.tribuo.interop.onnx.LabelTransformer
 
generatesProbabilities() - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
 
generatesProbabilities() - Method in interface org.tribuo.interop.onnx.OutputTransformer
Does this OutputTransformer generate probabilities.
generatesProbabilities() - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
generatesProbabilities() - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
generatesProbabilities() - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
generatesProbabilities() - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Does this OutputConverter generate probabilities.
generatesProbabilities() - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
generatesProbabilities() - Method in class org.tribuo.Model
Does this model generate probabilistic predictions.
generatesProbabilities() - Method in class org.tribuo.regression.xgboost.XGBoostRegressionConverter
 
generatesProbabilities(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Does the model generate probabilities.
generatesProbabilities(CommandInterpreter) - Method in class org.tribuo.ModelExplorer
Checks if the model generates probabilities.
generateTestData() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator
Simple test data for checking multi-label trainers.
generateTrainData() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator
Simple training data for checking multi-label trainers.
generateTransformer() - Method in class org.tribuo.transform.transformations.SimpleTransform
Returns itself.
generateTransformer() - Method in interface org.tribuo.transform.TransformStatistics
Generates the appropriate Transformer from the collected statistics.
generateUniform(int, int) - Static method in class org.tribuo.util.infotheory.example.InformationTheoryDemo
Generates a sample from a uniform distribution over the integers.
generateUniformFloatVector(int, float) - Static method in class org.tribuo.util.Util
Generates a float vector of the specified length filled with the specified value.
generateUniformVector(int, double) - Static method in class org.tribuo.util.Util
Generates an array of the specified length filled with the specified value.
generateUniformVector(int, float) - Static method in class org.tribuo.util.Util
Generates an array of the specified length filled with the specified value.
generateWeightedIndicesSample(int, double[], Random) - Static method in class org.tribuo.util.Util
Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSample(int, double[], SplittableRandom) - Static method in class org.tribuo.util.Util
Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSample(int, float[], Random) - Static method in class org.tribuo.util.Util
Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSample(int, float[], SplittableRandom) - Static method in class org.tribuo.util.Util
Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSampleWithoutReplacement(int, double[], Random) - Static method in class org.tribuo.util.Util
Generates a sample of indices weighted by the provided weights without replacement.
generateWeightedIndicesSampleWithoutReplacement(int, float[], Random) - Static method in class org.tribuo.util.Util
Generates a sample of indices weighted by the provided weights without replacement.
generateWeightsString() - Method in class org.tribuo.classification.sgd.crf.CRFModel
Generates a human readable string containing all the weights in this model.
generateXOR(int) - Static method in class org.tribuo.util.infotheory.example.InformationTheoryDemo
Generates a sample from a three variable XOR function.
get() - Method in class org.tribuo.classification.sgd.crf.CRFParameters
 
get() - Method in class org.tribuo.common.sgd.FMParameters
 
get() - Method in class org.tribuo.math.LinearParameters
 
get() - Method in interface org.tribuo.math.Parameters
Get a reference to the underlying Tensor array.
get(int) - Method in class org.tribuo.ImmutableFeatureMap
Gets the VariableIDInfo for this id number.
get(int) - Method in class org.tribuo.math.la.DenseVector
 
get(int) - Method in interface org.tribuo.math.la.SGDVector
Gets an element from this vector.
get(int) - Method in class org.tribuo.math.la.SparseVector
 
get(int) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
get(int) - Method in class org.tribuo.sequence.SequenceExample
Gets the example found at the specified index.
get(int) - Method in class org.tribuo.util.infotheory.impl.RowList
 
get(int, int) - Method in class org.tribuo.math.la.DenseMatrix
 
get(int, int) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
get(int, int) - Method in interface org.tribuo.math.la.Matrix
Gets an element from this Matrix.
get(int, int) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
get(String) - Method in class org.tribuo.FeatureMap
Gets the variable info associated with that feature name, or null if it's unknown.
get(String) - Method in class org.tribuo.hash.HashedFeatureMap
 
get(String) - Method in class org.tribuo.ImmutableFeatureMap
Gets the VariableIDInfo for this name.
get(String) - Method in class org.tribuo.transform.TransformerMap
Gets the transformer associated with a given feature name.
get(MetricID<MultiLabel>) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
get(MetricID<T>) - Method in interface org.tribuo.evaluation.Evaluation
Gets the value associated with the specific metric.
get(MetricID<T>) - Method in interface org.tribuo.sequence.SequenceEvaluation
Gets the value associated with the specific metric.
getA() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
Gets the first element.
getAB() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
Gets the pair of the first and second elements.
getABCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
The joint distribution over the first and second variables.
getABCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The joint distribution over the first and second variables.
getAC() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
Gets the pair of the first and third elements.
getACCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
The joint distribution over the first and third variables.
getACCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The joint distribution over the first and third variables.
getACount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
The marginal distribution over the first variable.
getACount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The marginal distribution over the first variable.
getActiveFeatures() - Method in interface org.tribuo.classification.explanations.Explanation
Returns the names of the active features in this explanation.
getActiveFeatures() - Method in class org.tribuo.classification.explanations.lime.LIMEExplanation
 
getActiveFeatures() - Method in class org.tribuo.SparseModel
Return an immutable view on the active features for each dimension.
getAlgorithm() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
getAlgorithm() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field represents a training algorithm step.
getAlgorithm() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field represents a training algorithm step.
getAlgorithmBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
getAlgorithmOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
getAlgorithmOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field represents a training algorithm step.
getAlgorithmOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field represents a training algorithm step.
getAnomalyCount() - Method in class org.tribuo.anomaly.AnomalyInfo
The number of anomalous events observed.
getArch() - Method in class org.tribuo.provenance.ModelProvenance
The CPU architecture used to create this model.
getAttribute(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
getAttribute(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto
Additional named attributes.
getAttribute(int) - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
Additional named attributes.
getAttributeBuilder(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
getAttributeBuilderList() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
getAttributeCount() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
getAttributeCount() - Method in class ai.onnx.proto.OnnxMl.NodeProto
Additional named attributes.
getAttributeCount() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
Additional named attributes.
getAttributeList() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
getAttributeList() - Method in class ai.onnx.proto.OnnxMl.NodeProto
Additional named attributes.
getAttributeList() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
Additional named attributes.
getAttributeOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
getAttributeOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto
Additional named attributes.
getAttributeOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
Additional named attributes.
getAttributeOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
getAttributeOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.NodeProto
Additional named attributes.
getAttributeOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
Additional named attributes.
getAverageTarget() - Method in class org.tribuo.evaluation.metrics.MetricTarget
Returns the average this metric computes, or Optional.empty() if it targets an output.
getB() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
Gets the second element.
getBaseName() - Method in class org.tribuo.util.onnx.ONNXRef
The name of this object.
getBatchPredictions(List<OnnxValue>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.onnx.LabelOneVOneTransformer
Rationalises the output of an onnx model into a standard format suitable for downstream work in Tribuo.
getBatchPredictions(List<OnnxValue>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.onnx.LabelTransformer
Rationalises the output of an onnx model into a standard format suitable for downstream work in Tribuo.
getBatchSize() - Method in class org.tribuo.interop.ExternalModel
Gets the current testing batch size.
getBatchSize() - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Gets the current testing batch size.
getBC() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
Gets the pair of the second and third elements.
getBCCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
The joint distribution over the second and third variables.
getBCCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The joint distribution over the second and third variables.
getBCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
The marginal distribution over the second variable.
getBCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The marginal distribution over the second variable.
getBegin() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 begin = 1;
getBegin() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
optional int64 begin = 1;
getBegin() - Method in interface ai.onnx.proto.OnnxMl.TensorProto.SegmentOrBuilder
optional int64 begin = 1;
getBias(int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Returns the bias for the specified label id.
getBiasesCopy() - Method in class org.tribuo.common.sgd.AbstractFMModel
Returns a copy of the output dimension biases.
getC() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
Gets the third element.
getCCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
The marginal distribution over the third variable.
getCCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The marginal distribution over the third variable.
getCentroids() - Method in class org.tribuo.clustering.kmeans.KMeansModel
Returns a list of features, one per centroid.
getCentroidVectors() - Method in class org.tribuo.clustering.kmeans.KMeansModel
Returns a copy of the centroids.
getCheckpointDirectory() - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Gets the checkpoint directory this model loads from.
getCheckpointName() - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Gets the checkpoint name this model loads from.
getClassName() - Method in class org.tribuo.anomaly.AnomalyFactory.AnomalyFactoryProvenance
 
getClassName() - Method in class org.tribuo.classification.LabelFactory.LabelFactoryProvenance
 
getClassName() - Method in class org.tribuo.clustering.ClusteringFactory.ClusteringFactoryProvenance
 
getClassName() - Method in class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
Deprecated.
 
getClassName() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
 
getClassName() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
 
getClassName() - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
 
getClassName() - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
 
getClassName() - Method in class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
 
getClassName() - Method in class org.tribuo.interop.ExternalTrainerProvenance
 
getClassName() - Method in class org.tribuo.multilabel.MultiLabelFactory.MultiLabelFactoryProvenance
 
getClassName() - Method in class org.tribuo.provenance.DatasetProvenance
 
getClassName() - Method in class org.tribuo.provenance.EvaluationProvenance
 
getClassName() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
 
getClassName() - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
 
getClassName() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
 
getClassName() - Method in class org.tribuo.provenance.ModelProvenance
 
getClassName() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
 
getClassName() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
 
getClassName() - Method in class org.tribuo.regression.RegressionFactory.RegressionFactoryProvenance
 
getClassName() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
 
getClassName() - Method in class org.tribuo.transform.transformations.IDFTransformation.IDFTransformationProvenance
 
getClassName() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
 
getClassName() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
 
getClassName() - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
 
getClassName() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
 
getCliqueValues(SGDVector[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Generates the local scores and tuples them with the label - label transition weights.
getClusterLabels() - Method in class org.tribuo.clustering.hdbscan.HdbscanModel
Returns the cluster labels for the training data.
getCM() - Method in class org.tribuo.classification.evaluation.LabelMetric.Context
Gets the confusion matrix.
getColumn(int) - Method in class org.tribuo.math.la.DenseMatrix
Returns a copy of the specified column.
getColumnEntry() - Method in class org.tribuo.data.columnar.ColumnarFeature
Gets the columnEntry (i.e., the feature name produced by the FieldExtractor without the fieldName).
getColumnNames() - Method in class org.tribuo.data.columnar.RowProcessor
The set of column names this will use for the feature processing.
getConfigurationManager() - Method in class org.tribuo.reproducibility.ReproUtil
Returns the ConfigurationManager the ReproUtil is using to manage the reproduced models.
getConfiguredParameters() - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
 
getConfiguredParameters() - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
 
getConfiguredParameters() - Method in class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
 
getConfiguredParameters() - Method in class org.tribuo.interop.ExternalTrainerProvenance
 
getConfiguredParameters() - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
 
getConfiguredParameters() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
 
getConfiguredParameters() - Method in interface org.tribuo.provenance.OutputFactoryProvenance
 
getConfiguredParameters() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
 
getConfiguredParameters() - Method in class org.tribuo.regression.RegressionFactory.RegressionFactoryProvenance
 
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
 
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.IDFTransformation.IDFTransformationProvenance
 
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
 
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
 
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
 
getConfusionMatrix() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the underlying confusion matrix.
getConfusionMatrix() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the confusion matrix backing this evaluation.
getConfusionMatrix() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
getConnection() - Method in class org.tribuo.data.sql.SQLDBConfig
Constructs a connection based on the object fields.
getCount() - Method in class org.tribuo.SkeletalVariableInfo
Returns the occurrence count of this feature.
getCount() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the observation count.
getCount() - Method in interface org.tribuo.VariableInfo
The occurrence count of this feature.
getCover() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Cover measures the number of examples a given feature discriminates across, relative to the total number of examples all features discriminate across.
getCover() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The number of examples a feature discriminates between.
getCover(int) - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Cover measures the number of examples a given feature discriminates across, relative to the total.
getData() - Method in class org.tribuo.dataset.DatasetView
 
getData() - Method in class org.tribuo.Dataset
Gets the examples as an unmodifiable list.
getData() - Method in class org.tribuo.sequence.SequenceDataset
Returns an unmodifiable view on the data.
getDataLocation() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
getDataLocation() - Method in class ai.onnx.proto.OnnxMl.TensorProto
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
getDataLocation() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
getDatasetProvenance() - Method in class org.tribuo.provenance.ModelProvenance
The training dataset provenance.
getDataType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The data type of the tensor.
getDataType() - Method in class ai.onnx.proto.OnnxMl.TensorProto
The data type of the tensor.
getDataType() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
The data type of the tensor.
getDataType() - Method in class org.tribuo.datasource.IDXDataSource
The type of the features that were loaded in.
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
getDefaultInstance() - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
getDefaultInstanceForType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
getDenotation() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
getDenotation() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
getDenotation() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
getDenotation() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
getDenotation() - Method in class ai.onnx.proto.OnnxMl.TypeProto
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
getDenotation() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
getDenotationBytes() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
getDenotationBytes() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
getDenotationBytes() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
getDenotationBytes() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
getDenotationBytes() - Method in class ai.onnx.proto.OnnxMl.TypeProto
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
getDenotationBytes() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
getDensify() - Method in class org.tribuo.transform.TransformedModel
Returns true if the model densifies the feature space before applying the transformations.
getDepth() - Method in class org.tribuo.common.tree.AbstractTrainingNode
The depth of this node in the tree.
getDepth() - Method in class org.tribuo.common.tree.TreeModel
Probes the tree to find the depth.
getDepth() - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
Probes the trees to find the depth.
getDescription() - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
getDescription() - Method in class org.tribuo.data.columnar.RowProcessor
Returns a description of the row processor and it's fields.
getDescription() - Method in class org.tribuo.data.DatasetExplorer
 
getDescription() - Method in class org.tribuo.ModelExplorer
 
getDescription() - Method in class org.tribuo.sequence.SequenceModelExplorer
 
getDescriptor() - Static method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
getDescriptor() - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
 
getDescriptor() - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
getDescriptor() - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
getDescriptor() - Static method in enum class ai.onnx.proto.OnnxMl.Version
 
getDescriptorForType() - Method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
getDescriptorForType() - Method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
 
getDescriptorForType() - Method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
getDescriptorForType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
getDescriptorForType() - Method in enum class ai.onnx.proto.OnnxMl.Version
 
getDigestSupplier(String) - Static method in class org.tribuo.hash.MessageDigestHasher
Creates a supplier for the specified hash type.
getDim(int) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDim(int) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDim(int) - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProtoOrBuilder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimCount() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimCount() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimCount() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProtoOrBuilder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimension(int) - Method in class org.tribuo.regression.Regressor
Returns a dimension tuple for the requested dimension index.
getDimension(String) - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
getDimension(String) - Method in class org.tribuo.regression.Regressor
Returns a dimension tuple for the requested dimension, or optional empty if it's not valid.
getDimension1Size() - Method in class org.tribuo.math.la.DenseMatrix
 
getDimension1Size() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
getDimension1Size() - Method in interface org.tribuo.math.la.Matrix
The size of the first dimension.
getDimension2Size() - Method in class org.tribuo.math.la.DenseMatrix
 
getDimension2Size() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
getDimension2Size() - Method in interface org.tribuo.math.la.Matrix
The size of the second dimension.
getDimensionName(int) - Method in class org.tribuo.classification.sgd.fm.FMClassificationModel
 
getDimensionName(int) - Method in class org.tribuo.classification.sgd.linear.LinearSGDModel
 
getDimensionName(int) - Method in class org.tribuo.common.sgd.AbstractFMModel
Gets the name of the indexed output dimension.
getDimensionName(int) - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
Gets the name of the indexed output dimension.
getDimensionName(int) - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelModel
 
getDimensionName(int) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDModel
 
getDimensionName(int) - Method in class org.tribuo.regression.sgd.fm.FMRegressionModel
 
getDimensionName(int) - Method in class org.tribuo.regression.sgd.linear.LinearSGDModel
 
getDimensionNamesString() - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
getDimensionNamesString() - Method in class org.tribuo.regression.Regressor
Returns a comma separated list of the dimension names.
getDimensionNamesString(char) - Method in class org.tribuo.regression.Regressor
Returns a delimiter separated list of the dimension names.
getDimList() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimList() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimList() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProtoOrBuilder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProtoOrBuilder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProtoOrBuilder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
getDimParam() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
namespace Shape
getDimParam() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
namespace Shape
getDimParam() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
namespace Shape
getDimParamBytes() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
namespace Shape
getDimParamBytes() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
namespace Shape
getDimParamBytes() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
namespace Shape
getDims(int) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDims(int) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDims(int) - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDims(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The shape of the tensor.
getDims(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
The shape of the tensor.
getDims(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
The shape of the tensor.
getDimsCount() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDimsCount() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDimsCount() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDimsCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The shape of the tensor.
getDimsCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
The shape of the tensor.
getDimsCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
The shape of the tensor.
getDimsList() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDimsList() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDimsList() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
getDimsList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The shape of the tensor.
getDimsList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
The shape of the tensor.
getDimsList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
The shape of the tensor.
getDimValue() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
int64 dim_value = 1;
getDimValue() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
int64 dim_value = 1;
getDimValue() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
int64 dim_value = 1;
getDistribution() - Method in class org.tribuo.common.tree.LeafNode
Gets the distribution over scores in this node.
getDocString() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
A human-readable documentation for this attribute.
getDocString() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
A human-readable documentation for this attribute.
getDocString() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
A human-readable documentation for this attribute.
getDocString() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A human-readable documentation for this graph.
getDocString() - Method in class ai.onnx.proto.OnnxMl.GraphProto
A human-readable documentation for this graph.
getDocString() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A human-readable documentation for this graph.
getDocString() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
A human-readable documentation for this model.
getDocString() - Method in class ai.onnx.proto.OnnxMl.ModelProto
A human-readable documentation for this model.
getDocString() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
A human-readable documentation for this model.
getDocString() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
A human-readable documentation for this node.
getDocString() - Method in class ai.onnx.proto.OnnxMl.NodeProto
A human-readable documentation for this node.
getDocString() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
A human-readable documentation for this node.
getDocString() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
A human-readable documentation for this tensor.
getDocString() - Method in class ai.onnx.proto.OnnxMl.TensorProto
A human-readable documentation for this tensor.
getDocString() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
A human-readable documentation for this tensor.
getDocString() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
A human-readable documentation for this value.
getDocString() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
A human-readable documentation for this value.
getDocString() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
A human-readable documentation for this value.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
A human-readable documentation for this attribute.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
A human-readable documentation for this attribute.
getDocStringBytes() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
A human-readable documentation for this attribute.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A human-readable documentation for this graph.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.GraphProto
A human-readable documentation for this graph.
getDocStringBytes() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A human-readable documentation for this graph.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
A human-readable documentation for this model.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto
A human-readable documentation for this model.
getDocStringBytes() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
A human-readable documentation for this model.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
A human-readable documentation for this node.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto
A human-readable documentation for this node.
getDocStringBytes() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
A human-readable documentation for this node.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
A human-readable documentation for this tensor.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.TensorProto
A human-readable documentation for this tensor.
getDocStringBytes() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
A human-readable documentation for this tensor.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
A human-readable documentation for this value.
getDocStringBytes() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
A human-readable documentation for this value.
getDocStringBytes() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
A human-readable documentation for this value.
getDomain() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Domain name of the model.
getDomain() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Domain name of the model.
getDomain() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Domain name of the model.
getDomain() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The domain of the OperatorSet that specifies the operator named by op_type.
getDomain() - Method in class ai.onnx.proto.OnnxMl.NodeProto
The domain of the OperatorSet that specifies the operator named by op_type.
getDomain() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
The domain of the OperatorSet that specifies the operator named by op_type.
getDomain() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The domain of the operator set being identified.
getDomain() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
The domain of the operator set being identified.
getDomain() - Method in interface ai.onnx.proto.OnnxMl.OperatorSetIdProtoOrBuilder
The domain of the operator set being identified.
getDomain() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
When missing, the domain is the same as the model's.
getDomain() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
When missing, the domain is the same as the model's.
getDomain() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.OpaqueOrBuilder
When missing, the domain is the same as the model's.
getDomain() - Method in class org.tribuo.anomaly.AnomalyInfo
Returns the set of possible Events.
getDomain() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
Returns the classification domain that this confusion matrix operates over.
getDomain() - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
getDomain() - Method in class org.tribuo.classification.ImmutableLabelInfo
Returns the set of possible Labels that this LabelInfo has seen.
getDomain() - Method in class org.tribuo.classification.LabelInfo
Returns the set of possible Labels that this LabelInfo has seen.
getDomain() - Method in class org.tribuo.clustering.ClusteringInfo
 
getDomain() - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
getDomain() - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
getDomain() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
getDomain() - Method in class org.tribuo.multilabel.MultiLabelInfo
Returns a set of MultiLabel, where each has a single Label inside it.
getDomain() - Method in interface org.tribuo.OutputInfo
Returns a set of Output which represent the space of possible values the Output has taken.
getDomain() - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
getDomain() - Method in class org.tribuo.regression.RegressionInfo
Returns a set containing a Regressor for each dimension with the minimum value observed.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Domain name of the model.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Domain name of the model.
getDomainBytes() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Domain name of the model.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The domain of the OperatorSet that specifies the operator named by op_type.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto
The domain of the OperatorSet that specifies the operator named by op_type.
getDomainBytes() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
The domain of the OperatorSet that specifies the operator named by op_type.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The domain of the operator set being identified.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
The domain of the operator set being identified.
getDomainBytes() - Method in interface ai.onnx.proto.OnnxMl.OperatorSetIdProtoOrBuilder
The domain of the operator set being identified.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
When missing, the domain is the same as the model's.
getDomainBytes() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
When missing, the domain is the same as the model's.
getDomainBytes() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.OpaqueOrBuilder
When missing, the domain is the same as the model's.
getDoubleData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleData(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleDataCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDoubleDataList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getDropInvalidExamples() - Method in class org.tribuo.ImmutableDataset
Returns true if this immutable dataset dropped any invalid examples on construction.
getElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
getElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
The type and optional shape of each element of the sequence.
getElemType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SequenceOrBuilder
The type and optional shape of each element of the sequence.
getElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getElemType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SparseTensorOrBuilder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getElemType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.TensorOrBuilder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getElemTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
getElemTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
getElemTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
The type and optional shape of each element of the sequence.
getElemTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SequenceOrBuilder
The type and optional shape of each element of the sequence.
getEmptyCopy() - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Returns a 3 element Tensor array.
getEmptyCopy() - Method in class org.tribuo.common.sgd.FMParameters
This returns a DenseMatrix the same size as the Parameters.
getEmptyCopy() - Method in class org.tribuo.math.LinearParameters
This returns a DenseMatrix the same size as the Parameters.
getEmptyCopy() - Method in interface org.tribuo.math.Parameters
Generates an empty copy of the underlying Tensor array.
getEnd() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 end = 2;
getEnd() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
optional int64 end = 2;
getEnd() - Method in interface ai.onnx.proto.OnnxMl.TensorProto.SegmentOrBuilder
optional int64 end = 2;
getEnd() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
getEnd() - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
getEnd() - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
getEnd() - Method in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
getEnd() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
getEnd() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
getEnd() - Method in interface org.tribuo.util.tokens.Tokenizer
Gets the ending offset (exclusive) of the current token in the character sequence
getEnd() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
getEvaluation() - Method in class org.tribuo.classification.explanations.lime.LIMEExplanation
Gets the evaluator which scores how close the sparse model's predictions are to the complex model's predictions.
getEvaluator() - Method in class org.tribuo.anomaly.AnomalyFactory
 
getEvaluator() - Method in class org.tribuo.classification.LabelFactory
 
getEvaluator() - Method in class org.tribuo.clustering.ClusteringFactory
 
getEvaluator() - Method in class org.tribuo.multilabel.MultiLabelFactory
 
getEvaluator() - Method in interface org.tribuo.OutputFactory
Gets an Evaluator suitable for measuring performance of predictions for the Output subclass.
getEvaluator() - Method in class org.tribuo.regression.RegressionFactory
 
getEventCount(Event.EventType) - Method in class org.tribuo.anomaly.AnomalyInfo
Gets the count of the supplied EventType.
getExample() - Method in class org.tribuo.Excuse
The example being excused.
getExample() - Method in class org.tribuo.Prediction
Returns the example itself.
getExample(int) - Method in class org.tribuo.dataset.DatasetView
 
getExample(int) - Method in class org.tribuo.Dataset
Gets the example at the supplied index.
getExample(int) - Method in class org.tribuo.sequence.SequenceDataset
Gets the example at the specified index, or throws IllegalArgumentException if the index is out of bounds.
getExampleIndices() - Method in class org.tribuo.dataset.DatasetView
Returns a copy of the indicies used in this view.
getExampleSize() - Method in class org.tribuo.Prediction
Returns the number of features in the example.
getExcuse(Example<Label>) - Method in class org.tribuo.classification.baseline.DummyClassifierModel
 
getExcuse(Example<Label>) - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesModel
 
getExcuse(Example<Label>) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMModel
 
getExcuse(Example<ClusterID>) - Method in class org.tribuo.clustering.hdbscan.HdbscanModel
 
getExcuse(Example<ClusterID>) - Method in class org.tribuo.clustering.kmeans.KMeansModel
 
getExcuse(Example<MultiLabel>) - Method in class org.tribuo.multilabel.baseline.ClassifierChainModel
 
getExcuse(Example<MultiLabel>) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelModel
 
getExcuse(Example<Regressor>) - Method in class org.tribuo.regression.baseline.DummyRegressionModel
 
getExcuse(Example<Regressor>) - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
 
getExcuse(Example<Regressor>) - Method in class org.tribuo.regression.slm.SparseLinearModel
 
getExcuse(Example<T>) - Method in class org.tribuo.common.liblinear.LibLinearModel
This call is expensive as it copies out the weight matrix from the LibLinear model.
getExcuse(Example<T>) - Method in class org.tribuo.common.libsvm.LibSVMModel
 
getExcuse(Example<T>) - Method in class org.tribuo.common.nearest.KNNModel
 
getExcuse(Example<T>) - Method in class org.tribuo.common.sgd.AbstractFMModel
Factorization machines don't provide excuses, use an explainer.
getExcuse(Example<T>) - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
 
getExcuse(Example<T>) - Method in class org.tribuo.common.tree.TreeModel
 
getExcuse(Example<T>) - Method in class org.tribuo.common.xgboost.XGBoostModel
 
getExcuse(Example<T>) - Method in class org.tribuo.ensemble.EnsembleModel
 
getExcuse(Example<T>) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
 
getExcuse(Example<T>) - Method in class org.tribuo.interop.ExternalModel
By default third party models don't return excuses.
getExcuse(Example<T>) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Deep learning models don't do excuses.
getExcuse(Example<T>) - Method in class org.tribuo.Model
Generates an excuse for an example.
getExcuse(Example<T>) - Method in class org.tribuo.transform.TransformedModel
 
getExcuses(Iterable<Example<T>>) - Method in class org.tribuo.common.liblinear.LibLinearModel
 
getExcuses(Iterable<Example<T>>) - Method in class org.tribuo.Model
Generates an excuse for each example.
getExpectedCount() - Method in class org.tribuo.anomaly.AnomalyInfo
The number of expected events observed.
getExternalData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalData(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getExternalDataOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
getF() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
Exactly ONE of the following fields must be present for this version of the IR
getF() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
Exactly ONE of the following fields must be present for this version of the IR
getF() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
Exactly ONE of the following fields must be present for this version of the IR
getF1() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns the F_1 score of the anomalous events, i.e., the harmonic mean of the precision and the recall.
getFactorsCopy() - Method in class org.tribuo.common.sgd.AbstractFMModel
Returns a copy of the factors.
getFalseNegatives() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns the number of false negatives, i.e., anomalous events classified as expected.
getFalsePositives() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns the number of false positives, i.e., expected events classified as anomalous.
getFeature() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Gets the inverted feature values for this feature.
getFeatureID() - Method in class org.tribuo.common.tree.SplitNode
Gets the feature ID that this node uses for splitting.
getFeatureIDMap() - Method in class org.tribuo.Dataset
Returns or generates an ImmutableFeatureMap.
getFeatureIDMap() - Method in class org.tribuo.ImmutableDataset
 
getFeatureIDMap() - Method in class org.tribuo.Model
Gets the feature domain.
getFeatureIDMap() - Method in class org.tribuo.MutableDataset
 
getFeatureIDMap() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
 
getFeatureIDMap() - Method in class org.tribuo.sequence.MutableSequenceDataset
 
getFeatureIDMap() - Method in class org.tribuo.sequence.SequenceDataset
An immutable view on the feature map.
getFeatureIDMap() - Method in class org.tribuo.sequence.SequenceModel
Gets the feature domain.
getFeatureImportance() - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
Creates objects to report feature importance metrics for XGBoost.
getFeatureImportance() - Method in class org.tribuo.common.xgboost.XGBoostModel
Creates objects to report feature importance metrics for XGBoost.
getFeatureMap() - Method in class org.tribuo.dataset.DatasetView
 
getFeatureMap() - Method in class org.tribuo.Dataset
Returns this dataset's FeatureMap.
getFeatureMap() - Method in class org.tribuo.ImmutableDataset
 
getFeatureMap() - Method in class org.tribuo.MutableDataset
 
getFeatureMap() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
 
getFeatureMap() - Method in class org.tribuo.sequence.MutableSequenceDataset
 
getFeatureMap() - Method in class org.tribuo.sequence.SequenceDataset
The feature map.
getFeatureName() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The feature name.
getFeatureProcessors() - Method in class org.tribuo.data.columnar.RowProcessor
Returns the set of FeatureProcessors this RowProcessor uses.
getFeatures() - Method in class org.tribuo.common.tree.TreeModel
Returns the set of features which are split on in this tree.
getFeatures() - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
 
getFeatureTransformations() - Method in class org.tribuo.transform.TransformationMap
Gets the map of feature specific transformations.
getFeatureType() - Method in interface org.tribuo.data.columnar.FieldProcessor
Returns the feature type this FieldProcessor generates.
getFeatureType() - Method in class org.tribuo.data.columnar.processors.field.DateFieldProcessor
 
getFeatureType() - Method in class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
 
getFeatureType() - Method in class org.tribuo.data.columnar.processors.field.IdentityProcessor
 
getFeatureType() - Method in class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
 
getFeatureType() - Method in class org.tribuo.data.columnar.processors.field.TextFieldProcessor
 
getFeatureWeights() - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyModel
 
getFeatureWeights() - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel
 
getFeatureWeights() - Method in class org.tribuo.common.liblinear.LibLinearModel
Extracts the feature weights from the models.
getFeatureWeights() - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
 
getFeatureWeights(int) - Method in class org.tribuo.classification.sgd.crf.CRFModel
Get a copy of the weights for feature featureID.
getFeatureWeights(int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Gets a copy of the weights for the specified label id.
getFeatureWeights(String) - Method in class org.tribuo.classification.sgd.crf.CRFModel
Get a copy of the weights for feature named featureName.
getFieldName() - Method in class org.tribuo.data.columnar.ColumnarFeature
Gets the field name.
getFieldName() - Method in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
Gets the field name this extractor operates on.
getFieldName() - Method in interface org.tribuo.data.columnar.FieldProcessor
Gets the field name this FieldProcessor uses.
getFieldName() - Method in class org.tribuo.data.columnar.processors.field.DateFieldProcessor
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.field.IdentityProcessor
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.field.TextFieldProcessor
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Deprecated.
getFieldName() - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
Deprecated.
getFieldName() - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Deprecated.
getFieldName() - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
Deprecated.
getFieldName() - Method in interface org.tribuo.data.columnar.ResponseProcessor
Deprecated.
use ResponseProcessor.getFieldNames() and support multiple values instead. Gets the field name this ResponseProcessor uses.
getFieldNames() - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
 
getFieldNames() - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
 
getFieldNames() - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
getFieldNames() - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
getFieldNames() - Method in interface org.tribuo.data.columnar.ResponseProcessor
Gets the field names this ResponseProcessor uses.
getFieldProcessors() - Method in class org.tribuo.data.columnar.RowProcessor
Returns the map of FieldProcessors this RowProcessor uses.
getFields() - Method in class org.tribuo.data.columnar.ColumnarIterator
The immutable list of field names.
getFields() - Method in class org.tribuo.data.columnar.ColumnarIterator.Row
Gets the field headers.
getFirstCount() - Method in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
Gets the first marginal distribution.
getFirstFieldName() - Method in class org.tribuo.data.columnar.ColumnarFeature
If it's a conjunction feature, return the first field name.
getFlatDataset() - Method in class org.tribuo.sequence.SequenceDataset
Returns a view on this SequenceDataset which aggregates all the examples and ignores the sequence structure.
getFloatData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatData(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatDataCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloatDataList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
getFloats(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of floats
getFloats(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of floats
getFloats(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of floats
getFloatsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of floats
getFloatsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of floats
getFloatsCount() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of floats
getFloatsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of floats
getFloatsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of floats
getFloatsList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of floats
getFractionFeaturesInSplit() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
getFractionFeaturesInSplit() - Method in interface org.tribuo.common.tree.DecisionTreeTrainer
Returns the feature subsampling rate.
getG() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
getG() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
graph
getG() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
graph
getGain() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Gain measures the improvement in accuracy that a feature brings to the branches on which it appears.
getGain() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The information gain a feature provides when split on.
getGain(int) - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Gain measures the improvement in accuracy that a feature brings to the branches on which it appears.
getGamma() - Method in class org.tribuo.common.libsvm.SVMParameters
Gets the gamma value.
getGBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
getGlobalTransformations() - Method in class org.tribuo.transform.TransformationMap
Gets the global transformations in this TransformationMap.
getGOrBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
getGOrBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
graph
getGOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
graph
getGradientParams() - Method in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Zips the gradient parameter names and values.
getGraph() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
getGraph() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The parameterized graph that is evaluated to execute the model.
getGraph() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The parameterized graph that is evaluated to execute the model.
getGraphBuilder() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
getGraphOrBuilder() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
getGraphOrBuilder() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The parameterized graph that is evaluated to execute the model.
getGraphOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The parameterized graph that is evaluated to execute the model.
getGraphs(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
getGraphs(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of graph
getGraphs(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of graph
getGraphsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
getGraphsBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
getGraphsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
getGraphsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of graph
getGraphsCount() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of graph
getGraphsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
getGraphsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of graph
getGraphsList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of graph
getGraphsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
getGraphsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of graph
getGraphsOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of graph
getGraphsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
getGraphsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of graph
getGraphsOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of graph
getGreaterThan() - Method in class org.tribuo.common.tree.SplitNode
The node used if the value is greater than the splitValue.
getHashedTrainer(Trainer<T>) - Method in class org.tribuo.hash.HashingOptions
Gets the trainer wrapped in a hashing trainer.
getHasher() - Method in class org.tribuo.hash.HashingOptions
Get the specified hasher.
getHyperparameterFeed() - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
Build any necessary non-data parameter tensors.
getI() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
int
getI() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
int
getI() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
int
getID() - Method in enum class org.tribuo.anomaly.Event.EventType
Returns the id of the event.
getID() - Method in class org.tribuo.CategoricalIDInfo
 
getID() - Method in class org.tribuo.clustering.ClusterID
Gets the cluster id number.
getID() - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
The metric ID, a combination of the metric target and metric name.
getID() - Method in class org.tribuo.RealIDInfo
 
getID() - Method in interface org.tribuo.VariableIDInfo
The id number associated with this variable.
getID(String) - Method in class org.tribuo.hash.HashedFeatureMap
Gets the id number for this feature, returns -1 if it's unknown.
getID(String) - Method in class org.tribuo.ImmutableFeatureMap
Gets the id number for this feature, returns -1 if it's unknown.
getID(String) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
Gets the id for the supplied label string.
getID(Event) - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
getID(Label) - Method in class org.tribuo.classification.ImmutableLabelInfo
 
getID(ClusterID) - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
getID(MultiLabel) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
getID(Regressor) - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
getID(T) - Method in interface org.tribuo.ImmutableOutputInfo
Return the id number associated with this output, or -1 if the output is unknown.
getIDtoNaturalOrderMapping() - Method in class org.tribuo.regression.ImmutableRegressionInfo
Computes the mapping between ID numbers and regressor dimension indices.
getIdx(int) - Method in class org.tribuo.impl.IndexedArrayExample
Gets the feature at internal index i.
getImpl() - Method in enum class org.tribuo.classification.evaluation.LabelMetrics
Returns the implementing function for this metric.
getImpl() - Method in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
Gets the implementing function for this metric.
getImpl() - Method in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
Get the implementation function for this metric.
getImportances() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Gets all the feature importances for all the features.
getImportances(int) - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Gets the feature importances for the top n features sorted by gain.
getImpurity() - Method in class org.tribuo.classification.dtree.impl.ClassifierTrainingNode
 
getImpurity() - Method in class org.tribuo.common.tree.LeafNode
 
getImpurity() - Method in interface org.tribuo.common.tree.Node
The impurity score of this node.
getImpurity() - Method in class org.tribuo.common.tree.SplitNode
 
getImpurity() - Method in class org.tribuo.regression.rtree.impl.JointRegressorTrainingNode
 
getImpurity() - Method in class org.tribuo.regression.rtree.impl.RegressorTrainingNode
 
getIndex() - Method in class org.tribuo.data.columnar.ColumnarIterator.Row
Gets the row index.
getIndices() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
getIndices() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The indices of the non-default values, which may be stored in one of two formats.
getIndices() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The indices of the non-default values, which may be stored in one of two formats.
getIndicesBuilder() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
getIndicesOrBuilder() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
getIndicesOrBuilder() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The indices of the non-default values, which may be stored in one of two formats.
getIndicesOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The indices of the non-default values, which may be stored in one of two formats.
getInitialization() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
getInitialization() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field describes a graph to compute the initial tensors upon starting the training process.
getInitialization() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field describes a graph to compute the initial tensors upon starting the training process.
getInitializationBinding(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBinding(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBinding(int) - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingBuilderList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingCount() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingCount() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingCount() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingList() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBindingOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
getInitializationBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
getInitializationOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
getInitializationOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field describes a graph to compute the initial tensors upon starting the training process.
getInitializationOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field describes a graph to compute the initial tensors upon starting the training process.
getInitializer(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializer(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
A list of named tensor values, used to specify constant inputs of the graph.
getInitializer(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerCount() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
A list of named tensor values, used to specify constant inputs of the graph.
getInitializerOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A list of named tensor values, used to specify constant inputs of the graph.
getInnerExcuses() - Method in class org.tribuo.ensemble.EnsembleExcuse
The individual ensemble member's excuses.
getInnerModel() - Method in class org.tribuo.transform.TransformedModel
Gets the inner model to allow access to any class specific methods that model contains (e.g., to examine cluster centroids).
getInnerModels() - Method in class org.tribuo.common.liblinear.LibLinearModel
Returns an unmodifiable list containing a copy of each model.
getInnerModels() - Method in class org.tribuo.common.libsvm.LibSVMModel
Returns an unmodifiable copy of the underlying list of libsvm models.
getInnerModels() - Method in class org.tribuo.common.xgboost.XGBoostModel
Returns an unmodifiable list containing a copy of each model.
getInput(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
getInput(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
The inputs and outputs of the graph.
getInput(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The inputs and outputs of the graph.
getInput(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getInput(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getInput(int) - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getInputBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
getInputBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
getInputBytes(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getInputBytes(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getInputBytes(int) - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getInputCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
getInputCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The inputs and outputs of the graph.
getInputCount() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The inputs and outputs of the graph.
getInputCount() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getInputCount() - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getInputCount() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getInputList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
getInputList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The inputs and outputs of the graph.
getInputList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The inputs and outputs of the graph.
getInputList() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getInputList() - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getInputList() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getInputOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
getInputOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
The inputs and outputs of the graph.
getInputOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The inputs and outputs of the graph.
getInputOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
getInputOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The inputs and outputs of the graph.
getInputOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The inputs and outputs of the graph.
getInstanceProvenance() - Method in class org.tribuo.provenance.ModelProvenance
Provenance for the specific training run which created this model.
getInstanceValues() - Method in class org.tribuo.data.csv.CSVDataSource.CSVDataSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.data.sql.SQLDataSource.SQLDataSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.data.text.DirectoryFileSource.DirectoryFileSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.data.text.impl.SimpleStringDataSource.SimpleStringDataSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.data.text.impl.SimpleTextDataSource.SimpleTextDataSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.interop.ExternalTrainerProvenance
 
getInstanceValues() - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance
 
getInstanceValues() - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
 
getInstanceValues() - Method in class org.tribuo.json.JsonDataSource.JsonDataSourceProvenance
 
getInstanceValues() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
 
getInstanceValues() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
 
getInt32Data(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32Data(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32Data(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32DataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32DataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32DataCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32DataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32DataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt32DataList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
getInt64Data(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int64.
getInt64Data(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
For int64.
getInt64Data(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For int64.
getInt64DataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int64.
getInt64DataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For int64.
getInt64DataCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For int64.
getInt64DataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int64.
getInt64DataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For int64.
getInt64DataList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For int64.
getInts(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of ints
getInts(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of ints
getInts(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of ints
getIntsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of ints
getIntsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of ints
getIntsCount() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of ints
getIntsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of ints
getIntsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of ints
getIntsList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of ints
getInvocationCount() - Method in class org.tribuo.classification.baseline.DummyClassifierTrainer
 
getInvocationCount() - Method in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
getInvocationCount() - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
 
getInvocationCount() - Method in class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
 
getInvocationCount() - Method in class org.tribuo.classification.sgd.crf.CRFTrainer
 
getInvocationCount() - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
 
getInvocationCount() - Method in class org.tribuo.clustering.hdbscan.HdbscanTrainer
 
getInvocationCount() - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
getInvocationCount() - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
getInvocationCount() - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
getInvocationCount() - Method in class org.tribuo.common.nearest.KNNTrainer
 
getInvocationCount() - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
getInvocationCount() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
getInvocationCount() - Method in class org.tribuo.common.xgboost.XGBoostTrainer
 
getInvocationCount() - Method in class org.tribuo.ensemble.BaggingTrainer
 
getInvocationCount() - Method in class org.tribuo.hash.HashingTrainer
 
getInvocationCount() - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
getInvocationCount() - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
getInvocationCount() - Method in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
 
getInvocationCount() - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
 
getInvocationCount() - Method in class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
 
getInvocationCount() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
 
getInvocationCount() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
 
getInvocationCount() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
 
getInvocationCount() - Method in class org.tribuo.regression.slm.ElasticNetCDTrainer
 
getInvocationCount() - Method in class org.tribuo.regression.slm.SLMTrainer
 
getInvocationCount() - Method in class org.tribuo.sequence.HashingSequenceTrainer
 
getInvocationCount() - Method in class org.tribuo.sequence.IndependentSequenceTrainer
 
getInvocationCount() - Method in interface org.tribuo.sequence.SequenceTrainer
Returns the number of times the train method has been invoked.
getInvocationCount() - Method in interface org.tribuo.Trainer
The number of times this trainer instance has had it's train method invoked.
getInvocationCount() - Method in class org.tribuo.transform.TransformTrainer
 
getIrVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the IR this model targets.
getIrVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The version of the IR this model targets.
getIrVersion() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The version of the IR this model targets.
getJavaVersion() - Method in class org.tribuo.provenance.ModelProvenance
The Java version used to create this model.
getJointCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
The joint distribution over the three variables.
getJointCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
The joint distribution over the three variables.
getJointCounts() - Method in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
Gets the joint distribution.
getK() - Method in class org.tribuo.evaluation.CrossValidation
Returns the number of folds.
getKernelType() - Method in class org.tribuo.common.libsvm.SVMParameters
Gets the kernel type.
getKernelType(int) - Static method in enum class org.tribuo.common.libsvm.KernelType
Converts the LibSVM int id into the enum value.
getKey() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string key = 1;
getKey() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
optional string key = 1;
getKey() - Method in interface ai.onnx.proto.OnnxMl.StringStringEntryProtoOrBuilder
optional string key = 1;
getKeyBytes() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string key = 1;
getKeyBytes() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
optional string key = 1;
getKeyBytes() - Method in interface ai.onnx.proto.OnnxMl.StringStringEntryProtoOrBuilder
optional string key = 1;
getKeyType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getKeyType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getKeyType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.MapOrBuilder
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
getLabel() - Method in class org.tribuo.classification.Label
Gets the name of this label.
getLabelCount(int) - Method in class org.tribuo.classification.ImmutableLabelInfo
Returns the number of times the supplied id was observed before this LabelInfo was frozen.
getLabelCount(int) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
Gets the count of the label occurrence for the specified id number, or 0 if it's unknown.
getLabelCount(String) - Method in class org.tribuo.classification.LabelInfo
Gets the count of the supplied label, or 0 if the label is unknown.
getLabelCount(String) - Method in class org.tribuo.multilabel.MultiLabelInfo
Get the number of times this String was observed, or 0 if unknown.
getLabelCount(Label) - Method in class org.tribuo.classification.LabelInfo
Gets the count of the supplied label, or 0 if the label is unknown.
getLabelCount(Label) - Method in class org.tribuo.multilabel.MultiLabelInfo
Get the number of times this Label was observed, or 0 if unknown.
getLabelOrder() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The label order this confusion matrix uses in toString.
getLabelOrder() - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
Gets the current label order.
getLabelOrder() - Method in class org.tribuo.multilabel.baseline.ClassifierChainModel
Returns the training label order.
getLabelOrder() - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
Gets the current label order.
getLabelScore(Label) - Method in class org.tribuo.multilabel.MultiLabel
The score for the specified label if present, returns an empty optional otherwise.
getLabelSet() - Method in class org.tribuo.multilabel.MultiLabel
The set of labels contained in this multilabel.
getLabelString() - Method in class org.tribuo.multilabel.MultiLabel
Returns a comma separated string representing the labels in this multilabel instance.
getLanguageTag() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
Returns the locale string this tokenizer uses.
getLessThanOrEqual() - Method in class org.tribuo.common.tree.SplitNode
The node used if the value is less than or equal to the splitValue.
getLinearDecaySGD(double) - Static method in class org.tribuo.math.optimisers.SGD
Generates an SGD optimiser with a linearly decaying learning rate initialised to learningRate.
getLinearDecaySGD(double, double, SGD.Momentum) - Static method in class org.tribuo.math.optimisers.SGD
Generates an SGD optimiser with a linearly decaying learning rate initialised to learningRate, with momentum.
getLinearWeightsCopy() - Method in class org.tribuo.common.sgd.AbstractFMModel
Returns a copy of the linear weights.
getLocalScores(SGDVector[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Generate the local scores (i.e., the linear classifier for each token).
getLongLittleEndian(byte[], int) - Static method in class org.tribuo.util.MurmurHash3
Gets a long from a byte buffer in little endian byte order.
getLoss() - Method in class org.tribuo.classification.sgd.fm.FMClassificationOptions
Returns the loss function specified in the arguments.
getLoss() - Method in class org.tribuo.classification.sgd.linear.LinearSGDOptions
Returns the loss function specified in the arguments.
getLoss() - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Returns the loss function specified in the arguments.
getLoss() - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
Returns the loss function specified in the arguments.
getLossOp - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
getLowerMedian() - Method in class org.tribuo.data.columnar.processors.response.Quartile
Returns the lower quartile value.
getMap() - Method in class org.tribuo.interop.tensorflow.TensorMap
Returns the underlying immutable map.
getMapType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
getMapType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a map.
getMapType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a map.
getMapTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
getMapTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
getMapTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a map.
getMapTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a map.
getMax() - Method in class org.tribuo.evaluation.DescriptiveStats
Calculates the max of the values.
getMax() - Method in class org.tribuo.RealInfo
Gets the maximum observed value.
getMax() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the maximum observed value.
getMax(int) - Method in class org.tribuo.regression.ImmutableRegressionInfo
Gets the maximum value this RegressionInfo has seen for that id.
getMax(String) - Method in class org.tribuo.regression.RegressionInfo
Gets the maximum value this RegressionInfo has seen, or NaN if it's not seen that dimension.
getMaxDepth() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
Gets the maximum tree depth.
getMaxFeatureID() - Method in class org.tribuo.datasource.LibSVMDataSource
Gets the maximum feature ID found.
getMaxInputCharactersPerWord() - Method in class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
a getter for the maximum character count for a token to consider when Wordpiece.wordpiece(String) is applied to a token.
getMaxLength() - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Returns the maximum length this BERT will accept.
getMaxTokenLength() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Returns the maximum token length this tokenizer will generate.
getMean() - Method in class org.tribuo.evaluation.DescriptiveStats
Calculates the mean of the values.
getMean() - Method in class org.tribuo.RealInfo
Gets the sample mean.
getMean() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the sample mean.
getMean(int) - Method in class org.tribuo.regression.ImmutableRegressionInfo
Gets the mean value this RegressionInfo has seen for that id.
getMean(String) - Method in class org.tribuo.regression.RegressionInfo
Gets the mean value this RegressionInfo has seen, or NaN if it's not seen that dimension.
getMeans() - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
Accessor used in the tests.
getMedian() - Method in class org.tribuo.data.columnar.processors.response.Quartile
Returns the median value.
getMemberProvenance() - Method in class org.tribuo.provenance.EnsembleModelProvenance
Get the provenances for each ensemble member.
getMetadata() - Method in class org.tribuo.Example
Returns a copy of this example's metadata.
getMetadataName() - Method in class org.tribuo.data.columnar.extractors.IndexExtractor
 
getMetadataName() - Method in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
Gets the metadata key name.
getMetadataName() - Method in interface org.tribuo.data.columnar.FieldExtractor
Gets the metadata key name.
getMetadataProps(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
getMetadataProps(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto
Named metadata values; keys should be distinct.
getMetadataProps(int) - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Named metadata values; keys should be distinct.
getMetadataPropsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
getMetadataPropsBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
getMetadataPropsCount() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
getMetadataPropsCount() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Named metadata values; keys should be distinct.
getMetadataPropsCount() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Named metadata values; keys should be distinct.
getMetadataPropsList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
getMetadataPropsList() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Named metadata values; keys should be distinct.
getMetadataPropsList() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Named metadata values; keys should be distinct.
getMetadataPropsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
getMetadataPropsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto
Named metadata values; keys should be distinct.
getMetadataPropsOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Named metadata values; keys should be distinct.
getMetadataPropsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
getMetadataPropsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Named metadata values; keys should be distinct.
getMetadataPropsOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Named metadata values; keys should be distinct.
getMetadataTypes() - Method in class org.tribuo.data.columnar.ColumnarDataSource
Returns the metadata keys and value types that are created by this DataSource.
getMetadataTypes() - Method in class org.tribuo.data.columnar.RowProcessor
Returns the metadata keys and value types that are extracted by this RowProcessor.
getMetadataValue(String) - Method in class org.tribuo.Example
Gets the associated metadata value for this key, if it exists.
getMin() - Method in class org.tribuo.evaluation.DescriptiveStats
Calculates the min of the values.
getMin() - Method in class org.tribuo.RealInfo
Gets the minimum observed value.
getMin() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the minimum observed value.
getMin(int) - Method in class org.tribuo.regression.ImmutableRegressionInfo
Gets the minimum value this RegressionInfo has seen for that id.
getMin(String) - Method in class org.tribuo.regression.RegressionInfo
Gets the minimum value this RegressionInfo has seen, or NaN if it's not seen anything.
getMinCardinality() - Method in class org.tribuo.dataset.MinimumCardinalityDataset
The minimum cardinality threshold for the features.
getMinCardinality() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset
The minimum cardinality threshold for the features.
getMinChildWeight() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
Gets the minimum example weight of a child node.
getMinImpurityDecrease() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
getMinImpurityDecrease() - Method in interface org.tribuo.common.tree.DecisionTreeTrainer
Returns the minimum decrease in impurity necessary to split a node.
getModel() - Method in interface org.tribuo.classification.explanations.Explanation
Returns the explanining model.
getModel() - Method in class org.tribuo.classification.explanations.lime.LIMEExplanation
 
getModel() - Method in class org.tribuo.common.libsvm.LibSVMModel
Deprecated.
Deprecated to unify the names across LibLinear, LibSVM and XGBoost.
getModel() - Method in class org.tribuo.evaluation.metrics.MetricContext
Gets the Model used by this context.
getModelClassName() - Method in class org.tribuo.classification.sgd.fm.FMClassificationTrainer
 
getModelClassName() - Method in class org.tribuo.classification.sgd.linear.LinearSGDTrainer
 
getModelClassName() - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Returns the class name of the model that's produced by this trainer.
getModelClassName() - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
 
getModelClassName() - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
 
getModelClassName() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
Returns the class name of the model that this class produces.
getModelClassName() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
Returns the class name of the model that this class produces.
getModelClassName() - Method in class org.tribuo.regression.sgd.fm.FMRegressionTrainer
 
getModelClassName() - Method in class org.tribuo.regression.sgd.linear.LinearSGDTrainer
 
getModelDump() - Method in class org.tribuo.common.xgboost.XGBoostModel
Returns the string model dumps from each Booster.
getModelParameters() - Method in class org.tribuo.common.sgd.AbstractSGDModel
Returns a copy of the model parameters.
getModelProvenance() - Method in class org.tribuo.provenance.EvaluationProvenance
The model provenance.
getModels() - Method in class org.tribuo.ensemble.EnsembleModel
Returns an unmodifiable view on the ensemble members.
getModelVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the graph encoded.
getModelVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The version of the graph encoded.
getModelVersion() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The version of the graph encoded.
getN() - Method in class org.tribuo.evaluation.DescriptiveStats
Returns the number of values.
getName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The name field MUST be present for this version of the IR.
getName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
The name field MUST be present for this version of the IR.
getName() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
The name field MUST be present for this version of the IR.
getName() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The name of the graph.
getName() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The name of the graph.
getName() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The name of the graph.
getName() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
An optional identifier for this node in a graph.
getName() - Method in class ai.onnx.proto.OnnxMl.NodeProto
An optional identifier for this node in a graph.
getName() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
An optional identifier for this node in a graph.
getName() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Optionally, a name for the tensor.
getName() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Optionally, a name for the tensor.
getName() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Optionally, a name for the tensor.
getName() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
The name is optional but significant when provided.
getName() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
The name is optional but significant when provided.
getName() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.OpaqueOrBuilder
The name is optional but significant when provided.
getName() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR.
getName() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
This field MUST be present in this version of the IR.
getName() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
This field MUST be present in this version of the IR.
getName() - Method in class org.tribuo.anomaly.evaluation.AnomalyMetric
 
getName() - Method in class org.tribuo.classification.evaluation.LabelMetric
 
getName() - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
getName() - Method in class org.tribuo.clustering.evaluation.ClusteringMetric
 
getName() - Method in class org.tribuo.common.sgd.AbstractFMTrainer
Returns the default model name.
getName() - Method in class org.tribuo.common.sgd.AbstractLinearSGDTrainer
Returns the default model name.
getName() - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Returns the default model name.
getName() - Method in class org.tribuo.data.DatasetExplorer
 
getName() - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
The name of this metric.
getName() - Method in class org.tribuo.Feature
Returns the feature name.
getName() - Method in class org.tribuo.Model
Returns the model name.
getName() - Method in class org.tribuo.ModelExplorer
 
getName() - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
 
getName() - Method in class org.tribuo.regression.evaluation.RegressionMetric
 
getName() - Method in class org.tribuo.regression.Regressor.DimensionTuple
Returns the name.
getName() - Method in class org.tribuo.sequence.SequenceModel
Gets the model name.
getName() - Method in class org.tribuo.sequence.SequenceModelExplorer
 
getName() - Method in class org.tribuo.SkeletalVariableInfo
Returns the name of the feature.
getName() - Method in class org.tribuo.util.onnx.ONNXAttribute
Gets the attribute's name.
getName() - Method in interface org.tribuo.VariableInfo
The name of this feature.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The name field MUST be present for this version of the IR.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
The name field MUST be present for this version of the IR.
getNameBytes() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
The name field MUST be present for this version of the IR.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The name of the graph.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The name of the graph.
getNameBytes() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The name of the graph.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
An optional identifier for this node in a graph.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto
An optional identifier for this node in a graph.
getNameBytes() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
An optional identifier for this node in a graph.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Optionally, a name for the tensor.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Optionally, a name for the tensor.
getNameBytes() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Optionally, a name for the tensor.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
The name is optional but significant when provided.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
The name is optional but significant when provided.
getNameBytes() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.OpaqueOrBuilder
The name is optional but significant when provided.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR.
getNameBytes() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
This field MUST be present in this version of the IR.
getNameBytes() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
This field MUST be present in this version of the IR.
getNames() - Method in class org.tribuo.regression.Regressor
The names of the dimensions.
getNameSet() - Method in class org.tribuo.multilabel.MultiLabel
The set of strings that represent the labels in this multilabel.
getNativeType() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
 
getNativeType() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
 
getNativeType() - Method in enum class org.tribuo.common.libsvm.KernelType
Gets LibSVM's int id.
getNativeType() - Method in interface org.tribuo.common.libsvm.SVMType
The LibSVM int id for the algorithm.
getNativeType() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
 
getNaturalOrderToIDMapping() - Method in class org.tribuo.regression.ImmutableRegressionInfo
Computes the mapping between regressor dimension indices and ID numbers.
getNextNode(SparseVector) - Method in class org.tribuo.common.tree.AbstractTrainingNode
 
getNextNode(SparseVector) - Method in class org.tribuo.common.tree.LeafNode
 
getNextNode(SparseVector) - Method in interface org.tribuo.common.tree.Node
Returns the next node in the tree based on the supplied example, or null if it's a leaf.
getNextNode(SparseVector) - Method in class org.tribuo.common.tree.SplitNode
Return the appropriate child node.
getNode(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
getNode(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
The nodes in the graph, sorted topologically.
getNode(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The nodes in the graph, sorted topologically.
getNodeBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
getNodeBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
getNodeCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
getNodeCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The nodes in the graph, sorted topologically.
getNodeCount() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The nodes in the graph, sorted topologically.
getNodeList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
getNodeList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The nodes in the graph, sorted topologically.
getNodeList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The nodes in the graph, sorted topologically.
getNodeOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
getNodeOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
The nodes in the graph, sorted topologically.
getNodeOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The nodes in the graph, sorted topologically.
getNodeOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
getNodeOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The nodes in the graph, sorted topologically.
getNodeOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The nodes in the graph, sorted topologically.
getNormalizer() - Method in interface org.tribuo.classification.sgd.LabelObjective
Generates a new VectorNormalizer which normalizes the predictions into [0,1].
getNormalizer() - Method in class org.tribuo.classification.sgd.objectives.Hinge
Returns a new NoopNormalizer.
getNormalizer() - Method in class org.tribuo.classification.sgd.objectives.LogMulticlass
 
getNormalizer() - Method in interface org.tribuo.multilabel.sgd.MultiLabelObjective
Generates a new VectorNormalizer which normalizes the predictions into a suitable format.
getNormalizer() - Method in class org.tribuo.multilabel.sgd.objectives.BinaryCrossEntropy
 
getNormalizer() - Method in class org.tribuo.multilabel.sgd.objectives.Hinge
Returns a new NoopNormalizer.
getNumActiveFeatures() - Method in class org.tribuo.Prediction
Returns the number of features used in the prediction.
getNumber() - Method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
 
getNumber() - Method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
 
getNumber() - Method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
 
getNumber() - Method in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
 
getNumber() - Method in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
getNumber() - Method in enum class ai.onnx.proto.OnnxMl.Version
 
getNumberOfSupportVectors() - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyModel
Returns the number of support vectors.
getNumberOfSupportVectors() - Method in class org.tribuo.classification.libsvm.LibSVMClassificationModel
Returns the number of support vectors.
getNumberOfSupportVectors() - Method in class org.tribuo.classification.sgd.kernel.KernelSVMModel
Returns the number of support vectors used.
getNumberOfSupportVectors() - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
Returns the support vectors used for each dimension.
getNumExamples() - Method in class org.tribuo.common.tree.AbstractTrainingNode
The number of training examples in this node.
getNumExamples() - Method in class org.tribuo.provenance.DatasetProvenance
The number of examples.
getNumExamplesRemoved() - Method in class org.tribuo.dataset.MinimumCardinalityDataset
The number of examples removed due to a lack of features.
getNumExamplesRemoved() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset
The number of examples removed due to a lack of features.
getNumFeatures() - Method in class org.tribuo.provenance.DatasetProvenance
The number of features.
getNumModels() - Method in class org.tribuo.ensemble.EnsembleModel
The number of ensemble members.
getNumNamespaces() - Method in interface org.tribuo.data.columnar.FieldProcessor
Binarised categoricals can be namespaced, where the field name is appended with "#<non-negative-int>" to denote the namespace.
getNumOutputs() - Method in class org.tribuo.provenance.DatasetProvenance
The number of output dimensions.
getObjective() - Method in class org.tribuo.classification.sgd.fm.FMClassificationTrainer
 
getObjective() - Method in class org.tribuo.classification.sgd.linear.LinearSGDTrainer
 
getObjective() - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Returns the objective used by this trainer.
getObjective() - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
 
getObjective() - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
 
getObjective() - Method in class org.tribuo.regression.sgd.fm.FMRegressionTrainer
 
getObjective() - Method in class org.tribuo.regression.sgd.linear.LinearSGDTrainer
 
getObservationCount(double) - Method in class org.tribuo.CategoricalInfo
Gets the number of times a specific value was observed, and zero if this value is unknown.
getOpaqueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
getOpaqueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
.onnx.TypeProto.Opaque opaque_type = 7;
getOpaqueType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
.onnx.TypeProto.Opaque opaque_type = 7;
getOpaqueTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
getOpaqueTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
getOpaqueTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto
.onnx.TypeProto.Opaque opaque_type = 7;
getOpaqueTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
.onnx.TypeProto.Opaque opaque_type = 7;
getOpsetImport(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
getOpsetImport(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto
The OperatorSets this model relies on.
getOpsetImport(int) - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The OperatorSets this model relies on.
getOpsetImportBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
getOpsetImportBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
getOpsetImportCount() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
getOpsetImportCount() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The OperatorSets this model relies on.
getOpsetImportCount() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The OperatorSets this model relies on.
getOpsetImportList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
getOpsetImportList() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The OperatorSets this model relies on.
getOpsetImportList() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The OperatorSets this model relies on.
getOpsetImportOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
getOpsetImportOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto
The OperatorSets this model relies on.
getOpsetImportOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The OperatorSets this model relies on.
getOpsetImportOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
getOpsetImportOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The OperatorSets this model relies on.
getOpsetImportOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The OperatorSets this model relies on.
getOpsetProto() - Static method in enum class org.tribuo.util.onnx.ONNXOperators
Returns the opset proto for these operators.
getOpsetVersion() - Static method in enum class org.tribuo.util.onnx.ONNXOperators
Returns the opset version supported by these operators.
getOptimiser() - Method in class org.tribuo.math.optimisers.GradientOptimiserOptions
Gets the configured gradient optimiser.
getOptionsDescription() - Method in class org.tribuo.classification.dtree.CARTClassificationOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.dtree.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.experiments.RunAll.RunAllOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.experiments.TrainTest.AllClassificationOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.liblinear.LibLinearOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.libsvm.LibSVMOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.sgd.fm.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.sgd.kernel.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.classification.xgboost.TrainTest.TrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.clustering.hdbscan.HdbscanOptions
 
getOptionsDescription() - Method in class org.tribuo.clustering.hdbscan.TrainTest.HdbscanCLIOptions
 
getOptionsDescription() - Method in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
getOptionsDescription() - Method in class org.tribuo.common.nearest.KNNClassifierOptions
 
getOptionsDescription() - Method in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
getOptionsDescription() - Method in class org.tribuo.data.DataOptions
 
getOptionsDescription() - Method in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
 
getOptionsDescription() - Method in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
 
getOptionsDescription() - Method in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
getOptionsDescription() - Method in class org.tribuo.json.StripProvenance.StripProvenanceOptions
 
getOptionsDescription() - Method in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
 
getOptionsDescription() - Method in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 
getOptionsDescription() - Method in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
getOptionsDescription() - Method in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
 
getOptionsDescription() - Method in class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
getOptionsDescription() - Method in class org.tribuo.regression.slm.TrainTest.SLMOptions
 
getOptionsDescription() - Method in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
getOptionsDescription() - Method in class org.tribuo.util.infotheory.example.InformationTheoryDemo.DemoOptions
 
getOpType() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The symbolic identifier of the Operator to execute.
getOpType() - Method in class ai.onnx.proto.OnnxMl.NodeProto
The symbolic identifier of the Operator to execute.
getOpType() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
The symbolic identifier of the Operator to execute.
getOpTypeBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The symbolic identifier of the Operator to execute.
getOpTypeBytes() - Method in class ai.onnx.proto.OnnxMl.NodeProto
The symbolic identifier of the Operator to execute.
getOpTypeBytes() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
The symbolic identifier of the Operator to execute.
getOS() - Method in class org.tribuo.provenance.ModelProvenance
The name of the OS used to create this model.
getOutlierScores() - Method in class org.tribuo.clustering.hdbscan.HdbscanModel
Returns the GLOSH (Global-Local Outlier Scores from Hierarchies) outlier scores for the training data.
getOutput() - Method in class org.tribuo.common.tree.LeafNode
Gets the output in this node.
getOutput() - Method in class org.tribuo.Example
Gets the example's Output.
getOutput() - Method in class org.tribuo.Prediction
Returns the predicted output.
getOutput(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
getOutput(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
repeated .onnx.ValueInfoProto output = 12;
getOutput(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
repeated .onnx.ValueInfoProto output = 12;
getOutput(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getOutput(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getOutput(int) - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getOutput(int) - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
getOutput(int) - Method in class org.tribuo.classification.ImmutableLabelInfo
 
getOutput(int) - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
getOutput(int) - Method in interface org.tribuo.ImmutableOutputInfo
Returns the output associated with this id, or null if the id is unknown.
getOutput(int) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
getOutput(int) - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
getOutputBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
getOutputBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
getOutputBytes(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getOutputBytes(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getOutputBytes(int) - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getOutputCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
getOutputCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto
repeated .onnx.ValueInfoProto output = 12;
getOutputCount() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
repeated .onnx.ValueInfoProto output = 12;
getOutputCount() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getOutputCount() - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getOutputCount() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getOutputFactory() - Method in class org.tribuo.anomaly.example.GaussianAnomalyDataSource
 
getOutputFactory() - Method in class org.tribuo.classification.example.DemoLabelDataSource
 
getOutputFactory() - Method in class org.tribuo.clustering.example.GaussianClusterDataSource
 
getOutputFactory() - Method in class org.tribuo.data.columnar.ColumnarDataSource
 
getOutputFactory() - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
 
getOutputFactory() - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
 
getOutputFactory() - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
getOutputFactory() - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
getOutputFactory() - Method in interface org.tribuo.data.columnar.ResponseProcessor
Gets the OutputFactory this ResponseProcessor uses.
getOutputFactory() - Method in class org.tribuo.data.text.DirectoryFileSource
 
getOutputFactory() - Method in class org.tribuo.data.text.TextDataSource
Returns the output factory used to convert the text input into an Output.
getOutputFactory() - Method in class org.tribuo.Dataset
Gets the output factory this dataset contains.
getOutputFactory() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
 
getOutputFactory() - Method in class org.tribuo.datasource.AggregateDataSource
 
getOutputFactory() - Method in interface org.tribuo.DataSource
Returns the OutputFactory associated with this Output subclass.
getOutputFactory() - Method in class org.tribuo.datasource.IDXDataSource
 
getOutputFactory() - Method in class org.tribuo.datasource.LibSVMDataSource
 
getOutputFactory() - Method in class org.tribuo.datasource.ListDataSource
 
getOutputFactory() - Method in class org.tribuo.multilabel.example.MultiLabelGaussianDataSource
 
getOutputFactory() - Method in class org.tribuo.regression.example.GaussianDataSource
 
getOutputFactory() - Method in class org.tribuo.regression.example.NonlinearGaussianDataSource
 
getOutputFactory() - Method in class org.tribuo.sequence.SequenceDataset
Gets the output factory.
getOutputFactory() - Method in interface org.tribuo.sequence.SequenceDataSource
Gets the OutputFactory which was used to generate the Outputs in this SequenceDataSource.
getOutputID() - Method in class org.tribuo.impl.IndexedArrayExample
Gets the output id dimension number.
getOutputIDInfo() - Method in class org.tribuo.Dataset
Returns or generates an ImmutableOutputInfo.
getOutputIDInfo() - Method in class org.tribuo.ImmutableDataset
 
getOutputIDInfo() - Method in class org.tribuo.Model
Gets the output domain.
getOutputIDInfo() - Method in class org.tribuo.MutableDataset
 
getOutputIDInfo() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
 
getOutputIDInfo() - Method in class org.tribuo.sequence.MutableSequenceDataset
 
getOutputIDInfo() - Method in class org.tribuo.sequence.SequenceDataset
An immutable view on the output info in this dataset.
getOutputIDInfo() - Method in class org.tribuo.sequence.SequenceModel
Gets the output domain.
getOutputInfo() - Method in class org.tribuo.dataset.DatasetView
 
getOutputInfo() - Method in class org.tribuo.Dataset
Returns this dataset's OutputInfo.
getOutputInfo() - Method in class org.tribuo.ImmutableDataset
 
getOutputInfo() - Method in class org.tribuo.MutableDataset
 
getOutputInfo() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
 
getOutputInfo() - Method in class org.tribuo.sequence.MutableSequenceDataset
 
getOutputInfo() - Method in class org.tribuo.sequence.SequenceDataset
The output info in this dataset.
getOutputList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
getOutputList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
repeated .onnx.ValueInfoProto output = 12;
getOutputList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
repeated .onnx.ValueInfoProto output = 12;
getOutputList() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
getOutputList() - Method in class ai.onnx.proto.OnnxMl.NodeProto
namespace Value
getOutputList() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
namespace Value
getOutputName() - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Gets the name of the output operation.
getOutputOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
getOutputOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
repeated .onnx.ValueInfoProto output = 12;
getOutputOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
repeated .onnx.ValueInfoProto output = 12;
getOutputOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
getOutputOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
repeated .onnx.ValueInfoProto output = 12;
getOutputOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
repeated .onnx.ValueInfoProto output = 12;
getOutputs() - Method in class org.tribuo.dataset.DatasetView
Gets the set of outputs that occur in the examples in this dataset.
getOutputs() - Method in class org.tribuo.Dataset
Gets the set of outputs that occur in the examples in this dataset.
getOutputs() - Method in class org.tribuo.ImmutableDataset
 
getOutputs() - Method in class org.tribuo.MutableDataset
Gets the set of possible outputs in this dataset.
getOutputs() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
 
getOutputs() - Method in class org.tribuo.sequence.MutableSequenceDataset
 
getOutputs() - Method in class org.tribuo.sequence.SequenceDataset
Gets the set of labels that occur in the examples in this dataset.
getOutputScores() - Method in class org.tribuo.Prediction
Gets the output scores for each output.
getOutputTarget() - Method in class org.tribuo.evaluation.metrics.MetricTarget
Returns the Output this metric targets, or Optional.empty() if it's an average.
getParameterNames() - Method in enum class org.tribuo.interop.tensorflow.GradientOptimiser
An unmodifiable view of the parameter names used by this gradient optimiser.
getParameters() - Method in class org.tribuo.common.libsvm.SVMParameters
Gets the underlying SVM parameter object.
getParserForType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
getParserForType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
getPos() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Gets the current position in the input.
getPrecision() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns the precision of the anomalous events, i.e., true positives divided by the number of predicted positives.
getPrediction() - Method in interface org.tribuo.classification.explanations.Explanation
The original model's prediction which is being explained.
getPrediction() - Method in class org.tribuo.classification.explanations.lime.LIMEExplanation
 
getPrediction() - Method in class org.tribuo.Excuse
Returns the prediction being excused.
getPrediction(int, Example<T>) - Method in class org.tribuo.common.tree.LeafNode
Constructs a new prediction object based on this node's scores.
getPredictions() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the flattened predictions.
getPredictions() - Method in interface org.tribuo.evaluation.Evaluation
Gets the predictions stored in this evaluation.
getPredictions() - Method in class org.tribuo.evaluation.metrics.MetricContext
Gets the predictions used by this context.
getPredictions() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
getProducerName() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The name of the framework or tool used to generate this model.
getProducerName() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The name of the framework or tool used to generate this model.
getProducerName() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The name of the framework or tool used to generate this model.
getProducerNameBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The name of the framework or tool used to generate this model.
getProducerNameBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The name of the framework or tool used to generate this model.
getProducerNameBytes() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The name of the framework or tool used to generate this model.
getProducerVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the framework or tool used to generate this model.
getProducerVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The version of the framework or tool used to generate this model.
getProducerVersion() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The version of the framework or tool used to generate this model.
getProducerVersionBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the framework or tool used to generate this model.
getProducerVersionBytes() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The version of the framework or tool used to generate this model.
getProducerVersionBytes() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The version of the framework or tool used to generate this model.
getProvenance() - Method in class org.tribuo.anomaly.AnomalyFactory
 
getProvenance() - Method in class org.tribuo.anomaly.example.GaussianAnomalyDataSource
 
getProvenance() - Method in class org.tribuo.anomaly.liblinear.LinearAnomalyType
 
getProvenance() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
 
getProvenance() - Method in class org.tribuo.classification.baseline.DummyClassifierTrainer
 
getProvenance() - Method in class org.tribuo.classification.dtree.CARTClassificationTrainer
 
getProvenance() - Method in class org.tribuo.classification.dtree.impurity.Entropy
 
getProvenance() - Method in class org.tribuo.classification.dtree.impurity.GiniIndex
 
getProvenance() - Method in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
getProvenance() - Method in class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
 
getProvenance() - Method in class org.tribuo.classification.ensemble.VotingCombiner
 
getProvenance() - Method in class org.tribuo.classification.example.DemoLabelDataSource
 
getProvenance() - Method in class org.tribuo.classification.LabelFactory
 
getProvenance() - Method in class org.tribuo.classification.liblinear.LinearClassificationType
 
getProvenance() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
 
getProvenance() - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
 
getProvenance() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
getProvenance() - Method in class org.tribuo.classification.sequence.viterbi.DefaultFeatureExtractor
 
getProvenance() - Method in class org.tribuo.classification.sequence.viterbi.NoopFeatureExtractor
 
getProvenance() - Method in class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
 
getProvenance() - Method in class org.tribuo.classification.sgd.crf.CRFTrainer
 
getProvenance() - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
 
getProvenance() - Method in class org.tribuo.classification.sgd.objectives.Hinge
 
getProvenance() - Method in class org.tribuo.classification.sgd.objectives.LogMulticlass
 
getProvenance() - Method in class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
 
getProvenance() - Method in class org.tribuo.clustering.ClusteringFactory
 
getProvenance() - Method in class org.tribuo.clustering.example.GaussianClusterDataSource
 
getProvenance() - Method in class org.tribuo.clustering.hdbscan.HdbscanTrainer
 
getProvenance() - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
getProvenance() - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
getProvenance() - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
getProvenance() - Method in class org.tribuo.common.nearest.KNNTrainer
 
getProvenance() - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
getProvenance() - Method in class org.tribuo.data.columnar.extractors.DateExtractor
 
getProvenance() - Method in class org.tribuo.data.columnar.extractors.DoubleExtractor
 
getProvenance() - Method in class org.tribuo.data.columnar.extractors.FloatExtractor
 
getProvenance() - Method in class org.tribuo.data.columnar.extractors.IdentityExtractor
 
getProvenance() - Method in class org.tribuo.data.columnar.extractors.IndexExtractor
 
getProvenance() - Method in class org.tribuo.data.columnar.extractors.IntExtractor
 
getProvenance() - Method in class org.tribuo.data.columnar.extractors.OffsetDateTimeExtractor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.feature.UniqueProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.field.DateFieldProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.field.IdentityProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.field.TextFieldProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.response.Quartile
 
getProvenance() - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
getProvenance() - Method in class org.tribuo.data.columnar.RowProcessor
 
getProvenance() - Method in class org.tribuo.data.csv.CSVDataSource
 
getProvenance() - Method in class org.tribuo.data.sql.SQLDataSource
 
getProvenance() - Method in class org.tribuo.data.sql.SQLDBConfig
 
getProvenance() - Method in class org.tribuo.data.text.DirectoryFileSource
 
getProvenance() - Method in class org.tribuo.data.text.impl.AverageAggregator
 
getProvenance() - Method in class org.tribuo.data.text.impl.BasicPipeline
 
getProvenance() - Method in class org.tribuo.data.text.impl.CasingPreprocessor
 
getProvenance() - Method in class org.tribuo.data.text.impl.FeatureHasher
 
getProvenance() - Method in class org.tribuo.data.text.impl.NewsPreprocessor
 
getProvenance() - Method in class org.tribuo.data.text.impl.NgramProcessor
 
getProvenance() - Method in class org.tribuo.data.text.impl.SimpleTextDataSource
 
getProvenance() - Method in class org.tribuo.data.text.impl.SumAggregator
 
getProvenance() - Method in class org.tribuo.data.text.impl.TextFeatureExtractorImpl
 
getProvenance() - Method in class org.tribuo.data.text.impl.TokenPipeline
 
getProvenance() - Method in class org.tribuo.data.text.impl.UniqueAggregator
 
getProvenance() - Method in class org.tribuo.dataset.DatasetView
 
getProvenance() - Method in class org.tribuo.dataset.MinimumCardinalityDataset
 
getProvenance() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
 
getProvenance() - Method in class org.tribuo.datasource.AggregateDataSource
 
getProvenance() - Method in class org.tribuo.datasource.IDXDataSource
 
getProvenance() - Method in class org.tribuo.datasource.LibSVMDataSource
 
getProvenance() - Method in class org.tribuo.datasource.ListDataSource
 
getProvenance() - Method in class org.tribuo.ensemble.BaggingTrainer
 
getProvenance() - Method in class org.tribuo.ensemble.EnsembleModel
 
getProvenance() - Method in class org.tribuo.hash.HashCodeHasher
 
getProvenance() - Method in class org.tribuo.hash.HashingTrainer
 
getProvenance() - Method in class org.tribuo.hash.MessageDigestHasher
 
getProvenance() - Method in class org.tribuo.hash.ModHashCodeHasher
 
getProvenance() - Method in class org.tribuo.ImmutableDataset
 
getProvenance() - Method in class org.tribuo.interop.oci.OCILabelConverter
 
getProvenance() - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
 
getProvenance() - Method in class org.tribuo.interop.oci.OCIRegressorConverter
 
getProvenance() - Method in class org.tribuo.interop.onnx.DenseTransformer
 
getProvenance() - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
getProvenance() - Method in class org.tribuo.interop.onnx.ImageTransformer
 
getProvenance() - Method in class org.tribuo.interop.onnx.LabelTransformer
 
getProvenance() - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
 
getProvenance() - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
getProvenance() - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
getProvenance() - Method in class org.tribuo.interop.tensorflow.ImageConverter
 
getProvenance() - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
getProvenance() - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
getProvenance() - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
getProvenance() - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
getProvenance() - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
getProvenance() - Method in class org.tribuo.json.JsonDataSource
 
getProvenance() - Method in class org.tribuo.math.kernel.Linear
 
getProvenance() - Method in class org.tribuo.math.kernel.Polynomial
 
getProvenance() - Method in class org.tribuo.math.kernel.RBF
 
getProvenance() - Method in class org.tribuo.math.kernel.Sigmoid
 
getProvenance() - Method in class org.tribuo.math.optimisers.AdaDelta
 
getProvenance() - Method in class org.tribuo.math.optimisers.AdaGrad
 
getProvenance() - Method in class org.tribuo.math.optimisers.AdaGradRDA
 
getProvenance() - Method in class org.tribuo.math.optimisers.Adam
 
getProvenance() - Method in class org.tribuo.math.optimisers.ParameterAveraging
 
getProvenance() - Method in class org.tribuo.math.optimisers.Pegasos
 
getProvenance() - Method in class org.tribuo.math.optimisers.RMSProp
 
getProvenance() - Method in class org.tribuo.math.optimisers.SGD
 
getProvenance() - Method in class org.tribuo.Model
 
getProvenance() - Method in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
 
getProvenance() - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
 
getProvenance() - Method in class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
 
getProvenance() - Method in class org.tribuo.multilabel.ensemble.MultiLabelVotingCombiner
 
getProvenance() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
getProvenance() - Method in class org.tribuo.multilabel.example.MultiLabelGaussianDataSource
 
getProvenance() - Method in class org.tribuo.multilabel.MultiLabelFactory
 
getProvenance() - Method in class org.tribuo.multilabel.sgd.objectives.BinaryCrossEntropy
 
getProvenance() - Method in class org.tribuo.multilabel.sgd.objectives.Hinge
 
getProvenance() - Method in class org.tribuo.MutableDataset
 
getProvenance() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
 
getProvenance() - Method in class org.tribuo.regression.ensemble.AveragingCombiner
 
getProvenance() - Method in class org.tribuo.regression.example.GaussianDataSource
 
getProvenance() - Method in class org.tribuo.regression.example.NonlinearGaussianDataSource
 
getProvenance() - Method in class org.tribuo.regression.liblinear.LinearRegressionType
 
getProvenance() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
 
getProvenance() - Method in class org.tribuo.regression.RegressionFactory
 
getProvenance() - Method in class org.tribuo.regression.rtree.CARTJointRegressionTrainer
 
getProvenance() - Method in class org.tribuo.regression.rtree.CARTRegressionTrainer
 
getProvenance() - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
 
getProvenance() - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
 
getProvenance() - Method in class org.tribuo.regression.sgd.objectives.AbsoluteLoss
 
getProvenance() - Method in class org.tribuo.regression.sgd.objectives.Huber
 
getProvenance() - Method in class org.tribuo.regression.sgd.objectives.SquaredLoss
 
getProvenance() - Method in class org.tribuo.regression.slm.ElasticNetCDTrainer
 
getProvenance() - Method in class org.tribuo.regression.slm.SLMTrainer
 
getProvenance() - Method in class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
 
getProvenance() - Method in class org.tribuo.sequence.HashingSequenceTrainer
 
getProvenance() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
 
getProvenance() - Method in class org.tribuo.sequence.IndependentSequenceTrainer
 
getProvenance() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset
 
getProvenance() - Method in class org.tribuo.sequence.MutableSequenceDataset
 
getProvenance() - Method in class org.tribuo.sequence.SequenceModel
 
getProvenance() - Method in class org.tribuo.transform.TransformationMap
 
getProvenance() - Method in class org.tribuo.transform.TransformationMap.TransformationList
 
getProvenance() - Method in class org.tribuo.transform.transformations.BinningTransformation
 
getProvenance() - Method in class org.tribuo.transform.transformations.IDFTransformation
 
getProvenance() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation
 
getProvenance() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation
 
getProvenance() - Method in class org.tribuo.transform.transformations.SimpleTransform
 
getProvenance() - Method in class org.tribuo.transform.TransformerMap
 
getProvenance() - Method in class org.tribuo.transform.TransformTrainer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.WhitespaceTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
getProvenance() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
getQuantizationAnnotation(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotation(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotation(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationCount() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantizationAnnotationOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
getQuantParameterTensorNames(int) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNames(int) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNames(int) - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesCount() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesCount() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesCount() - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesList() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesList() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesList() - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getQuantParameterTensorNamesOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
getRawData() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Serializations can either use one of the fields above, or use this raw bytes field.
getRawData() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Serializations can either use one of the fields above, or use this raw bytes field.
getRawData() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Serializations can either use one of the fields above, or use this raw bytes field.
getRecall() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns the recall of the anomalous events, i.e., true positives divided by the number of positives.
getRefAttrName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
getRefAttrName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
getRefAttrName() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
getRefAttrNameBytes() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
getRefAttrNameBytes() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
getRefAttrNameBytes() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
getReference() - Method in interface org.tribuo.math.la.MatrixIterator
Gets the MatrixTuple reference that this iterator updates.
getReference() - Method in interface org.tribuo.math.la.VectorIterator
Gets the reference to the VectorTuple this iterator updates.
getReference() - Method in class org.tribuo.util.onnx.ONNXInitializer
 
getReference() - Method in class org.tribuo.util.onnx.ONNXNode
 
getReference() - Method in class org.tribuo.util.onnx.ONNXPlaceholder
 
getReference() - Method in class org.tribuo.util.onnx.ONNXRef
Gets the output name of this object.
getRemoved() - Method in class org.tribuo.dataset.MinimumCardinalityDataset
The feature names that were removed.
getRemoved() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset
The feature names that were removed.
getResponseProcessor() - Method in class org.tribuo.data.columnar.RowProcessor
Returns the response processor this RowProcessor uses.
getRMSE(String) - Method in class org.tribuo.classification.explanations.lime.LIMEExplanation
Get the RMSE of a specific dimension of the explanation model.
getRoot() - Method in class org.tribuo.common.tree.TreeModel
Returns the root node of this tree.
getRoot() - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
Returns null, as this model contains multiple roots, one per regression output dimension.
getRoots() - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
Returns an unmodifiable view on the root node collection.
getRow() - Method in class org.tribuo.data.columnar.ColumnarIterator
Returns the next row of data based on internal state stored by the implementor, or Optional.empty() if there is no more data.
getRow() - Method in class org.tribuo.data.csv.CSVIterator
 
getRow() - Method in class org.tribuo.data.sql.ResultSetIterator
 
getRow() - Method in class org.tribuo.json.JsonFileIterator
 
getRow(int) - Method in class org.tribuo.math.la.DenseMatrix
 
getRow(int) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
getRow(int) - Method in interface org.tribuo.math.la.Matrix
An SGDVector view of the row.
getRowData() - Method in class org.tribuo.data.columnar.ColumnarIterator.Row
Gets the row data.
getS() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
UTF-8 string
getS() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
UTF-8 string
getS() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
UTF-8 string
getScaledMinImpurityDecrease() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
Gets the minimum impurity decrease necessary to split a node.
getScore() - Method in class org.tribuo.anomaly.Event
Get a real valued score for this label.
getScore() - Method in class org.tribuo.classification.Label
Get a real valued score for this label.
getScore() - Method in class org.tribuo.clustering.ClusterID
Get a real valued score for this ClusterID.
getScore() - Method in class org.tribuo.multilabel.MultiLabel
The overall score for this set of labels.
getScoreAggregation() - Method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
Gets the score aggregation function.
getScores() - Method in class org.tribuo.Excuse
Returns the scores for all outputs and the relevant feature values.
getSecondCount() - Method in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
Gets the second marginal distribution.
getSecondFieldName() - Method in class org.tribuo.data.columnar.ColumnarFeature
If it's a conjunction feature, return the second field name.
getSegment() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
getSegment() - Method in class ai.onnx.proto.OnnxMl.TensorProto
optional .onnx.TensorProto.Segment segment = 3;
getSegment() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
optional .onnx.TensorProto.Segment segment = 3;
getSegmentBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
getSegmentOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
getSegmentOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorProto
optional .onnx.TensorProto.Segment segment = 3;
getSegmentOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
optional .onnx.TensorProto.Segment segment = 3;
getSequenceModel() - Method in class org.tribuo.evaluation.metrics.MetricContext
Gets the SequenceModel used by this context.
getSequenceTrainer() - Method in class org.tribuo.classification.sgd.crf.CRFOptions
Returns the configured CRF trainer.
getSequenceTrainer(Trainer<Label>) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions
Creates a viterbi trainer wrapping the supplied label trainer.
getSequenceType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
getSequenceType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a sequence.
getSequenceType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a sequence.
getSequenceTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
getSequenceTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
getSequenceTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a sequence.
getSequenceTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a sequence.
getSerializableForm(boolean) - Method in class org.tribuo.anomaly.Event
Returns "EventType" or "EventType,score=eventScore".
getSerializableForm(boolean) - Method in class org.tribuo.classification.Label
Returns "labelName" or "labelName,score=labelScore".
getSerializableForm(boolean) - Method in class org.tribuo.clustering.ClusterID
Returns "id" or "id,score=idScore".
getSerializableForm(boolean) - Method in class org.tribuo.multilabel.MultiLabel
For a MultiLabel with label set = {a, b, c}, outputs a string of the form:
getSerializableForm(boolean) - Method in interface org.tribuo.Output
Generates a String suitable for writing to a csv or json file.
getSerializableForm(boolean) - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
getSerializableForm(boolean) - Method in class org.tribuo.regression.Regressor
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
getSerializedSize() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
getShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
getShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
optional .onnx.TensorShapeProto shape = 2;
getShape() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SparseTensorOrBuilder
optional .onnx.TensorShapeProto shape = 2;
getShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
getShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
optional .onnx.TensorShapeProto shape = 2;
getShape() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.TensorOrBuilder
optional .onnx.TensorShapeProto shape = 2;
getShape() - Method in class org.tribuo.math.la.DenseMatrix
 
getShape() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
getShape() - Method in class org.tribuo.math.la.DenseVector
 
getShape() - Method in class org.tribuo.math.la.SparseVector
 
getShape() - Method in interface org.tribuo.math.la.Tensor
Returns an int array specifying the shape of this Tensor.
getShapeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
getShapeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
getShapeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
getShapeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
optional .onnx.TensorShapeProto shape = 2;
getShapeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SparseTensorOrBuilder
optional .onnx.TensorShapeProto shape = 2;
getShapeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
getShapeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
optional .onnx.TensorShapeProto shape = 2;
getShapeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.TensorOrBuilder
optional .onnx.TensorShapeProto shape = 2;
getSimpleSGD(double) - Static method in class org.tribuo.math.optimisers.SGD
Generates an SGD optimiser with a constant learning rate set to learningRate.
getSimpleSGD(double, double, SGD.Momentum) - Static method in class org.tribuo.math.optimisers.SGD
Generates an SGD optimiser with a constant learning rate set to learningRate, with momentum.
getSolverType() - Method in class org.tribuo.anomaly.liblinear.LinearAnomalyType
 
getSolverType() - Method in enum class org.tribuo.anomaly.liblinear.LinearAnomalyType.LinearType
Gets the type of the solver.
getSolverType() - Method in class org.tribuo.classification.liblinear.LinearClassificationType
 
getSolverType() - Method in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
Gets the LibLinear solver type.
getSolverType() - Method in interface org.tribuo.common.liblinear.LibLinearType
Returns the liblinear enum type.
getSolverType() - Method in class org.tribuo.regression.liblinear.LinearRegressionType
 
getSolverType() - Method in enum class org.tribuo.regression.liblinear.LinearRegressionType.LinearType
Returns the liblinear enum.
getSourceDescription() - Method in class org.tribuo.Dataset
A String description of this dataset.
getSourceDescription() - Method in class org.tribuo.sequence.SequenceDataset
Returns the description of the source provenance.
getSourceProvenance() - Method in class org.tribuo.Dataset
The provenance of the data this Dataset contains.
getSourceProvenance() - Method in class org.tribuo.provenance.DatasetProvenance
The input data provenance.
getSourceProvenance() - Method in class org.tribuo.sequence.SequenceDataset
Returns the source provenance.
getSparseInitializer(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
getSparseInitializer(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
Initializers (see above) stored in sparse format.
getSparseInitializer(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Initializers (see above) stored in sparse format.
getSparseInitializerBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
getSparseInitializerBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
getSparseInitializerCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
getSparseInitializerCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto
Initializers (see above) stored in sparse format.
getSparseInitializerCount() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Initializers (see above) stored in sparse format.
getSparseInitializerList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
getSparseInitializerList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
Initializers (see above) stored in sparse format.
getSparseInitializerList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Initializers (see above) stored in sparse format.
getSparseInitializerOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
getSparseInitializerOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
Initializers (see above) stored in sparse format.
getSparseInitializerOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Initializers (see above) stored in sparse format.
getSparseInitializerOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
getSparseInitializerOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
Initializers (see above) stored in sparse format.
getSparseInitializerOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Initializers (see above) stored in sparse format.
getSparseTensor() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
getSparseTensor() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
sparse tensor value
getSparseTensor() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
sparse tensor value
getSparseTensorBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
getSparseTensorOrBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
getSparseTensorOrBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
sparse tensor value
getSparseTensorOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
sparse tensor value
getSparseTensors(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
getSparseTensors(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of sparse tensors
getSparseTensors(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of sparse tensors
getSparseTensorsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
getSparseTensorsBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
getSparseTensorsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
getSparseTensorsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of sparse tensors
getSparseTensorsCount() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of sparse tensors
getSparseTensorsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
getSparseTensorsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of sparse tensors
getSparseTensorsList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of sparse tensors
getSparseTensorsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
getSparseTensorsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of sparse tensors
getSparseTensorsOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of sparse tensors
getSparseTensorsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
getSparseTensorsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of sparse tensors
getSparseTensorsOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of sparse tensors
getSparseTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
getSparseTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
getSparseTensorType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
getSparseTensorTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
getSparseTensorTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
getSparseTensorTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
getSparseTensorTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
getSplitCharacters() - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
Deprecated.
getSplitPatternRegex() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
Gets the String form of the regex in use.
getSplitXDigitsCharacters() - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
Deprecated.
getSqrtDecaySGD(double) - Static method in class org.tribuo.math.optimisers.SGD
Generates an SGD optimiser with a sqrt decaying learning rate initialised to learningRate.
getSqrtDecaySGD(double, double, SGD.Momentum) - Static method in class org.tribuo.math.optimisers.SGD
Generates an SGD optimiser with a sqrt decaying learning rate initialised to learningRate, with momentum.
getStackSize() - Method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
Gets the stack size of this model.
getStandardDeviation() - Method in class org.tribuo.evaluation.DescriptiveStats
Calculates the standard deviation of the values.
getStart() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
getStart() - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
getStart() - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
getStart() - Method in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
getStart() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
getStart() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
getStart() - Method in interface org.tribuo.util.tokens.Tokenizer
Gets the starting character offset of the current token in the character sequence
getStart() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
getStatement() - Method in class org.tribuo.data.sql.SQLDBConfig
Constructs a statement based on the object fields.
getStdDev() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the sample standard deviation.
getStringData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For strings.
getStringData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
For strings.
getStringData(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For strings.
getStringDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For strings.
getStringDataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For strings.
getStringDataCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For strings.
getStringDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For strings.
getStringDataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For strings.
getStringDataList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For strings.
getStrings(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of UTF-8 strings
getStrings(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of UTF-8 strings
getStrings(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of UTF-8 strings
getStringsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of UTF-8 strings
getStringsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of UTF-8 strings
getStringsCount() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of UTF-8 strings
getStringsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of UTF-8 strings
getStringsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of UTF-8 strings
getStringsList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of UTF-8 strings
getSvmType() - Method in class org.tribuo.common.libsvm.SVMParameters
Gets the SVM type.
getT() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
getT() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
tensor value
getT() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
tensor value
getTarget() - Method in class org.tribuo.anomaly.evaluation.AnomalyMetric
 
getTarget() - Method in class org.tribuo.classification.evaluation.LabelMetric
 
getTarget() - Method in class org.tribuo.clustering.evaluation.ClusteringMetric
 
getTarget() - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
The target for this metric instance.
getTarget() - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
 
getTarget() - Method in class org.tribuo.regression.evaluation.RegressionMetric
 
getTarget(ImmutableOutputInfo<Label>, Label) - Method in class org.tribuo.classification.sgd.fm.FMClassificationTrainer
 
getTarget(ImmutableOutputInfo<Label>, Label) - Method in class org.tribuo.classification.sgd.linear.LinearSGDTrainer
 
getTarget(ImmutableOutputInfo<MultiLabel>, MultiLabel) - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
 
getTarget(ImmutableOutputInfo<MultiLabel>, MultiLabel) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
 
getTarget(ImmutableOutputInfo<Regressor>, Regressor) - Method in class org.tribuo.regression.sgd.fm.FMRegressionTrainer
 
getTarget(ImmutableOutputInfo<Regressor>, Regressor) - Method in class org.tribuo.regression.sgd.linear.LinearSGDTrainer
 
getTarget(ImmutableOutputInfo<T>, T) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Extracts the appropriate training time representation from the supplied output.
getTBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
getTensor(String) - Method in class org.tribuo.interop.tensorflow.TensorMap
Returns the specified tensor if present.
getTensorName() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
optional string tensor_name = 1;
getTensorName() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
optional string tensor_name = 1;
getTensorName() - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
optional string tensor_name = 1;
getTensorNameBytes() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
optional string tensor_name = 1;
getTensorNameBytes() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
optional string tensor_name = 1;
getTensorNameBytes() - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
optional string tensor_name = 1;
getTensors(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
getTensors(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of tensors
getTensors(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of tensors
getTensorsBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
getTensorsBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
getTensorsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
getTensorsCount() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of tensors
getTensorsCount() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of tensors
getTensorsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
getTensorsList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of tensors
getTensorsList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of tensors
getTensorsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
getTensorsOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of tensors
getTensorsOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of tensors
getTensorsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
getTensorsOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
list of tensors
getTensorsOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
list of tensors
getTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
getTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a tensor.
getTensorType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a tensor.
getTensorTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
getTensorTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
getTensorTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a tensor.
getTensorTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a tensor.
getTest() - Method in class org.tribuo.evaluation.TrainTestSplitter
Gets the testing datasource.
getTestDatasetProvenance() - Method in class org.tribuo.provenance.EvaluationProvenance
The test dataset provenance.
getText() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
getText() - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
getText() - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
getText() - Method in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
getText() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
getText() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
getText() - Method in interface org.tribuo.util.tokens.Tokenizer
Gets the text of the current token, as a string
getText() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
getThreshold() - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
Returns the threshold this converter uses to emit labels.
getToken() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
getToken() - Method in interface org.tribuo.util.tokens.Tokenizer
Generates a Token object from the current state of the tokenizer.
getTokenizer() - Method in class org.tribuo.util.tokens.options.BreakIteratorTokenizerOptions
 
getTokenizer() - Method in class org.tribuo.util.tokens.options.CoreTokenizerOptions
 
getTokenizer() - Method in class org.tribuo.util.tokens.options.SplitCharactersTokenizerOptions
 
getTokenizer() - Method in class org.tribuo.util.tokens.options.SplitPatternTokenizerOptions
 
getTokenizer() - Method in interface org.tribuo.util.tokens.options.TokenizerOptions
Creates the appropriately configured tokenizer.
getTopFeatures(int) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyModel
 
getTopFeatures(int) - Method in class org.tribuo.classification.baseline.DummyClassifierModel
 
getTopFeatures(int) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel
 
getTopFeatures(int) - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesModel
 
getTopFeatures(int) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
 
getTopFeatures(int) - Method in class org.tribuo.classification.sgd.crf.CRFModel
 
getTopFeatures(int) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMModel
 
getTopFeatures(int) - Method in class org.tribuo.clustering.hdbscan.HdbscanModel
 
getTopFeatures(int) - Method in class org.tribuo.clustering.kmeans.KMeansModel
 
getTopFeatures(int) - Method in class org.tribuo.common.libsvm.LibSVMModel
 
getTopFeatures(int) - Method in class org.tribuo.common.nearest.KNNModel
 
getTopFeatures(int) - Method in class org.tribuo.common.sgd.AbstractFMModel
Gets the top n features for each output dimension.
getTopFeatures(int) - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
 
getTopFeatures(int) - Method in class org.tribuo.common.tree.TreeModel
 
getTopFeatures(int) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
getTopFeatures(int) - Method in class org.tribuo.common.xgboost.XGBoostModel
 
getTopFeatures(int) - Method in class org.tribuo.ensemble.EnsembleModel
 
getTopFeatures(int) - Method in class org.tribuo.interop.oci.OCIModel
 
getTopFeatures(int) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
 
getTopFeatures(int) - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceModel
Returns an empty map, as the top features are not well defined for most TensorFlow models.
getTopFeatures(int) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
 
getTopFeatures(int) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Deep learning models don't do feature rankings.
getTopFeatures(int) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
 
getTopFeatures(int) - Method in class org.tribuo.Model
Gets the top n features associated with this model.
getTopFeatures(int) - Method in class org.tribuo.multilabel.baseline.ClassifierChainModel
 
getTopFeatures(int) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelModel
This aggregates the top features from each of the models.
getTopFeatures(int) - Method in class org.tribuo.regression.baseline.DummyRegressionModel
 
getTopFeatures(int) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
 
getTopFeatures(int) - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
 
getTopFeatures(int) - Method in class org.tribuo.regression.slm.SparseLinearModel
 
getTopFeatures(int) - Method in class org.tribuo.sequence.IndependentSequenceModel
 
getTopFeatures(int) - Method in class org.tribuo.sequence.SequenceModel
Gets the top n features associated with this model.
getTopFeatures(int) - Method in class org.tribuo.transform.TransformedModel
 
getTopLabels(Map<String, Label>) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
 
getTopLabels(Map<String, Label>, int) - Static method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
 
getTOrBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
getTOrBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
tensor value
getTOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
tensor value
getTotalCover() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Total Cover is similar to cover, but not locally averaged by weight, and thus not skewed in the way that weight can be skewed.
getTotalCover() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The total number of examples a feature discrimnates between.
getTotalCover(int) - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Total Cover is similar to cover, but not locally averaged by weight, and thus not skewed in the way that weight can be skewed.
getTotalGain() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Total Gain is similar to gain, but not locally averaged by weight, and thus not skewed in the way that weight can be skewed.
getTotalGain() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The total gain across all times the feature is used to split.
getTotalGain(int) - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Total Gain is similar to gain, but not locally averaged by weight, and thus not skewed in the way that weight can be skewed.
getTotalObservations() - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
getTotalObservations() - Method in class org.tribuo.classification.ImmutableLabelInfo
 
getTotalObservations() - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
getTotalObservations() - Method in interface org.tribuo.ImmutableOutputInfo
Returns the total number of observed outputs seen by this ImmutableOutputInfo.
getTotalObservations() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
getTotalObservations() - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
getTrain() - Method in class org.tribuo.evaluation.TrainTestSplitter
Gets the training data source.
getTrainer() - Method in interface org.tribuo.classification.ClassificationOptions
Constructs the trainer based on the provided arguments.
getTrainer() - Method in class org.tribuo.classification.dtree.CARTClassificationOptions
 
getTrainer() - Method in class org.tribuo.classification.experiments.AllTrainerOptions
 
getTrainer() - Method in class org.tribuo.classification.liblinear.LibLinearOptions
 
getTrainer() - Method in class org.tribuo.classification.libsvm.LibSVMOptions
 
getTrainer() - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesOptions
 
getTrainer() - Method in class org.tribuo.classification.sgd.fm.FMClassificationOptions
 
getTrainer() - Method in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
getTrainer() - Method in class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
getTrainer() - Method in class org.tribuo.classification.xgboost.XGBoostOptions
 
getTrainer() - Method in class org.tribuo.clustering.hdbscan.HdbscanOptions
Gets the configured HdbscanTrainer using the options in this object.
getTrainer() - Method in class org.tribuo.clustering.kmeans.KMeansOptions
Gets the configured KMeansTrainer using the options in this object.
getTrainer() - Method in class org.tribuo.common.nearest.KNNClassifierOptions
 
getTrainer() - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
Gets the trainer as configured by these options.
getTrainer() - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
Gets the LinearSGDTrainer specified by the options in this object.
getTrainer() - Method in class org.tribuo.regression.xgboost.XGBoostOptions
Gets the configured XGBoostRegressionTrainer.
getTrainerProvenance() - Method in class org.tribuo.provenance.ModelProvenance
The trainer provenance.
getTrainingInfo(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
getTrainingInfo(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto
Training-specific information.
getTrainingInfo(int) - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Training-specific information.
getTrainingInfoBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
getTrainingInfoBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
getTrainingInfoCount() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
getTrainingInfoCount() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Training-specific information.
getTrainingInfoCount() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Training-specific information.
getTrainingInfoList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
getTrainingInfoList() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Training-specific information.
getTrainingInfoList() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Training-specific information.
getTrainingInfoOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
getTrainingInfoOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto
Training-specific information.
getTrainingInfoOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Training-specific information.
getTrainingInfoOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
getTrainingInfoOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Training-specific information.
getTrainingInfoOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Training-specific information.
getTrainingTime() - Method in class org.tribuo.provenance.ModelProvenance
The training timestamp.
getTransformationProvenance() - Method in class org.tribuo.provenance.DatasetProvenance
The transformation provenances, in application order.
getTransformerMap() - Method in class org.tribuo.transform.TransformedModel
Gets the transformers that this model applies to each example.
getTribuoProvenance() - Method in class org.tribuo.interop.onnx.ONNXExternalModel
Returns the model provenance from the ONNX model if that model was trained in Tribuo.
getTribuoVersion() - Method in class org.tribuo.provenance.DatasetProvenance
The Tribuo version used to create this dataset.
getTribuoVersion() - Method in class org.tribuo.provenance.EvaluationProvenance
The Tribuo version used to create this dataset.
getTribuoVersion() - Method in class org.tribuo.provenance.ModelProvenance
The Tribuo version used to create this dataset.
getTribuoVersion() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
The Tribuo version.
getTrueNegatives() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns the number of true negatives, i.e., expected events classified as events.
getTruePositives() - Method in interface org.tribuo.anomaly.evaluation.AnomalyEvaluation
Returns the number of true positives, i.e., anomalous events classified as anomalous.
getType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The type field MUST be present for this version of the IR.
getType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
The type field MUST be present for this version of the IR.
getType() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
The type field MUST be present for this version of the IR.
getType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
getType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
getType() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
getType() - Method in class org.tribuo.anomaly.Event
Gets the event type.
getType() - Method in class org.tribuo.util.onnx.ONNXAttribute
Gets the attribute's type.
getType() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
getType() - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
getType() - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
getType() - Method in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
getType() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
getType() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
getType() - Method in interface org.tribuo.util.tokens.Tokenizer
Gets the type of the current token.
getType() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
getTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
getTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
getTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
getTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
getUint64Data(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64Data(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64Data(int) - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64DataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64DataCount() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64DataCount() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64DataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64DataList() - Method in class ai.onnx.proto.OnnxMl.TensorProto
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUint64DataList() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
getUniqueObservations() - Method in class org.tribuo.CategoricalInfo
Gets the number of unique values this CategoricalInfo has observed.
getUnknownCount() - Method in class org.tribuo.anomaly.AnomalyInfo
 
getUnknownCount() - Method in class org.tribuo.classification.LabelInfo
 
getUnknownCount() - Method in class org.tribuo.clustering.ClusteringInfo
 
getUnknownCount() - Method in class org.tribuo.multilabel.MultiLabelInfo
 
getUnknownCount() - Method in interface org.tribuo.OutputInfo
Returns the number of unknown Output instances (generated by OutputFactory.getUnknownOutput()) that this OutputInfo has seen.
getUnknownCount() - Method in class org.tribuo.regression.RegressionInfo
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
getUnknownFields() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
getUnknownOutput() - Method in class org.tribuo.anomaly.AnomalyFactory
 
getUnknownOutput() - Method in class org.tribuo.classification.LabelFactory
 
getUnknownOutput() - Method in class org.tribuo.clustering.ClusteringFactory
 
getUnknownOutput() - Method in class org.tribuo.multilabel.MultiLabelFactory
 
getUnknownOutput() - Method in interface org.tribuo.OutputFactory
Returns the singleton unknown output of type T which can be used for prediction time examples.
getUnknownOutput() - Method in class org.tribuo.regression.RegressionFactory
 
getUnknownToken() - Method in class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
a getter for the "unknown" token specified during initialization.
getUpdateBinding(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
getUpdateBinding(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
Gradient-based training is usually an iterative procedure.
getUpdateBinding(int) - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
Gradient-based training is usually an iterative procedure.
getUpdateBindingBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
getUpdateBindingBuilderList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
getUpdateBindingCount() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
getUpdateBindingCount() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
Gradient-based training is usually an iterative procedure.
getUpdateBindingCount() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
Gradient-based training is usually an iterative procedure.
getUpdateBindingList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
getUpdateBindingList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
Gradient-based training is usually an iterative procedure.
getUpdateBindingList() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
Gradient-based training is usually an iterative procedure.
getUpdateBindingOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
getUpdateBindingOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
Gradient-based training is usually an iterative procedure.
getUpdateBindingOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
Gradient-based training is usually an iterative procedure.
getUpdateBindingOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
getUpdateBindingOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
Gradient-based training is usually an iterative procedure.
getUpdateBindingOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
Gradient-based training is usually an iterative procedure.
getUpperMedian() - Method in class org.tribuo.data.columnar.processors.response.Quartile
The upper quartile value.
getUseRandomSplitPoints() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
getUseRandomSplitPoints() - Method in interface org.tribuo.common.tree.DecisionTreeTrainer
Returns whether to choose split points for features at random.
getValue() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string value = 2;
getValue() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
optional string value = 2;
getValue() - Method in interface ai.onnx.proto.OnnxMl.StringStringEntryProtoOrBuilder
optional string value = 2;
getValue() - Method in class org.tribuo.Feature
Returns the feature value.
getValue() - Method in class org.tribuo.regression.Regressor.DimensionTuple
Returns the value.
getValueBytes() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string value = 2;
getValueBytes() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
optional string value = 2;
getValueBytes() - Method in interface ai.onnx.proto.OnnxMl.StringStringEntryProtoOrBuilder
optional string value = 2;
getValueCase() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
getValueCase() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
getValueCase() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
 
getValueCase() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
getValueCase() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
getValueCase() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
 
getValueDescriptor() - Method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
 
getValueDescriptor() - Method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
 
getValueDescriptor() - Method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
 
getValueDescriptor() - Method in enum class ai.onnx.proto.OnnxMl.Version
 
getValueInfo(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
getValueInfo(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
Information for the values in the graph.
getValueInfo(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Information for the values in the graph.
getValueInfoBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
getValueInfoBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
getValueInfoCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
getValueInfoCount() - Method in class ai.onnx.proto.OnnxMl.GraphProto
Information for the values in the graph.
getValueInfoCount() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Information for the values in the graph.
getValueInfoList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
getValueInfoList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
Information for the values in the graph.
getValueInfoList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Information for the values in the graph.
getValueInfoOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
getValueInfoOrBuilder(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto
Information for the values in the graph.
getValueInfoOrBuilder(int) - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Information for the values in the graph.
getValueInfoOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
getValueInfoOrBuilderList() - Method in class ai.onnx.proto.OnnxMl.GraphProto
Information for the values in the graph.
getValueInfoOrBuilderList() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
Information for the values in the graph.
getValues() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
getValues() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The sequence of non-default values are encoded as a tensor of shape [NNZ].
getValues() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
getValues() - Method in class org.tribuo.regression.Regressor
Returns the regression values.
getValuesBuilder() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
getValuesOrBuilder() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
getValuesOrBuilder() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The sequence of non-default values are encoded as a tensor of shape [NNZ].
getValuesOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
getValueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
getValueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
This field MUST be present for this version of the IR.
getValueType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.MapOrBuilder
This field MUST be present for this version of the IR.
getValueType() - Method in class org.tribuo.data.columnar.extractors.DateExtractor
 
getValueType() - Method in class org.tribuo.data.columnar.extractors.DoubleExtractor
 
getValueType() - Method in class org.tribuo.data.columnar.extractors.FloatExtractor
 
getValueType() - Method in class org.tribuo.data.columnar.extractors.IdentityExtractor
 
getValueType() - Method in class org.tribuo.data.columnar.extractors.IndexExtractor
 
getValueType() - Method in class org.tribuo.data.columnar.extractors.IntExtractor
 
getValueType() - Method in class org.tribuo.data.columnar.extractors.OffsetDateTimeExtractor
 
getValueType() - Method in interface org.tribuo.data.columnar.FieldExtractor
Gets the class of the value produced by this extractor.
getValueTypeBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
getValueTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
getValueTypeOrBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
This field MUST be present for this version of the IR.
getValueTypeOrBuilder() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.MapOrBuilder
This field MUST be present for this version of the IR.
getVariance() - Method in class org.tribuo.evaluation.DescriptiveStats
Calculates the sample variance of the values.
getVariance() - Method in class org.tribuo.RealInfo
Gets the sample variance.
getVariance() - Method in class org.tribuo.regression.Regressor.DimensionTuple
Returns the variance.
getVariance() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the sample variance.
getVariance(int) - Method in class org.tribuo.regression.ImmutableRegressionInfo
Gets the variance this RegressionInfo has seen for that id.
getVariance(String) - Method in class org.tribuo.regression.RegressionInfo
Gets the variance this RegressionInfo has seen, or NaN if it's not seen that dimension.
getVariances() - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
Accessor used in the tests.
getVariances() - Method in class org.tribuo.regression.Regressor
The variances of the regressed values, if known.
getVersion() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The version of the operator set being identified.
getVersion() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
The version of the operator set being identified.
getVersion() - Method in interface ai.onnx.proto.OnnxMl.OperatorSetIdProtoOrBuilder
The version of the operator set being identified.
getVocab() - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Returns the vocabulary that this BERTFeatureExtractor understands.
getWeight() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Weight measures the number a times a feature occurs in the model.
getWeight() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The number of times a feature is used in the model.
getWeight() - Method in class org.tribuo.Example
Gets the example's weight.
getWeight() - Method in class org.tribuo.sequence.SequenceExample
Gets the weight of this sequence.
getWeight(int) - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Weight measures the number a times a feature occurs in the model.
getWeight(int, int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Returns the feature/label weight for the specified feature and label id.
getWeightMatrix() - Method in class org.tribuo.math.LinearParameters
Returns the weight matrix.
getWeights() - Method in class org.tribuo.regression.slm.SparseLinearModel
Gets a copy of the model parameters.
getWeightsCopy() - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
Returns a copy of the weights.
getWeightSum() - Method in class org.tribuo.classification.dtree.impl.ClassifierTrainingNode
 
getWeightSum() - Method in class org.tribuo.common.tree.AbstractTrainingNode
The sum of the weights associated with this node's examples.
getWeightSum() - Method in class org.tribuo.regression.rtree.impl.JointRegressorTrainingNode
 
getWeightSum() - Method in class org.tribuo.regression.rtree.impl.RegressorTrainingNode
 
GINI - Enum constant in enum class org.tribuo.classification.dtree.CARTClassificationOptions.ImpurityType
Uses GiniIndex.
GiniIndex - Class in org.tribuo.classification.dtree.impurity
The Gini index impurity measure.
GiniIndex() - Constructor for class org.tribuo.classification.dtree.impurity.GiniIndex
 
GPU_HIST - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
GPU implementation of the XGBoostTrainer.TreeMethod.HIST algorithm.
GRADIENT_DESCENT - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
A standard gradient descent optimiser with a fixed learning rate.
GradientOptimiser - Enum Class in org.tribuo.interop.tensorflow
An enum for the gradient optimisers exposed by TensorFlow-Java.
GradientOptimiserOptions - Class in org.tribuo.math.optimisers
CLI options for configuring a gradient optimiser.
GradientOptimiserOptions() - Constructor for class org.tribuo.math.optimisers.GradientOptimiserOptions
 
GradientOptimiserOptions.StochasticGradientOptimiserType - Enum Class in org.tribuo.math.optimisers
Type of the gradient optimisers available in CLIs.
gradientOptions - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Gradient descent options.
gradientOptions - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Gradient descent options.
gradientOptions - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
Gradient descent options.
gradientParamNames - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Gradient optimizer param names, see org.tribuo.interop.tensorflow.GradientOptimiser.
gradientParamValues - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Gradient optimizer param values, see org.tribuo.interop.tensorflow.GradientOptimiser.
gradients(Pair<Double, SGDVector>, SGDVector) - Method in class org.tribuo.common.sgd.FMParameters
Generate the gradients for a particular feature vector given the loss and the per output gradients.
gradients(Pair<Double, SGDVector>, SGDVector) - Method in interface org.tribuo.math.FeedForwardParameters
Generates the parameter gradients given the loss, output gradient and input features.
gradients(Pair<Double, SGDVector>, SGDVector) - Method in class org.tribuo.math.LinearParameters
Generate the gradients for a particular feature vector given the loss and the per output gradients.
GRAPH - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
GRAPH = 5;
GRAPH_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
GRAPH_HASH - Static variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance
The name of the provenance field containing the graph hash.
GRAPH_HASH - Static variable in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
The name of the provenance field containing the graph hash.
GRAPH_LAST_MOD - Static variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance
The name of the provenance field containing the graph modified timestamp.
GRAPH_LAST_MOD - Static variable in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
The name of the provenance field containing the graph modified timestamp.
GRAPH_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
GRAPH = 5;
graphDef - Variable in class org.tribuo.interop.tensorflow.example.GraphDefTuple
The graph definition protobuf.
GraphDefTuple - Class in org.tribuo.interop.tensorflow.example
A tuple containing a graph def protobuf along with the relevant operation names.
GraphDefTuple(GraphDef, String, String) - Constructor for class org.tribuo.interop.tensorflow.example.GraphDefTuple
Creates a graphDef record.
graphPath - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
GRAPHS - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
GRAPHS = 10;
GRAPHS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
GRAPHS_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
GRAPHS = 10;
GREATER - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Greater than, returns the element-wise greater than operation on the two tensors.
GREATER_OR_EQUAL - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Greater than or equal to, returns the element-wise greater than or equal to operation on the two tensors.
greaterThan - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
GROUPS - Enum constant in enum class org.tribuo.data.columnar.processors.field.RegexFieldProcessor.Mode
Triggers feature generation for each matching group in the string.
grow(int) - Method in class org.tribuo.common.tree.impl.IntArrayContainer
Grows the backing array, copying the elements.
growArray() - Method in class org.tribuo.impl.ArrayExample
Grows the backing arrays by size+1.
growArray() - Method in class org.tribuo.impl.BinaryFeaturesExample
Grows the backing arrays by size+1.
growArray(int) - Method in class org.tribuo.impl.ArrayExample
Grows the backing arrays storing the names and values.
growArray(int) - Method in class org.tribuo.impl.BinaryFeaturesExample
Grows the backing arrays storing the names.
growArray(int) - Method in class org.tribuo.impl.IndexedArrayExample
 
gStatistic - Variable in class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
The G test statistic.
gTest(List<T1>, List<T2>, Set<List<T3>>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the GTest statistics for the input variables conditioned on the set.
GTestStatistics(double, int, double) - Constructor for class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
Constructs a GTestStatistics tuple with the supplied values.

H

hadamardProductInPlace(Tensor) - Method in interface org.tribuo.math.la.Tensor
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseMatrix
 
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseSparseMatrix
Only implemented for DenseMatrix.
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
 
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
 
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor
Updates this Tensor with the Hadamard product (i.e., a term by term multiply) of this and other.
handleChar() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Handle a character to add to the token buffer.
handleDoc(String) - Method in class org.tribuo.data.text.TextDataSource
A method that can be overridden to do different things to each document that we've read.
HARDMAX - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Hardmax(element in input, axis) = 1 if the element is the first maximum value along the specified axis, 0 otherwise.
hasAlgorithm() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
hasAlgorithm() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field represents a training algorithm step.
hasAlgorithm() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field represents a training algorithm step.
hasBegin() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 begin = 1;
hasBegin() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
optional int64 begin = 1;
hasBegin() - Method in interface ai.onnx.proto.OnnxMl.TensorProto.SegmentOrBuilder
optional int64 begin = 1;
hasDataLocation() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
hasDataLocation() - Method in class ai.onnx.proto.OnnxMl.TensorProto
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
hasDataLocation() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
hasDataType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The data type of the tensor.
hasDataType() - Method in class ai.onnx.proto.OnnxMl.TensorProto
The data type of the tensor.
hasDataType() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
The data type of the tensor.
hasDenotation() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
hasDenotation() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
hasDenotation() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
hasDenotation() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
hasDenotation() - Method in class ai.onnx.proto.OnnxMl.TypeProto
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
hasDenotation() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
hasDimParam() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
namespace Shape
hasDimParam() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
namespace Shape
hasDimParam() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
namespace Shape
hasDimValue() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
int64 dim_value = 1;
hasDimValue() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
int64 dim_value = 1;
hasDimValue() - Method in interface ai.onnx.proto.OnnxMl.TensorShapeProto.DimensionOrBuilder
int64 dim_value = 1;
hasDocString() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
A human-readable documentation for this attribute.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
A human-readable documentation for this attribute.
hasDocString() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
A human-readable documentation for this attribute.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A human-readable documentation for this graph.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.GraphProto
A human-readable documentation for this graph.
hasDocString() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
A human-readable documentation for this graph.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
A human-readable documentation for this model.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.ModelProto
A human-readable documentation for this model.
hasDocString() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
A human-readable documentation for this model.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
A human-readable documentation for this node.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.NodeProto
A human-readable documentation for this node.
hasDocString() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
A human-readable documentation for this node.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
A human-readable documentation for this tensor.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.TensorProto
A human-readable documentation for this tensor.
hasDocString() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
A human-readable documentation for this tensor.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
A human-readable documentation for this value.
hasDocString() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
A human-readable documentation for this value.
hasDocString() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
A human-readable documentation for this value.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Domain name of the model.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.ModelProto
Domain name of the model.
hasDomain() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
Domain name of the model.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The domain of the OperatorSet that specifies the operator named by op_type.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.NodeProto
The domain of the OperatorSet that specifies the operator named by op_type.
hasDomain() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
The domain of the OperatorSet that specifies the operator named by op_type.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The domain of the operator set being identified.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
The domain of the operator set being identified.
hasDomain() - Method in interface ai.onnx.proto.OnnxMl.OperatorSetIdProtoOrBuilder
The domain of the operator set being identified.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
When missing, the domain is the same as the model's.
hasDomain() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
When missing, the domain is the same as the model's.
hasDomain() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.OpaqueOrBuilder
When missing, the domain is the same as the model's.
hasElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
hasElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
The type and optional shape of each element of the sequence.
hasElemType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SequenceOrBuilder
The type and optional shape of each element of the sequence.
hasElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasElemType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SparseTensorOrBuilder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasElemType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasElemType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.TensorOrBuilder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasEnd() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 end = 2;
hasEnd() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
optional int64 end = 2;
hasEnd() - Method in interface ai.onnx.proto.OnnxMl.TensorProto.SegmentOrBuilder
optional int64 end = 2;
hasF() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
Exactly ONE of the following fields must be present for this version of the IR
hasF() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
Exactly ONE of the following fields must be present for this version of the IR
hasF() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
Exactly ONE of the following fields must be present for this version of the IR
hasG() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
hasG() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
graph
hasG() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
graph
hasGraph() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
hasGraph() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The parameterized graph that is evaluated to execute the model.
hasGraph() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The parameterized graph that is evaluated to execute the model.
hash(String) - Method in class org.tribuo.hash.HashCodeHasher
 
hash(String) - Method in class org.tribuo.hash.Hasher
Hashes the supplied input using the hashing function.
hash(String) - Method in class org.tribuo.hash.MessageDigestHasher
 
hash(String) - Method in class org.tribuo.hash.ModHashCodeHasher
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
hashCode() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
hashCode() - Method in class org.tribuo.anomaly.AnomalyFactory.AnomalyFactoryProvenance
 
hashCode() - Method in class org.tribuo.anomaly.Event
 
hashCode() - Method in class org.tribuo.classification.evaluation.LabelMetric
 
hashCode() - Method in class org.tribuo.classification.Label
 
hashCode() - Method in class org.tribuo.classification.LabelFactory
 
hashCode() - Method in class org.tribuo.classification.LabelFactory.LabelFactoryProvenance
 
hashCode() - Method in class org.tribuo.clustering.ClusterID
 
hashCode() - Method in class org.tribuo.clustering.ClusteringFactory.ClusteringFactoryProvenance
 
hashCode() - Method in class org.tribuo.clustering.ClusteringFactory
 
hashCode() - Method in class org.tribuo.common.tree.LeafNode
 
hashCode() - Method in class org.tribuo.common.tree.SplitNode
 
hashCode() - Method in class org.tribuo.data.csv.CSVDataSource.CSVDataSourceProvenance
 
hashCode() - Method in class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
Deprecated.
 
hashCode() - Method in class org.tribuo.data.sql.SQLDataSource.SQLDataSourceProvenance
 
hashCode() - Method in class org.tribuo.data.text.DirectoryFileSource.DirectoryFileSourceProvenance
 
hashCode() - Method in class org.tribuo.data.text.impl.SimpleStringDataSource.SimpleStringDataSourceProvenance
 
hashCode() - Method in class org.tribuo.data.text.impl.SimpleTextDataSource.SimpleTextDataSourceProvenance
 
hashCode() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
 
hashCode() - Method in class org.tribuo.dataset.MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance
 
hashCode() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
 
hashCode() - Method in class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance
 
hashCode() - Method in class org.tribuo.evaluation.DescriptiveStats
 
hashCode() - Method in class org.tribuo.evaluation.metrics.MetricTarget
 
hashCode() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
 
hashCode() - Method in class org.tribuo.Feature
 
hashCode() - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
 
hashCode() - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
 
hashCode() - Method in class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
 
hashCode() - Method in class org.tribuo.impl.ArrayExample
 
hashCode() - Method in class org.tribuo.impl.BinaryFeaturesExample
 
hashCode() - Method in class org.tribuo.impl.IndexedArrayExample
 
hashCode() - Method in class org.tribuo.impl.ListExample
 
hashCode() - Method in class org.tribuo.interop.ExternalTrainerProvenance
 
hashCode() - Method in class org.tribuo.interop.oci.OCILabelConverter
 
hashCode() - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
 
hashCode() - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
 
hashCode() - Method in class org.tribuo.json.JsonDataSource.JsonDataSourceProvenance
 
hashCode() - Method in class org.tribuo.math.la.DenseMatrix
 
hashCode() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
hashCode() - Method in class org.tribuo.math.la.DenseVector
 
hashCode() - Method in class org.tribuo.math.la.MatrixTuple
 
hashCode() - Method in class org.tribuo.math.la.SparseVector
 
hashCode() - Method in class org.tribuo.math.la.VectorTuple
 
hashCode() - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
 
hashCode() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
hashCode() - Method in class org.tribuo.multilabel.MultiLabel
 
hashCode() - Method in class org.tribuo.multilabel.MultiLabelFactory
 
hashCode() - Method in class org.tribuo.multilabel.MultiLabelFactory.MultiLabelFactoryProvenance
 
hashCode() - Method in class org.tribuo.multilabel.MultiLabelInfo
 
hashCode() - Method in class org.tribuo.provenance.DatasetProvenance
 
hashCode() - Method in class org.tribuo.provenance.EnsembleModelProvenance
 
hashCode() - Method in class org.tribuo.provenance.EvaluationProvenance
 
hashCode() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
 
hashCode() - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
 
hashCode() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
 
hashCode() - Method in class org.tribuo.provenance.ModelProvenance
 
hashCode() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
 
hashCode() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
 
hashCode() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
 
hashCode() - Method in class org.tribuo.regression.RegressionFactory
 
hashCode() - Method in class org.tribuo.regression.RegressionFactory.RegressionFactoryProvenance
 
hashCode() - Method in class org.tribuo.regression.Regressor.DimensionTuple
All regressors have a hashcode based on only the dimension names.
hashCode() - Method in class org.tribuo.regression.Regressor
Regressor's hashcode is based on the hash of the dimension names.
hashCode() - Method in record class org.tribuo.reproducibility.ReproUtil.FeatureDiff
Returns a hash code value for this object.
hashCode() - Method in record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Returns a hash code value for this object.
hashCode() - Method in record class org.tribuo.reproducibility.ReproUtil.OutputDiff
Returns a hash code value for this object.
hashCode() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
 
hashCode() - Method in class org.tribuo.SkeletalVariableInfo
 
hashCode() - Method in class org.tribuo.transform.TransformationMap.TransformationList
 
hashCode() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
 
hashCode() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
 
hashCode() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
 
hashCode() - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
 
hashCode() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
 
hashCode() - Method in class org.tribuo.util.infotheory.impl.CachedPair
Overridden hashcode.
hashCode() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
 
hashCode() - Method in class org.tribuo.util.infotheory.impl.Row
 
hashCode() - Method in class org.tribuo.util.infotheory.impl.WeightCountTuple
 
hashCode() - Method in class org.tribuo.util.IntDoublePair
 
hashCode() - Method in class org.tribuo.util.MeanVarianceAccumulator
 
HashCodeHasher - Class in org.tribuo.hash
Hashes names using String.hashCode().
HashCodeHasher(String) - Constructor for class org.tribuo.hash.HashCodeHasher
Constructs a HashCodeHasher using the specified salt value.
HashCodeHasher.HashCodeHasherProvenance - Class in org.tribuo.hash
Provenance for the HashCodeHasher.
HashCodeHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
Deserialization constructor.
hashDim - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Hashing dimension used for standard text format.
hashDim - Variable in class org.tribuo.data.DataOptions
Hashing dimension used for standard text format.
HashedFeatureMap - Class in org.tribuo.hash
A FeatureMap used by the HashingTrainer to provide feature name hashing and guarantee that the Model does not contain feature name information, but still works with unhashed features names.
Hasher - Class in org.tribuo.hash
An abstract base class for hash functions used to hash the names of features.
Hasher() - Constructor for class org.tribuo.hash.Hasher
 
hashFeatureMap(Dataset<T>, Hasher) - Static method in class org.tribuo.ImmutableDataset
Creates an immutable shallow copy of the supplied dataset, using the hasher to generate a HashedFeatureMap which transparently maps from the feature name to the hashed variant.
hashingOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for hashing trainers.
HashingOptions - Class in org.tribuo.hash
An Options implementation which provides CLI arguments for the model hashing functionality.
HashingOptions() - Constructor for class org.tribuo.hash.HashingOptions
 
HashingOptions.ModelHashingType - Enum Class in org.tribuo.hash
Supported types of hashes in CLI programs.
HashingSequenceTrainer<T extends Output<T>> - Class in org.tribuo.sequence
A SequenceTrainer that hashes all the feature names on the way in.
HashingSequenceTrainer(SequenceTrainer<T>, Hasher) - Constructor for class org.tribuo.sequence.HashingSequenceTrainer
Constructs a hashing sequence trainer using the supplied parameters.
HashingSequenceTrainer.HashingSequenceTrainerProvenance - Class in org.tribuo.sequence
Provenance for HashingSequenceTrainer.
HashingSequenceTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.sequence.HashingSequenceTrainer.HashingSequenceTrainerProvenance
Deserialization constructor.
HashingTrainer<T extends Output<T>> - Class in org.tribuo.hash
A Trainer which hashes the Dataset before the Model is produced.
HashingTrainer(Trainer<T>, Hasher) - Constructor for class org.tribuo.hash.HashingTrainer
Constructs a hashing trainer using the supplied parameters.
hashType - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
The hash type to use.
hasI() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
int
hasI() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
int
hasI() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
int
hasIndices() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
hasIndices() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The indices of the non-default values, which may be stored in one of two formats.
hasIndices() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The indices of the non-default values, which may be stored in one of two formats.
hasInitialization() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
hasInitialization() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
This field describes a graph to compute the initial tensors upon starting the training process.
hasInitialization() - Method in interface ai.onnx.proto.OnnxMl.TrainingInfoProtoOrBuilder
This field describes a graph to compute the initial tensors upon starting the training process.
hasIrVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the IR this model targets.
hasIrVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The version of the IR this model targets.
hasIrVersion() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The version of the IR this model targets.
hasKey() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string key = 1;
hasKey() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
optional string key = 1;
hasKey() - Method in interface ai.onnx.proto.OnnxMl.StringStringEntryProtoOrBuilder
optional string key = 1;
hasKeyType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasKeyType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasKeyType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.MapOrBuilder
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
hasMapType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
hasMapType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a map.
hasMapType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a map.
hasModelVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the graph encoded.
hasModelVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The version of the graph encoded.
hasModelVersion() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The version of the graph encoded.
hasName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The name field MUST be present for this version of the IR.
hasName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
The name field MUST be present for this version of the IR.
hasName() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
The name field MUST be present for this version of the IR.
hasName() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The name of the graph.
hasName() - Method in class ai.onnx.proto.OnnxMl.GraphProto
The name of the graph.
hasName() - Method in interface ai.onnx.proto.OnnxMl.GraphProtoOrBuilder
The name of the graph.
hasName() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
An optional identifier for this node in a graph.
hasName() - Method in class ai.onnx.proto.OnnxMl.NodeProto
An optional identifier for this node in a graph.
hasName() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
An optional identifier for this node in a graph.
hasName() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Optionally, a name for the tensor.
hasName() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Optionally, a name for the tensor.
hasName() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Optionally, a name for the tensor.
hasName() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
The name is optional but significant when provided.
hasName() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
The name is optional but significant when provided.
hasName() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.OpaqueOrBuilder
The name is optional but significant when provided.
hasName() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR.
hasName() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
This field MUST be present in this version of the IR.
hasName() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
This field MUST be present in this version of the IR.
hasNext() - Method in class org.tribuo.data.columnar.ColumnarIterator
 
hasOpaqueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
hasOpaqueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
.onnx.TypeProto.Opaque opaque_type = 7;
hasOpaqueType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
.onnx.TypeProto.Opaque opaque_type = 7;
hasOpType() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The symbolic identifier of the Operator to execute.
hasOpType() - Method in class ai.onnx.proto.OnnxMl.NodeProto
The symbolic identifier of the Operator to execute.
hasOpType() - Method in interface ai.onnx.proto.OnnxMl.NodeProtoOrBuilder
The symbolic identifier of the Operator to execute.
hasProbabilities() - Method in class org.tribuo.Prediction
Are the scores probabilities?
hasProducerName() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The name of the framework or tool used to generate this model.
hasProducerName() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The name of the framework or tool used to generate this model.
hasProducerName() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The name of the framework or tool used to generate this model.
hasProducerVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the framework or tool used to generate this model.
hasProducerVersion() - Method in class ai.onnx.proto.OnnxMl.ModelProto
The version of the framework or tool used to generate this model.
hasProducerVersion() - Method in interface ai.onnx.proto.OnnxMl.ModelProtoOrBuilder
The version of the framework or tool used to generate this model.
hasRawData() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Serializations can either use one of the fields above, or use this raw bytes field.
hasRawData() - Method in class ai.onnx.proto.OnnxMl.TensorProto
Serializations can either use one of the fields above, or use this raw bytes field.
hasRawData() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
Serializations can either use one of the fields above, or use this raw bytes field.
hasRefAttrName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
hasRefAttrName() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
hasRefAttrName() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
hasS() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
UTF-8 string
hasS() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
UTF-8 string
hasS() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
UTF-8 string
hasSegment() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
hasSegment() - Method in class ai.onnx.proto.OnnxMl.TensorProto
optional .onnx.TensorProto.Segment segment = 3;
hasSegment() - Method in interface ai.onnx.proto.OnnxMl.TensorProtoOrBuilder
optional .onnx.TensorProto.Segment segment = 3;
hasSequenceType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
hasSequenceType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a sequence.
hasSequenceType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a sequence.
hasShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
hasShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
optional .onnx.TensorShapeProto shape = 2;
hasShape() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.SparseTensorOrBuilder
optional .onnx.TensorShapeProto shape = 2;
hasShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
hasShape() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
optional .onnx.TensorShapeProto shape = 2;
hasShape() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.TensorOrBuilder
optional .onnx.TensorShapeProto shape = 2;
hasSparseTensor() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
hasSparseTensor() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
sparse tensor value
hasSparseTensor() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
sparse tensor value
hasSparseTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
hasSparseTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
hasSparseTensorType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
hasT() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
hasT() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
tensor value
hasT() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
tensor value
hasTensorName() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
optional string tensor_name = 1;
hasTensorName() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
optional string tensor_name = 1;
hasTensorName() - Method in interface ai.onnx.proto.OnnxMl.TensorAnnotationOrBuilder
optional string tensor_name = 1;
hasTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
hasTensorType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
The type of a tensor.
hasTensorType() - Method in interface ai.onnx.proto.OnnxMl.TypeProtoOrBuilder
The type of a tensor.
hasType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The type field MUST be present for this version of the IR.
hasType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
The type field MUST be present for this version of the IR.
hasType() - Method in interface ai.onnx.proto.OnnxMl.AttributeProtoOrBuilder
The type field MUST be present for this version of the IR.
hasType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
hasType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
hasType() - Method in interface ai.onnx.proto.OnnxMl.ValueInfoProtoOrBuilder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
hasValue() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string value = 2;
hasValue() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
optional string value = 2;
hasValue() - Method in interface ai.onnx.proto.OnnxMl.StringStringEntryProtoOrBuilder
optional string value = 2;
hasValues() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
hasValues() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
The sequence of non-default values are encoded as a tensor of shape [NNZ].
hasValues() - Method in interface ai.onnx.proto.OnnxMl.SparseTensorProtoOrBuilder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
hasValueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
hasValueType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
This field MUST be present for this version of the IR.
hasValueType() - Method in interface ai.onnx.proto.OnnxMl.TypeProto.MapOrBuilder
This field MUST be present for this version of the IR.
hasVersion() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The version of the operator set being identified.
hasVersion() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
The version of the operator set being identified.
hasVersion() - Method in interface ai.onnx.proto.OnnxMl.OperatorSetIdProtoOrBuilder
The version of the operator set being identified.
HC - Enum constant in enum class org.tribuo.hash.HashingOptions.ModelHashingType
Uses the String hash code.
HdbscanCLIOptions() - Constructor for class org.tribuo.clustering.hdbscan.TrainTest.HdbscanCLIOptions
 
HdbscanModel - Class in org.tribuo.clustering.hdbscan
A trained HDBSCAN* model which provides the cluster assignment labels and outlier scores for every data point.
hdbscanOptions - Variable in class org.tribuo.clustering.hdbscan.TrainTest.HdbscanCLIOptions
The HDBSCAN options
HdbscanOptions - Class in org.tribuo.clustering.hdbscan
OLCUT Options for the HDBSCAN* implementation.
HdbscanOptions() - Constructor for class org.tribuo.clustering.hdbscan.HdbscanOptions
 
HdbscanTrainer - Class in org.tribuo.clustering.hdbscan
An HDBSCAN* trainer which generates a hierarchical, density-based clustering representation of the supplied data.
HdbscanTrainer(int) - Constructor for class org.tribuo.clustering.hdbscan.HdbscanTrainer
Constructs an HDBSCAN* trainer with only the minClusterSize parameter.
HdbscanTrainer(int, HdbscanTrainer.Distance, int, int) - Constructor for class org.tribuo.clustering.hdbscan.HdbscanTrainer
Constructs an HDBSCAN* trainer using the supplied parameters.
HdbscanTrainer.Distance - Enum Class in org.tribuo.clustering.hdbscan
Available distance functions.
HeapMerger - Class in org.tribuo.math.util
Merges each SparseVector separately using a PriorityQueue as a heap.
HeapMerger() - Constructor for class org.tribuo.math.util.HeapMerger
 
Hinge - Class in org.tribuo.classification.sgd.objectives
Hinge loss, scores the correct value margin and any incorrect predictions -margin.
Hinge - Class in org.tribuo.multilabel.sgd.objectives
Hinge loss, scores the correct value margin and any incorrect predictions -margin.
Hinge() - Constructor for class org.tribuo.classification.sgd.objectives.Hinge
Construct a hinge objective with a margin of 1.0.
Hinge() - Constructor for class org.tribuo.multilabel.sgd.objectives.Hinge
Construct a hinge objective with a margin of 1.0.
Hinge(double) - Constructor for class org.tribuo.classification.sgd.objectives.Hinge
Construct a hinge objective with the supplied margin.
Hinge(double) - Constructor for class org.tribuo.multilabel.sgd.objectives.Hinge
Construct a hinge objective with the supplied margin.
HINGE - Enum constant in enum class org.tribuo.classification.sgd.fm.FMClassificationOptions.LossEnum
Hinge loss (like an SVM).
HINGE - Enum constant in enum class org.tribuo.classification.sgd.linear.LinearSGDOptions.LossEnum
Hinge loss.
HINGE - Enum constant in enum class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions.LossEnum
Hinge loss.
HINGE - Enum constant in enum class org.tribuo.multilabel.sgd.linear.LinearSGDOptions.LossEnum
Hinge loss.
HIST - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
Faster histogram optimized approximate algorithm.
HTMLOutput - Class in org.tribuo.util
Utilities for nice HTML output that can be put in wikis and such.
Huber - Class in org.tribuo.regression.sgd.objectives
Huber loss, i.e., a mixture of l2 and l1 losses.
Huber() - Constructor for class org.tribuo.regression.sgd.objectives.Huber
Huber Loss using the default cost Huber.DEFAULT_COST.
Huber(double) - Constructor for class org.tribuo.regression.sgd.objectives.Huber
Huber loss using the supplied cost.
HUBER - Enum constant in enum class org.tribuo.regression.sgd.fm.TrainTest.LossEnum
Uses Huber loss.
HUBER - Enum constant in enum class org.tribuo.regression.sgd.TrainTest.LossEnum
Uses Huber loss.

I

i - Variable in class org.tribuo.math.la.MatrixTuple
The i index.
I_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
id - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple
The feature id number.
IDENTITY - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Identity.
IdentityExtractor - Class in org.tribuo.data.columnar.extractors
Extracts the field value and emits it as a String.
IdentityExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.IdentityExtractor
Extracts the String value from the supplied field.
IdentityExtractor(String, String) - Constructor for class org.tribuo.data.columnar.extractors.IdentityExtractor
Extracts the String value from the supplied field.
IdentityProcessor - Class in org.tribuo.data.columnar.processors.field
A FieldProcessor which converts the field name and value into a feature with a value of IdentityProcessor.FEATURE_VALUE.
IdentityProcessor(String) - Constructor for class org.tribuo.data.columnar.processors.field.IdentityProcessor
Constructs a field processor which emits a single feature with a specific value and uses the field name and field value as the feature name.
IDFTransformation - Class in org.tribuo.transform.transformations
A feature transformation that computes the IDF for features and then transforms them with a TF-IDF weighting.
IDFTransformation() - Constructor for class org.tribuo.transform.transformations.IDFTransformation
Constructs an IDFTransformation.
IDFTransformation.IDFTransformationProvenance - Class in org.tribuo.transform.transformations
Provenance for IDFTransformation.
IDFTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.IDFTransformation.IDFTransformationProvenance
Deserialization constructor.
idIterator() - Method in class org.tribuo.impl.IndexedArrayExample
Iterator over the feature ids and values.
idMap - Variable in class org.tribuo.ImmutableFeatureMap
The map from id numbers to the feature infos.
IDXDataSource<T extends Output<T>> - Class in org.tribuo.datasource
A DataSource which can read IDX formatted data (i.e., MNIST).
IDXDataSource(Path, Path, OutputFactory<T>) - Constructor for class org.tribuo.datasource.IDXDataSource
Constructs an IDXDataSource from the supplied paths.
IDXDataSource.IDXData - Class in org.tribuo.datasource
Java side representation for an IDX file.
IDXDataSource.IDXDataSourceProvenance - Class in org.tribuo.datasource
Provenance class for IDXDataSource.
IDXDataSource.IDXType - Enum Class in org.tribuo.datasource
The possible IDX input formats.
IDXDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
Deserialization constructor.
IMAGE - Enum constant in enum class org.tribuo.interop.tensorflow.TrainTest.InputType
Image feature extractor, requires the image format option be set.
IMAGE_CLASSIFICATION - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Image classification, no strict Tribuo mapping.
ImageConverter - Class in org.tribuo.interop.tensorflow
Image converter.
ImageConverter(String, int, int, int) - Constructor for class org.tribuo.interop.tensorflow.ImageConverter
Builds an image converter for images of the supplied size.
imageFormat - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Image format, in [W,H,C].
ImageTransformer - Class in org.tribuo.interop.onnx
Image transformer.
ImageTransformer(int, int, int) - Constructor for class org.tribuo.interop.onnx.ImageTransformer
Constructs an image transformer with the specified parameters.
ImmutableAnomalyInfo - Class in org.tribuo.anomaly
An ImmutableOutputInfo object for Events.
ImmutableClusteringInfo - Class in org.tribuo.clustering
An ImmutableOutputInfo object for ClusterIDs.
ImmutableClusteringInfo(Map<Integer, MutableLong>) - Constructor for class org.tribuo.clustering.ImmutableClusteringInfo
Constructs an immutable clustering info from the supplied cluster counts.
ImmutableClusteringInfo(ClusteringInfo) - Constructor for class org.tribuo.clustering.ImmutableClusteringInfo
Copies the supplied clustering info, generating id numbers.
ImmutableDataset<T extends Output<T>> - Class in org.tribuo
This is a Dataset which has an ImmutableFeatureMap to store the feature information.
ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
Creates a dataset from a data source.
ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
Creates a dataset from a data source.
ImmutableDataset(DataSource<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
Creates a dataset from a data source.
ImmutableDataset(DataSource<T>, Model<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
Creates a dataset from a data source.
ImmutableDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.ImmutableDataset
If you call this it's your job to setup outputMap, featureIDMap and fill it with examples.
ImmutableDataset(DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.ImmutableDataset
This is dangerous, and should not be used unless you've overridden everything in ImmutableDataset.
ImmutableFeatureMap - Class in org.tribuo
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
ImmutableFeatureMap() - Constructor for class org.tribuo.ImmutableFeatureMap
Constructs a new empty immutable feature map.
ImmutableFeatureMap(List<VariableInfo>) - Constructor for class org.tribuo.ImmutableFeatureMap
Constructs a new immutable feature map copying the supplied variable infos and generating appropriate ID numbers.
ImmutableFeatureMap(FeatureMap) - Constructor for class org.tribuo.ImmutableFeatureMap
Constructs a new immutable version which is a deep copy of the supplied feature map, generating new ID numbers.
ImmutableLabelInfo - Class in org.tribuo.classification
An ImmutableOutputInfo object for Labels.
ImmutableMultiLabelInfo - Class in org.tribuo.multilabel
An ImmutableOutputInfo for working with MultiLabel tasks.
ImmutableOutputInfo<T extends Output<T>> - Interface in org.tribuo
An OutputInfo that is fixed, and contains an id number for each valid output.
ImmutableRegressionInfo - Class in org.tribuo.regression
ImmutableSequenceDataset<T extends Output<T>> - Class in org.tribuo.sequence
This is a SequenceDataset which has an ImmutableFeatureMap to store the feature information.
ImmutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, FeatureMap, OutputInfo<T>, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
Creates a dataset from a data source.
ImmutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
Creates a dataset from a data source.
ImmutableSequenceDataset(DataProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
This is dangerous, and should not be used unless you've overridden everything in ImmutableSequenceDataset.
ImmutableSequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
If you call this it's your job to setup outputIDInfo and featureIDMap.
ImmutableSequenceDataset(SequenceDataSource<T>, FeatureMap, OutputInfo<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
Creates a dataset from a data source, using the specified output and feature domains.
ImmutableSequenceDataset(SequenceDataSource<T>, SequenceModel<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
Creates a dataset from a data source, taking the output and feature domains from the supplied model.
impurity - Variable in class org.tribuo.regression.rtree.impurity.RegressorImpurity.ImpurityTuple
The impurity value.
impurity(double[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Calculates the impurity assuming the inputs are counts.
impurity(float[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Calculates the impurity assuming the input are fractional counts.
impurity(float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
 
impurity(float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
 
impurity(float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the impurity based on the supplied weights and targets.
impurity(int[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Calculates the impurity assuming the input are counts.
impurity(int[], float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the weighted impurity of the targets specified in the indices array.
impurity(int[], int, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the weighted impurity of the targets specified in the indices array.
impurity(List<int[]>, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the weighted impurity of the targets specified in all the indices arrays.
impurity(Map<String, Double>) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Takes a Map for weighted counts.
impurity(IntArrayContainer, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the weighted impurity of the targets specified in the indices container.
impurityNormed(double[]) - Method in class org.tribuo.classification.dtree.impurity.Entropy
 
impurityNormed(double[]) - Method in class org.tribuo.classification.dtree.impurity.GiniIndex
 
impurityNormed(double[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Calculates the impurity, assuming it's input is a normalized probability distribution.
impurityScore - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
impurityTuple(int[], int, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
 
impurityTuple(int[], int, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
 
impurityTuple(int[], int, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the weighted impurity of the targets specified in the indices array.
impurityTuple(List<int[]>, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
 
impurityTuple(List<int[]>, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
 
impurityTuple(List<int[]>, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the weighted impurity of the targets specified in all the indices arrays.
ImpurityTuple(float, float) - Constructor for class org.tribuo.regression.rtree.impurity.RegressorImpurity.ImpurityTuple
Construct an impurity tuple.
impurityType - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Impurity measure to use.
impurityWeighted(double[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Calculates the impurity assuming the inputs are weighted counts normalizing by their sum.
impurityWeighted(float[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Calculates the impurity by assuming the input are weighted counts and converting them into a probability distribution by dividing by their sum.
incr - Variable in class org.tribuo.util.tokens.universal.Range
The value to increment by.
INCREMENT_INVOCATION_COUNT - Static variable in interface org.tribuo.Trainer
When training a model, passing this value will inform the trainer to simply increment the invocation count rather than set a new one
incrementalTrain(Dataset<T>, U) - Method in interface org.tribuo.IncrementalTrainer
Incrementally trains the supplied model with the new data.
IncrementalTrainer<T extends Output<T>,U extends Model<T>> - Interface in org.tribuo
An interface for incremental training of Models.
IndependentMultiLabelModel - Class in org.tribuo.multilabel.baseline
A Model which wraps n binary models, where n is the size of the MultiLabel domain.
IndependentMultiLabelTrainer - Class in org.tribuo.multilabel.baseline
Trains n independent binary Models, each of which predicts a single Label.
IndependentMultiLabelTrainer(Trainer<Label>) - Constructor for class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
Constructs an independent multi-label trainer wrapped around the supplied classification trainer.
IndependentRegressionTreeModel - Class in org.tribuo.regression.rtree
A Model wrapped around a list of decision tree root Nodes used to generate independent predictions for each dimension in a regression.
IndependentSequenceModel<T extends Output<T>> - Class in org.tribuo.sequence
A SequenceModel which independently predicts each element of the sequence.
IndependentSequenceTrainer<T extends Output<T>> - Class in org.tribuo.sequence
Trains a sequence model by training a regular model to independently predict every example in each sequence.
IndependentSequenceTrainer(Trainer<T>) - Constructor for class org.tribuo.sequence.IndependentSequenceTrainer
Builds a sequence trainer which uses a Trainer to independently predict each sequence element.
index - Variable in class org.tribuo.math.la.VectorTuple
The current index.
index - Variable in class org.tribuo.util.IntDoublePair
The key.
IndexedArrayExample<T extends Output<T>> - Class in org.tribuo.impl
A version of ArrayExample which also has the id numbers.
IndexedArrayExample(Example<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample
This constructor removes unknown features.
IndexedArrayExample(IndexedArrayExample<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample
Copy constructor.
IndexedArrayExample.FeatureTuple - Class in org.tribuo.impl
A tuple of the feature name, id and value.
IndexExtractor - Class in org.tribuo.data.columnar.extractors
An Extractor with special casing for loading the index from a Row.
IndexExtractor() - Constructor for class org.tribuo.data.columnar.extractors.IndexExtractor
Extracts the index writing to the default metadata field name Example.NAME.
IndexExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.IndexExtractor
Extracts the index, writing to the supplied metadata field name.
indexOf(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
 
indexOfMax() - Method in class org.tribuo.math.la.DenseVector
 
indexOfMax() - Method in interface org.tribuo.math.la.SGDVector
Returns the index of the maximum value.
indexOfMax() - Method in class org.tribuo.math.la.SparseVector
 
indexOfMax() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
indices - Variable in class org.tribuo.Dataset
The indices of the shuffled order.
indices - Variable in class org.tribuo.math.la.SparseVector
 
indices() - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
Gets the indices where this feature value occurs.
INDICES_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
INFIX - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
Some tokenizers produce "sub-word" tokens.
INFO - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
Tree building info is logged as well as warnings.
InformationTheory - Class in org.tribuo.util.infotheory
A class of (discrete) information theoretic functions.
InformationTheory.GTestStatistics - Class in org.tribuo.util.infotheory
An immutable named tuple containing the statistics from a G test.
InformationTheoryDemo - Class in org.tribuo.util.infotheory.example
Demo showing how to calculate various mutual informations and entropies.
InformationTheoryDemo() - Constructor for class org.tribuo.util.infotheory.example.InformationTheoryDemo
 
InformationTheoryDemo.DemoOptions - Class in org.tribuo.util.infotheory.example
Command line options.
InformationTheoryDemo.DistributionType - Enum Class in org.tribuo.util.infotheory.example
Type of data distribution.
initialisation - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
Initialisation function in K-Means.
initialisation - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
Type of initialisation to use for centroids.
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaDelta
 
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaGrad
 
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaGradRDA
 
initialise(Parameters) - Method in class org.tribuo.math.optimisers.Adam
 
initialise(Parameters) - Method in class org.tribuo.math.optimisers.ParameterAveraging
 
initialise(Parameters) - Method in class org.tribuo.math.optimisers.Pegasos
 
initialise(Parameters) - Method in class org.tribuo.math.optimisers.RMSProp
 
initialise(Parameters) - Method in class org.tribuo.math.optimisers.SGD
 
initialise(Parameters) - Method in interface org.tribuo.math.StochasticGradientOptimiser
Initialises the gradient optimiser.
INITIALIZATION_BINDING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
INITIALIZATION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
initialize() - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Initializes the model.
INITIALIZER_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
initialLearningRate - Variable in class org.tribuo.math.optimisers.SGD
 
innerGetExcuse(Example<Event>, double[][]) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyModel
The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
innerGetExcuse(Example<Label>, double[][]) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel
The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
innerGetExcuse(Example<Regressor>, double[][]) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
innerGetExcuse(Example<T>, double[][]) - Method in class org.tribuo.common.liblinear.LibLinearModel
The call to getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
innerModel - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.common.nearest.KNNModel
Uses the model to predict the output for multiple examples.
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.interop.ExternalModel
 
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
 
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.Model
Called by the base implementations of Model.predict(Iterable) and Model.predict(Dataset).
INNERTHREADPOOL - Enum constant in enum class org.tribuo.common.nearest.KNNModel.Backend
Uses a thread pool at the inner level (i.e., the whole thread pool works on each prediction).
innerTrainer - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
innerTrainer - Variable in class org.tribuo.ensemble.BaggingTrainer
 
inPlaceAdd(double[], double[]) - Static method in class org.tribuo.util.Util
Adds update to input in place.
inPlaceAdd(float[], float[]) - Static method in class org.tribuo.util.Util
Adds update to input in place.
inplaceNormalizeToDistribution(double[]) - Static method in class org.tribuo.util.Util
Normalizes the input array in place.
inplaceNormalizeToDistribution(float[]) - Static method in class org.tribuo.util.Util
Normalizes the input array in place.
inPlaceSubtract(double[], double[]) - Static method in class org.tribuo.util.Util
Subtracts update from input in place.
inPlaceSubtract(float[], float[]) - Static method in class org.tribuo.util.Util
Subtracts update from input in place.
INPUT_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
INPUT_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
 
INPUT_IDS - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Input name for the token ids.
inputFile - Variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.BERTFeatureExtractorOptions
Input file to read, one doc per line
inputFormat - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Loads the data using the specified format.
inputFormat - Variable in class org.tribuo.data.DataOptions
Loads the data using the specified format.
inputModel - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
The model to load.
inputName - Variable in class org.tribuo.interop.tensorflow.example.GraphDefTuple
Name of the input operation.
inputName - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Name of the input placeholder.
inputNamesSet() - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
inputNamesSet() - Method in interface org.tribuo.interop.tensorflow.FeatureConverter
Gets a view of the names of the inputs this converter produces.
inputNamesSet() - Method in class org.tribuo.interop.tensorflow.ImageConverter
 
inputNamesSet() - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceFeatureConverter
Gets a view of the names of the inputs this converter produces.
inputPath - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
SQL File to run as a query, defaults to stdin
inputPath - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
Input data file in standard text format.
inputType - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Input type.
INSTANCE - Enum constant in enum class org.tribuo.json.StripProvenance.ProvenanceTypes
Select any instance provenance from the specific training run that created this model.
INSTANCE_VALUES - Static variable in class org.tribuo.provenance.ModelProvenance
 
instanceCount - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Number of model instances to deploy.
instanceCount - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelDeploymentConfig
The number of instances to create.
instanceProvenance - Variable in class org.tribuo.provenance.ModelProvenance
 
instanceShape - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
OCI shape to run the model on.
INT - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
INT = 2;
INT - Enum constant in enum class org.tribuo.datasource.IDXDataSource.IDXType
A 32-bit integer.
INT_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
INT = 2;
INT16 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int16_t
INT16_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int16_t
INT32 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int32_t
INT32_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
INT32_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int32_t
INT64 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int64_t
INT64_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
INT64_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int64_t
INT8 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int8_t
INT8_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
int8_t
IntArrayContainer - Class in org.tribuo.common.tree.impl
An array container which maintains the array and the size.
IntArrayContainer(int) - Constructor for class org.tribuo.common.tree.impl.IntArrayContainer
Constructs a new int array container with the specified initial backing array size.
IntDoublePair - Class in org.tribuo.util
A Pair of a primitive int and a primitive double.
IntDoublePair(int, double) - Constructor for class org.tribuo.util.IntDoublePair
Constructs a tuple out of an int and a double.
INTEGER - Enum constant in enum class org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Ordered integral feature values (e.g.
InterlockingCrescentsDataSource - Class in org.tribuo.classification.example
A data source of two interleaved half circles.
InterlockingCrescentsDataSource(int) - Constructor for class org.tribuo.classification.example.InterlockingCrescentsDataSource
Constructs an interlocking crescents data source.
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
internalGetFieldAccessorTable() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
internalGetValueMap() - Static method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
 
internalGetValueMap() - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
 
internalGetValueMap() - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
 
internalGetValueMap() - Static method in enum class ai.onnx.proto.OnnxMl.Version
 
internalProvenances() - Method in class org.tribuo.provenance.EnsembleModelProvenance
 
internalProvenances() - Method in class org.tribuo.provenance.ModelProvenance
Returns a list of all the provenances in this model provenance so subclasses can append to the list.
intersectAndAddInPlace(Tensor) - Method in interface org.tribuo.math.la.Tensor
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseMatrix
 
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseSparseMatrix
Only implemented for DenseMatrix.
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
 
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
 
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor
Updates this Tensor by adding all the values from the intersection with other.
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
intersection(SparseVector) - Method in class org.tribuo.math.la.SparseVector
Generates an array of the indices that are active in both this vector and other
intersectionSize(MultiLabel, MultiLabel) - Static method in class org.tribuo.multilabel.MultiLabel
The number of labels present in both MultiLabels.
IntExtractor - Class in org.tribuo.data.columnar.extractors
Extracts the field value and converts it to a int.
IntExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.IntExtractor
Extracts a int value from the supplied field name.
IntExtractor(String, String) - Constructor for class org.tribuo.data.columnar.extractors.IntExtractor
Extracts a int value from the supplied field name.
INTS - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
INTS = 7;
INTS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
INTS_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
INTS = 7;
invalidMultiDimSparseExample() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator
Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invertData(Dataset<Regressor>) - Static method in class org.tribuo.regression.rtree.impl.RegressorTrainingNode
Inverts a training dataset from row major to column major.
InvertedFeature - Class in org.tribuo.regression.rtree.impl
Internal datastructure for implementing a decision tree.
InvertedFeature(double, int) - Constructor for class org.tribuo.regression.rtree.impl.InvertedFeature
Constructs an inverted feature for the specifed value which occurs at a single index.
InvertedFeature(double, int[]) - Constructor for class org.tribuo.regression.rtree.impl.InvertedFeature
Constructs an inverted feature for the specified value which occurs at the specified indices.
IR_VERSION - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 7 published on <TBD> - Add support to allow function body graph to rely on multiple external opreator sets.
IR_VERSION_2017_10_10 - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
The version field is always serialized and we will use it to store the version that the graph is generated from.
IR_VERSION_2017_10_10_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
The version field is always serialized and we will use it to store the version that the graph is generated from.
IR_VERSION_2017_10_30 - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
IR_VERSION 2 published on Oct 30, 2017 - Added type discriminator to AttributeProto to support proto3 users
IR_VERSION_2017_10_30_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
IR_VERSION 2 published on Oct 30, 2017 - Added type discriminator to AttributeProto to support proto3 users
IR_VERSION_2017_11_3 - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 3 published on Nov 3, 2017 - For operator versioning: - Added new message OperatorSetIdProto - Added opset_import in ModelProto - For vendor extensions, added domain in NodeProto
IR_VERSION_2017_11_3_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 3 published on Nov 3, 2017 - For operator versioning: - Added new message OperatorSetIdProto - Added opset_import in ModelProto - For vendor extensions, added domain in NodeProto
IR_VERSION_2019_1_22 - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 4 published on Jan 22, 2019 - Relax constraint that initializers should be a subset of graph inputs - Add type BFLOAT16
IR_VERSION_2019_1_22_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 4 published on Jan 22, 2019 - Relax constraint that initializers should be a subset of graph inputs - Add type BFLOAT16
IR_VERSION_2019_3_18 - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 5 published on March 18, 2019 - Add message TensorAnnotation.
IR_VERSION_2019_3_18_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 5 published on March 18, 2019 - Add message TensorAnnotation.
IR_VERSION_2019_9_19 - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 6 published on Sep 19, 2019 - Add support for sparse tensor constants stored in model.
IR_VERSION_2019_9_19_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 6 published on Sep 19, 2019 - Add support for sparse tensor constants stored in model.
IR_VERSION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
IR_VERSION_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
IR VERSION 7 published on <TBD> - Add support to allow function body graph to rely on multiple external opreator sets.
IS_SEQUENCE - Static variable in interface org.tribuo.provenance.TrainerProvenance
The name of the provenance field recording if this is a sequence trainer.
IS_SNAPSHOT - Static variable in class org.tribuo.Tribuo
Is this a snapshot build.
isAnomaly() - Method in class org.tribuo.anomaly.liblinear.LinearAnomalyType
 
isAnomaly() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
 
isAnomaly() - Method in class org.tribuo.classification.liblinear.LinearClassificationType
 
isAnomaly() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
 
isAnomaly() - Method in interface org.tribuo.common.liblinear.LibLinearType
Is this class an anomaly detection algorithm?
isAnomaly() - Method in interface org.tribuo.common.libsvm.SVMType
Is this an anomaly detection algorithm.
isAnomaly() - Method in class org.tribuo.regression.liblinear.LinearRegressionType
 
isAnomaly() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
 
isBinary(Feature) - Static method in class org.tribuo.impl.BinaryFeaturesExample
Is the supplied feature binary (i.e., does it have a value of 1.0)?
isChinese(int) - Static method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Determines if the provided codepoint is a Chinese character or not.
isClassification() - Method in class org.tribuo.anomaly.liblinear.LinearAnomalyType
 
isClassification() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
 
isClassification() - Method in class org.tribuo.classification.liblinear.LinearClassificationType
 
isClassification() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
 
isClassification() - Method in interface org.tribuo.common.liblinear.LibLinearType
Is this class a Classification algorithm?
isClassification() - Method in interface org.tribuo.common.libsvm.SVMType
Is this a classification algorithm.
isClassification() - Method in class org.tribuo.regression.liblinear.LinearRegressionType
 
isClassification() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
 
isConfigured() - Method in class org.tribuo.data.columnar.RowProcessor
Returns true if the regexes have been expanded into field processors.
isControl(int) - Static method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Determines if the provided codepoint is a control character or not.
isDense() - Method in class org.tribuo.MutableDataset
Is the dataset dense (i.e., do all features in the domain have a value in each example).
isDense() - Method in class org.tribuo.provenance.DatasetProvenance
Is the Dataset dense?
isDense() - Method in class org.tribuo.sequence.MutableSequenceDataset
Is the dataset dense (i.e., do all features in the domain have a value in each example).
isDense(FeatureMap) - Method in class org.tribuo.Example
Is this example dense wrt the supplied feature map.
isDense(FeatureMap) - Method in class org.tribuo.impl.ArrayExample
 
isDense(FeatureMap) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
isDense(FeatureMap) - Method in class org.tribuo.impl.ListExample
 
isDense(FeatureMap) - Method in class org.tribuo.sequence.SequenceExample
Is this sequence example dense wrt the supplied feature map.
isDigit(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer
A quick check for whether a character is a digit.
isEmpty() - Method in class org.tribuo.util.infotheory.impl.RowList
 
isGenerateNgrams() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Does this tokenizer generate ngrams?
isGenerateUnigrams() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Does this tokenizer generate unigrams?
isInitialized() - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
isInitialized() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
isInitialized() - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Is this model initialized?
isLeaf() - Method in class org.tribuo.common.tree.AbstractTrainingNode
 
isLeaf() - Method in class org.tribuo.common.tree.LeafNode
 
isLeaf() - Method in interface org.tribuo.common.tree.Node
Is it a leaf node?
isLeaf() - Method in class org.tribuo.common.tree.SplitNode
 
isLetterOrDigit(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer
A quick check for whether a character should be kept in a word or should be removed from the word if it occurs at one of the ends.
isMandatory() - Method in class org.tribuo.util.onnx.ONNXAttribute
Is this attribute mandatory?
isNgram(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer
A quick check for a character in a language that may not separate words with whitespace (includes Arabic, CJK, and Thai).
isNu() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
 
isNu() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
 
isNu() - Method in interface org.tribuo.common.libsvm.SVMType
Is this a nu-SVM.
isNu() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
 
isProbabilistic() - Method in interface org.tribuo.classification.sgd.LabelObjective
Does the objective function score probabilities or not?
isProbabilistic() - Method in class org.tribuo.classification.sgd.objectives.Hinge
Returns false.
isProbabilistic() - Method in class org.tribuo.classification.sgd.objectives.LogMulticlass
Returns true.
isProbabilistic() - Method in interface org.tribuo.multilabel.sgd.MultiLabelObjective
Does the objective function score probabilities or not?
isProbabilistic() - Method in class org.tribuo.multilabel.sgd.objectives.BinaryCrossEntropy
Returns true.
isProbabilistic() - Method in class org.tribuo.multilabel.sgd.objectives.Hinge
Returns false.
isPunctuation(int) - Static method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Determines if the input code point should be considered a character that is punctuation.
isRegression() - Method in class org.tribuo.anomaly.liblinear.LinearAnomalyType
 
isRegression() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
 
isRegression() - Method in class org.tribuo.classification.liblinear.LinearClassificationType
 
isRegression() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
 
isRegression() - Method in interface org.tribuo.common.liblinear.LibLinearType
Is this class a Regression algorithm?
isRegression() - Method in interface org.tribuo.common.libsvm.SVMType
Is this a regression algorithm.
isRegression() - Method in class org.tribuo.regression.liblinear.LinearRegressionType
 
isRegression() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
 
isSampled() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
Is this view from a bootstrap sample.
isSequence() - Method in class org.tribuo.provenance.DatasetProvenance
Is it a sequence dataset?
isSequence() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
Is this a sequence trainer.
isSplitCharacter(char) - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
Deprecated.
isSplitCharacter(char) - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer.SplitCharactersSplitterFunction
Checks if this is a valid split character or whitespace.
isSplitXDigitCharacter(char) - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
Deprecated.
isSplitXDigitCharacter(char) - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer.SplitCharactersSplitterFunction
Checks if this a valid split character outside of a run of digits.
isWeighted() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
Is this view a weighted bootstrap sample.
isWhitespace(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer
A quick check for whether a character is whitespace.
isZeroIndexed() - Method in class org.tribuo.datasource.LibSVMDataSource
Returns true if this dataset is zero indexed, false otherwise (i.e., it starts from 1).
iteration - Variable in class org.tribuo.math.optimisers.SGD
 
iterations - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
Iterations of the k-means algorithm.
iterations - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
Maximum number of iterations.
iterations - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
Iterations of Elastic Net.
iterator() - Method in class org.tribuo.anomaly.example.GaussianAnomalyDataSource
 
iterator() - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
iterator() - Method in class org.tribuo.classification.example.DemoLabelDataSource
 
iterator() - Method in class org.tribuo.classification.ImmutableLabelInfo
 
iterator() - Method in class org.tribuo.clustering.example.GaussianClusterDataSource
 
iterator() - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
iterator() - Method in class org.tribuo.data.columnar.ColumnarDataSource
 
iterator() - Method in class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
Deprecated.
 
iterator() - Method in class org.tribuo.data.text.DirectoryFileSource
 
iterator() - Method in class org.tribuo.data.text.TextDataSource
 
iterator() - Method in class org.tribuo.dataset.DatasetView
 
iterator() - Method in class org.tribuo.Dataset
 
iterator() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
 
iterator() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
 
iterator() - Method in class org.tribuo.datasource.AggregateDataSource
 
iterator() - Method in class org.tribuo.datasource.IDXDataSource
 
iterator() - Method in class org.tribuo.datasource.LibSVMDataSource
 
iterator() - Method in class org.tribuo.datasource.ListDataSource
 
iterator() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
 
iterator() - Method in class org.tribuo.FeatureMap
 
iterator() - Method in class org.tribuo.impl.ArrayExample
 
iterator() - Method in class org.tribuo.impl.BinaryFeaturesExample
 
iterator() - Method in class org.tribuo.impl.ListExample
 
iterator() - Method in class org.tribuo.math.la.DenseMatrix
 
iterator() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
iterator() - Method in class org.tribuo.math.la.DenseVector
 
iterator() - Method in class org.tribuo.math.la.SparseVector
 
iterator() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
iterator() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
iterator() - Method in class org.tribuo.multilabel.example.MultiLabelGaussianDataSource
 
iterator() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
iterator() - Method in class org.tribuo.provenance.DatasetProvenance
 
iterator() - Method in class org.tribuo.provenance.EvaluationProvenance
 
iterator() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
 
iterator() - Method in class org.tribuo.provenance.ModelProvenance
Calls ModelProvenance.internalProvenances() and returns the iterator from that list.
iterator() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
 
iterator() - Method in class org.tribuo.regression.example.GaussianDataSource
 
iterator() - Method in class org.tribuo.regression.example.NonlinearGaussianDataSource
 
iterator() - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
iterator() - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
iterator() - Method in class org.tribuo.regression.Regressor
 
iterator() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
 
iterator() - Method in class org.tribuo.sequence.SequenceDataset
 
iterator() - Method in class org.tribuo.sequence.SequenceExample
 
iterator() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
 
iterator() - Method in class org.tribuo.util.infotheory.impl.RowList
 

J

j - Variable in class org.tribuo.math.la.MatrixTuple
The j index.
JACCARD_SCORE - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The Jaccard score, i.e., the average across the predictions of the intersection over union.
jaccardScore() - Method in interface org.tribuo.multilabel.evaluation.MultiLabelEvaluation
The average across the predictions of the intersection of the true and predicted labels divided by the union of the true and predicted labels.
jaccardScore() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
jaccardScore(List<Prediction<MultiLabel>>) - Static method in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The average Jaccard score across the predictions.
jaccardScore(MultiLabel, MultiLabel) - Static method in class org.tribuo.multilabel.MultiLabel
The Jaccard score/index between the two MultiLabels.
JAVA_VERSION_STRING - Static variable in class org.tribuo.provenance.ModelProvenance
 
javaVersionString - Variable in class org.tribuo.provenance.ModelProvenance
 
JOINER - Static variable in class org.tribuo.data.columnar.ColumnarFeature
The joiner between the field name and feature name.
jointCounts - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
The joint distribution.
jointEntropy(ArrayList<T1>, ArrayList<T2>, ArrayList<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the Shannon/Guiasu weighted joint entropy of two arrays, using histogram probability estimators.
jointEntropy(List<T1>, List<T2>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the Shannon joint entropy of two arrays, using histogram probability estimators.
jointMI(List<T1>, List<T2>, List<T3>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon joint mutual information, using histogram probability estimators.
jointMI(List<T1>, List<T2>, List<T3>, List<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted joint mutual information, using histogram probability estimators.
jointMI(TripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon joint mutual information, using histogram probability estimators.
jointMI(TripleDistribution<T1, T2, T3>, Map<?, Double>, WeightedInformationTheory.VariableSelector) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted joint mutual information, using histogram probability estimators.
jointMI(WeightedTripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted joint mutual information, using histogram probability estimators.
JointRegressorTrainingNode - Class in org.tribuo.regression.rtree.impl
A decision tree node used at training time.
JointRegressorTrainingNode(RegressorImpurity, Dataset<Regressor>, boolean, AbstractTrainingNode.LeafDeterminer) - Constructor for class org.tribuo.regression.rtree.impl.JointRegressorTrainingNode
Constructor which creates the inverted file.
JsonDataSource<T extends Output<T>> - Class in org.tribuo.json
A DataSource for loading data from a JSON text file and applying FieldProcessors to it.
JsonDataSource(URI, RowProcessor<T>, boolean) - Constructor for class org.tribuo.json.JsonDataSource
Creates a JsonDataSource using the specified RowProcessor to process the data.
JsonDataSource(Path, RowProcessor<T>, boolean) - Constructor for class org.tribuo.json.JsonDataSource
Creates a JsonDataSource using the specified RowProcessor to process the data.
JsonDataSource.JsonDataSourceProvenance - Class in org.tribuo.json
Provenance for JsonDataSource.
JsonDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.json.JsonDataSource.JsonDataSourceProvenance
Deserialization constructor.
JsonFileIterator - Class in org.tribuo.json
An iterator for JSON format files converting them into a format suitable for RowProcessor.
JsonFileIterator(Reader) - Constructor for class org.tribuo.json.JsonFileIterator
Builds a JsonFileIterator for the supplied Reader.
JsonFileIterator(URI) - Constructor for class org.tribuo.json.JsonFileIterator
Builds a CSVIterator for the supplied URI.
JsonUtil - Class in org.tribuo.json
Utilities for interacting with JSON objects or text representations.

K

k - Variable in class org.tribuo.clustering.hdbscan.HdbscanOptions
The number of nearest-neighbors to use in the initial density approximation.
Kernel - Interface in org.tribuo.math.kernel
An interface for a Mercer kernel function.
kernelDegree - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Degree in polynomial kernel function.
kernelDist(double, double) - Static method in class org.tribuo.classification.explanations.lime.LIMEBase
Calculates an RBF kernel of a specific width.
kernelEpochs - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Number of SGD epochs.
kernelGamma - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Gamma value in kernel function.
kernelIntercept - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Intercept in kernel function.
kernelKernel - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Kernel function.
kernelLambda - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Lambda value in gradient optimisation.
kernelLoggingInterval - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Log the objective after n examples.
kernelSeed - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
Sets the random seed for the Kernel SVM.
KernelSVMModel - Class in org.tribuo.classification.sgd.kernel
The inference time version of a kernel model trained using Pegasos.
kernelSVMOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for Kernel SVM trainers.
KernelSVMOptions - Class in org.tribuo.classification.sgd.kernel
Options for using the KernelSVMTrainer.
KernelSVMOptions() - Constructor for class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
KernelSVMOptions.KernelEnum - Enum Class in org.tribuo.classification.sgd.kernel
The kernel types.
KernelSVMTrainer - Class in org.tribuo.classification.sgd.kernel
A trainer for a kernelised model using the Pegasos optimiser.
KernelSVMTrainer(Kernel, double, int, int, long) - Constructor for class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
Constructs a trainer for a kernel SVM model.
KernelSVMTrainer(Kernel, double, int, long) - Constructor for class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
Constructs a trainer for a kernel SVM model.
kernelType - Variable in class org.tribuo.common.libsvm.SVMParameters
 
kernelType - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
Type of SVM kernel.
KernelType - Enum Class in org.tribuo.common.libsvm
Kernel types from libsvm.
kernelWidth - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
KEY_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
KEY_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
keySet() - Method in class org.tribuo.FeatureMap
Returns all the feature names in the domain.
KFoldSplitter<T extends Output<T>> - Class in org.tribuo.evaluation
A k-fold splitter to be used in cross-validation.
KFoldSplitter(int) - Constructor for class org.tribuo.evaluation.KFoldSplitter
Builds a k-fold splitter using Trainer.DEFAULT_SEED as the seed.
KFoldSplitter(int, long) - Constructor for class org.tribuo.evaluation.KFoldSplitter
Builds a k-fold splitter.
KFoldSplitter.TrainTestFold<T extends Output<T>> - Class in org.tribuo.evaluation
Stores a train/test split for a dataset.
KMeansModel - Class in org.tribuo.clustering.kmeans
A K-Means model with a selectable distance function.
KMeansOptions - Class in org.tribuo.clustering.kmeans
OLCUT Options for the K-Means implementation.
KMeansOptions() - Constructor for class org.tribuo.clustering.kmeans.KMeansOptions
 
KMeansOptions() - Constructor for class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
KMeansTrainer - Class in org.tribuo.clustering.kmeans
A K-Means trainer, which generates a K-means clustering of the supplied data.
KMeansTrainer(int, int, KMeansTrainer.Distance, int, long) - Constructor for class org.tribuo.clustering.kmeans.KMeansTrainer
Constructs a K-Means trainer using the supplied parameters and the default random initialisation.
KMeansTrainer(int, int, KMeansTrainer.Distance, KMeansTrainer.Initialisation, int, long) - Constructor for class org.tribuo.clustering.kmeans.KMeansTrainer
Constructs a K-Means trainer using the supplied parameters.
KMeansTrainer.Distance - Enum Class in org.tribuo.clustering.kmeans
Possible distance functions.
KMeansTrainer.Initialisation - Enum Class in org.tribuo.clustering.kmeans
Possible initialization functions.
KNN - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
Creates a KNNTrainer.
knnBackend - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
Parallel backend to use.
KNNClassifierOptions - Class in org.tribuo.common.nearest
CLI Options for training a k-nearest neighbour predictor.
KNNClassifierOptions() - Constructor for class org.tribuo.common.nearest.KNNClassifierOptions
 
KNNClassifierOptions.EnsembleCombinerType - Enum Class in org.tribuo.common.nearest
The type of combination function.
knnDistance - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
Distance metric to use.
knnEnsembleCombiner - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
Parallel backend to use.
knnK - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
K nearest neighbours to use.
KNNModel<T extends Output<T>> - Class in org.tribuo.common.nearest
A k-nearest neighbours model.
KNNModel.Backend - Enum Class in org.tribuo.common.nearest
The parallel backend for batch predictions.
knnNumThreads - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
Number of threads to use.
knnOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for K-NN trainers.
KNNTrainer<T extends Output<T>> - Class in org.tribuo.common.nearest
A Trainer for k-nearest neighbour models.
KNNTrainer(int, KNNTrainer.Distance, int, EnsembleCombiner<T>, KNNModel.Backend) - Constructor for class org.tribuo.common.nearest.KNNTrainer
Creates a K-NN trainer using the supplied parameters.
KNNTrainer.Distance - Enum Class in org.tribuo.common.nearest
The available distance functions.

L

L1 - Enum constant in enum class org.tribuo.clustering.hdbscan.HdbscanTrainer.Distance
L1 (or Manhattan) distance.
L1 - Enum constant in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Distance
L1 (or Manhattan) distance.
L1 - Enum constant in enum class org.tribuo.common.nearest.KNNTrainer.Distance
L1 (or Manhattan) distance.
l1Distance(SGDVector) - Method in class org.tribuo.math.la.DenseVector
The l1 or Manhattan distance between this vector and the other vector.
l1Distance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
The l1 or Manhattan distance between this vector and the other vector.
l1Distance(SGDVector) - Method in class org.tribuo.math.la.SparseVector
 
L1R_L2LOSS_SVC - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
L1-regularized L2-loss support vector classification
L1R_LR - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
L1-regularized logistic regression
l1Ratio - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
Ratio between the l1 and l2 penalties in the Elastic Net.
L2 - Enum constant in enum class org.tribuo.common.nearest.KNNTrainer.Distance
L2 (or Euclidean) distance.
l2Distance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Synonym for euclideanDistance.
L2R_L1LOSS_SVC_DUAL - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
L2-regularized L1-loss support vector classification (dual)
L2R_L1LOSS_SVR_DUAL - Enum constant in enum class org.tribuo.regression.liblinear.LinearRegressionType.LinearType
L2-regularized L1-loss support vector regression (dual)
L2R_L2LOSS_SVC - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
L2-regularized L2-loss support vector classification (primal)
L2R_L2LOSS_SVC_DUAL - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
L2-regularized L2-loss support vector classification (dual)
L2R_L2LOSS_SVR - Enum constant in enum class org.tribuo.regression.liblinear.LinearRegressionType.LinearType
L2-regularized L2-loss support vector regression (primal)
L2R_L2LOSS_SVR_DUAL - Enum constant in enum class org.tribuo.regression.liblinear.LinearRegressionType.LinearType
L2-regularized L2-loss support vector regression (dual)
L2R_LR - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
L2-regularized logistic regression (primal)
L2R_LR_DUAL - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
L2-regularized logistic regression (dual)
label - Variable in class org.tribuo.classification.Label
The name of the label.
Label - Class in org.tribuo.classification
An immutable multi-class classification label.
Label(String) - Constructor for class org.tribuo.classification.Label
Builds a label with the sentinel score of Double.NaN.
Label(String, double) - Constructor for class org.tribuo.classification.Label
Builds a label with the supplied string and score.
LabelConfusionMatrix - Class in org.tribuo.classification.evaluation
A confusion matrix for Labels.
LabelConfusionMatrix(ImmutableOutputInfo<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelConfusionMatrix
Creates a confusion matrix from the supplied predictions and label info.
LabelConfusionMatrix(Model<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelConfusionMatrix
Creates a confusion matrix from the supplied predictions, using the label info from the supplied model.
LabelConverter - Class in org.tribuo.interop.tensorflow
Can convert a Label into a Tensor containing one hot encoding of the label and can convert a TFloat16 or TFloat32 into a Prediction or a Label.
LabelConverter() - Constructor for class org.tribuo.interop.tensorflow.LabelConverter
Constructs a LabelConverter.
labelCounts - Variable in class org.tribuo.classification.LabelInfo
The occurrence counts of each label.
labelCounts - Variable in class org.tribuo.multilabel.MultiLabelInfo
 
LabelEvaluation - Interface in org.tribuo.classification.evaluation
Adds multi-class classification specific metrics to ClassifierEvaluation.
LabelEvaluationUtil - Class in org.tribuo.classification.evaluation
Static utility functions for calculating performance metrics on Labels.
LabelEvaluationUtil.PRCurve - Class in org.tribuo.classification.evaluation
Stores the Precision-Recall curve as three arrays: the precisions, the recalls, and the thresholds associated with those values.
LabelEvaluationUtil.ROC - Class in org.tribuo.classification.evaluation
Stores the ROC curve as three arrays: the false positive rate, the true positive rate, and the thresholds associated with those rates.
LabelEvaluator - Class in org.tribuo.classification.evaluation
An Evaluator for Labels.
LabelEvaluator() - Constructor for class org.tribuo.classification.evaluation.LabelEvaluator
 
LabelFactory - Class in org.tribuo.classification
A factory for making Label related classes.
LabelFactory() - Constructor for class org.tribuo.classification.LabelFactory
Constructs a label factory.
LabelFactory.LabelFactoryProvenance - Class in org.tribuo.classification
Provenance for LabelFactory.
LabelFactoryProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.classification.LabelFactory.LabelFactoryProvenance
Constructor used by the provenance serialization system.
LabelFeatureExtractor - Interface in org.tribuo.classification.sequence.viterbi
A class for featurising labels from previous steps in Viterbi.
LabelImpurity - Interface in org.tribuo.classification.dtree.impurity
Calculates a tree impurity score based on label counts, weighted label counts or a probability distribution.
LabelInfo - Class in org.tribuo.classification
The base class for information about multi-class classification Labels.
LabelledDataGenerator - Class in org.tribuo.classification.example
Generates three example train and test datasets, used for unit testing.
LabelMetric - Class in org.tribuo.classification.evaluation
A EvaluationMetric for Labels which calculates the value based on a ConfusionMatrix.
LabelMetric(MetricTarget<Label>, String, ToDoubleBiFunction<MetricTarget<Label>, LabelMetric.Context>) - Constructor for class org.tribuo.classification.evaluation.LabelMetric
Construct a new LabelMetric for the supplied metric target, using the supplied function.
LabelMetric.Context - Class in org.tribuo.classification.evaluation
The context for a LabelMetric is a ConfusionMatrix.
LabelMetrics - Enum Class in org.tribuo.classification.evaluation
An enum of the default LabelMetrics supported by the multi-class classification evaluation package.
LabelObjective - Interface in org.tribuo.classification.sgd
An interface for single label prediction objectives.
LabelOneVOneTransformer - Class in org.tribuo.interop.onnx
Can convert an OnnxValue into a Prediction or a Label.
LabelOneVOneTransformer() - Constructor for class org.tribuo.interop.onnx.LabelOneVOneTransformer
Constructs a Label transformer that operates on a one v one output and produces scores via voting.
labels - Variable in class org.tribuo.classification.LabelInfo
The label domain.
labels - Variable in class org.tribuo.classification.sgd.crf.Chunk
The labels for the next labels.length values.
labels - Variable in class org.tribuo.classification.sgd.Util.ExampleArray
The label indices.
labels - Variable in class org.tribuo.classification.sgd.Util.SequenceExampleArray
The sequence example label indices.
labels - Variable in class org.tribuo.multilabel.MultiLabelInfo
 
LabelSequenceEvaluation - Class in org.tribuo.classification.sequence
A class that can be used to evaluate a sequence label classification model element wise on a given set of data.
LabelSequenceEvaluation(Map<MetricID<Label>, Double>, LabelMetric.Context, EvaluationProvenance) - Constructor for class org.tribuo.classification.sequence.LabelSequenceEvaluation
Constructs a LabelSequenceEvaluation using the supplied parameters.
LabelSequenceEvaluator - Class in org.tribuo.classification.sequence
A sequence evaluator for labels.
LabelSequenceEvaluator() - Constructor for class org.tribuo.classification.sequence.LabelSequenceEvaluator
 
LabelTransformer - Class in org.tribuo.interop.onnx
Can convert an OnnxValue into a Prediction or a Label.
LabelTransformer() - Constructor for class org.tribuo.interop.onnx.LabelTransformer
Constructs a LabelTransformer which assumes the model emits probabilities.
LabelTransformer(boolean) - Constructor for class org.tribuo.interop.onnx.LabelTransformer
Constructs a LabelTransformer.
lambda - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
Lambda for Pegasos.
lambda - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
L2 regularization term for weights (default 1).
lambda - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
L2 regularization term for weights (default 1).
languageTag - Variable in class org.tribuo.util.tokens.options.BreakIteratorTokenizerOptions
BreakIteratorTokenizer - The language tag of the locale to be used.
LARS - Enum constant in enum class org.tribuo.regression.slm.TrainTest.SLMType
Creates a LARSTrainer.
LARSLASSO - Enum constant in enum class org.tribuo.regression.slm.TrainTest.SLMType
Creates a LARSLassoTrainer.
LARSLassoTrainer - Class in org.tribuo.regression.slm
A trainer for a lasso linear regression model which uses LARS to construct the model.
LARSLassoTrainer() - Constructor for class org.tribuo.regression.slm.LARSLassoTrainer
Constructs a lasso LARS trainer that selects all the features.
LARSLassoTrainer(int) - Constructor for class org.tribuo.regression.slm.LARSLassoTrainer
Constructs a lasso LARS trainer for a linear model.
LARSTrainer - Class in org.tribuo.regression.slm
A trainer for a linear regression model which uses least angle regression.
LARSTrainer() - Constructor for class org.tribuo.regression.slm.LARSTrainer
Constructs a least angle regression trainer that selects all the features.
LARSTrainer(int) - Constructor for class org.tribuo.regression.slm.LARSTrainer
Constructs a least angle regression trainer for a linear model.
LAST - Enum constant in enum class org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Select the last feature value in the list.
lastIndexOf(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
 
leafDeterminer - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
LeafDeterminer(int, float, float) - Constructor for class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
Constructs a leaf determiner using the supplied parameters.
LeafNode<T extends Output<T>> - Class in org.tribuo.common.tree
An immutable leaf Node that can create a prediction.
LeafNode(double, T, Map<String, T>, boolean) - Constructor for class org.tribuo.common.tree.LeafNode
Constructs a leaf node.
learningRate - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
Learning rate for AdaGrad, AdaGradRDA, Adam, Pegasos.
learningRate() - Method in class org.tribuo.math.optimisers.SGD
Override to provide a function which calculates the learning rate.
leftMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseMatrix
 
leftMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
leftMultiply(SGDVector) - Method in interface org.tribuo.math.la.Matrix
Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
leftMultiply(SGDVector) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
len - Variable in class org.tribuo.util.tokens.universal.Range
The token length.
length() - Method in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
Returns the number of elements in this subsequence.
length() - Method in class org.tribuo.util.tokens.Token
The number of characters in this token.
length() - Method in class org.tribuo.util.tokens.universal.Range
 
LESS - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Less than, returns the element-wise less than operation on the two tensors.
LESS_OR_EQUAL - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Less than or equal to, returns the element-wise less than or equal to operation on the two tensors.
lessThanOrEqual - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
LIBLINEAR - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
LibLinearAnomalyModel - Class in org.tribuo.anomaly.liblinear
A Model which wraps a LibLinear-java anomaly detection model.
LibLinearAnomalyTrainer - Class in org.tribuo.anomaly.liblinear
A Trainer which wraps a liblinear-java anomaly detection trainer using a one-class SVM.
LibLinearAnomalyTrainer() - Constructor for class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
Creates a trainer using the default values (type:ONECLASS_SVM, cost:1, maxIterations:1000, terminationCriterion:0.1, nu:0.5).
LibLinearAnomalyTrainer(double) - Constructor for class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
Creates a trainer using the default values (type:ONECLASS_SVM, cost:1, maxIterations:1000, terminationCriterion:0.1) and the specified nu.
LibLinearAnomalyTrainer(LinearAnomalyType, double, double, double) - Constructor for class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
Creates a trainer for a LibLinearAnomalyModel.
LibLinearAnomalyTrainer(LinearAnomalyType, double, int, double, double) - Constructor for class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
Creates a trainer for a LibLinear model
LibLinearClassificationModel - Class in org.tribuo.classification.liblinear
A Model which wraps a LibLinear-java classification model.
LibLinearClassificationTrainer - Class in org.tribuo.classification.liblinear
A Trainer which wraps a liblinear-java classifier trainer.
LibLinearClassificationTrainer() - Constructor for class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
Creates a trainer using the default values (L2R_L2LOSS_SVC_DUAL, 1, 0.1).
LibLinearClassificationTrainer(LinearClassificationType, double, double) - Constructor for class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
Creates a trainer for a LibLinearClassificationModel.
LibLinearClassificationTrainer(LinearClassificationType, double, int, double) - Constructor for class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
Creates a trainer for a LibLinear model
LibLinearModel<T extends Output<T>> - Class in org.tribuo.common.liblinear
A Model which wraps a LibLinear-java model.
LibLinearModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, List<Model>) - Constructor for class org.tribuo.common.liblinear.LibLinearModel
Constructs a LibLinear model from the supplied arguments.
liblinearOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for LibLinear trainers.
libLinearOptions - Variable in class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
The liblinear options.
LibLinearOptions - Class in org.tribuo.classification.liblinear
Command line options for working with a classification liblinear model.
LibLinearOptions() - Constructor for class org.tribuo.classification.liblinear.LibLinearOptions
 
LibLinearOptions() - Constructor for class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
 
libLinearParams - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
LibLinearRegressionModel - Class in org.tribuo.regression.liblinear
A Model which wraps a LibLinear-java model.
LibLinearRegressionTrainer - Class in org.tribuo.regression.liblinear
A Trainer which wraps a liblinear-java regression trainer.
LibLinearRegressionTrainer() - Constructor for class org.tribuo.regression.liblinear.LibLinearRegressionTrainer
Creates a trainer using the default values (L2R_L2LOSS_SVR, 1, 1000, 0.1, 0.1).
LibLinearRegressionTrainer(LinearRegressionType) - Constructor for class org.tribuo.regression.liblinear.LibLinearRegressionTrainer
Creates a trainer for a LibLinear regression model.
LibLinearRegressionTrainer(LinearRegressionType, double, int, double, double) - Constructor for class org.tribuo.regression.liblinear.LibLinearRegressionTrainer
Creates a trainer for a LibLinear regression model.
LibLinearTrainer<T extends Output<T>> - Class in org.tribuo.common.liblinear
A Trainer which wraps a liblinear-java trainer.
LibLinearTrainer() - Constructor for class org.tribuo.common.liblinear.LibLinearTrainer
 
LibLinearTrainer(LibLinearType<T>, double, int, double) - Constructor for class org.tribuo.common.liblinear.LibLinearTrainer
Creates a trainer for a LibLinear model
LibLinearTrainer(LibLinearType<T>, double, int, double, double) - Constructor for class org.tribuo.common.liblinear.LibLinearTrainer
Creates a trainer for a LibLinear model
LibLinearType<T extends Output<T>> - Interface in org.tribuo.common.liblinear
A carrier type for the liblinear algorithm type.
LIBSVM - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
LIBSVM - Enum constant in enum class org.tribuo.data.DataOptions.InputFormat
LibSVM/svm-light format data.
LibSVMAnomalyModel - Class in org.tribuo.anomaly.libsvm
A anomaly detection model that uses an underlying libSVM model to make the predictions.
LibSVMAnomalyTrainer - Class in org.tribuo.anomaly.libsvm
A trainer for anomaly models that uses LibSVM.
LibSVMAnomalyTrainer() - Constructor for class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
For OLCUT.
LibSVMAnomalyTrainer(SVMParameters<Event>) - Constructor for class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
Creates a one-class LibSVM trainer using the supplied parameters and Trainer.DEFAULT_SEED.
LibSVMAnomalyTrainer(SVMParameters<Event>, long) - Constructor for class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
Creates a one-class LibSVM trainer using the supplied parameters and RNG seed.
LibSVMClassificationModel - Class in org.tribuo.classification.libsvm
A classification model that uses an underlying LibSVM model to make the predictions.
LibSVMClassificationTrainer - Class in org.tribuo.classification.libsvm
A trainer for classification models that uses LibSVM.
LibSVMClassificationTrainer() - Constructor for class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
For OLCUT.
LibSVMClassificationTrainer(SVMParameters<Label>) - Constructor for class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
Constructs a classification LibSVM trainer using the specified parameters and Trainer.DEFAULT_SEED.
LibSVMClassificationTrainer(SVMParameters<Label>, long) - Constructor for class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
Constructs a classification LibSVM trainer using the specified parameters and seed.
LibSVMDataSource<T extends Output<T>> - Class in org.tribuo.datasource
A DataSource which can read LibSVM formatted data.
LibSVMDataSource(URL, OutputFactory<T>) - Constructor for class org.tribuo.datasource.LibSVMDataSource
Constructs a LibSVMDataSource from the supplied URL and output factory.
LibSVMDataSource(URL, OutputFactory<T>, boolean, int) - Constructor for class org.tribuo.datasource.LibSVMDataSource
Constructs a LibSVMDataSource from the supplied URL and output factory.
LibSVMDataSource(Path, OutputFactory<T>) - Constructor for class org.tribuo.datasource.LibSVMDataSource
Constructs a LibSVMDataSource from the supplied path and output factory.
LibSVMDataSource(Path, OutputFactory<T>, boolean, int) - Constructor for class org.tribuo.datasource.LibSVMDataSource
Constructs a LibSVMDataSource from the supplied path and output factory.
LibSVMDataSource.LibSVMDataSourceProvenance - Class in org.tribuo.datasource
The provenance for a LibSVMDataSource.
LibSVMDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance
Constructs a provenance during unmarshalling.
LibSVMModel<T extends Output<T>> - Class in org.tribuo.common.libsvm
A model that uses an underlying libSVM model to make the predictions.
LibSVMModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, List<svm_model>) - Constructor for class org.tribuo.common.libsvm.LibSVMModel
Constructs a LibSVMModel from the supplied arguments.
libsvmOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for LibSVM trainers.
libsvmOptions - Variable in class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
The LibSVM options.
LibSVMOptions - Class in org.tribuo.classification.libsvm
CLI options for training a LibSVM classification model.
LibSVMOptions() - Constructor for class org.tribuo.classification.libsvm.LibSVMOptions
 
LibSVMOptions() - Constructor for class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 
LibSVMRegressionModel - Class in org.tribuo.regression.libsvm
A regression model that uses an underlying libSVM model to make the predictions.
LibSVMRegressionTrainer - Class in org.tribuo.regression.libsvm
A trainer for regression models that uses LibSVM.
LibSVMRegressionTrainer() - Constructor for class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
For olcut.
LibSVMRegressionTrainer(SVMParameters<Regressor>) - Constructor for class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
Constructs a LibSVMRegressionTrainer using the supplied parameters without standardizing the regression variables.
LibSVMRegressionTrainer(SVMParameters<Regressor>, boolean) - Constructor for class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
Constructs a LibSVMRegressionTrainer using the supplied parameters and Trainer.DEFAULT_SEED.
LibSVMRegressionTrainer(SVMParameters<Regressor>, boolean, long) - Constructor for class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
Constructs a LibSVMRegressionTrainer using the supplied parameters and seed.
LibSVMTrainer<T extends Output<T>> - Class in org.tribuo.common.libsvm
A trainer that will train using libsvm's Java implementation.
LibSVMTrainer() - Constructor for class org.tribuo.common.libsvm.LibSVMTrainer
For olcut.
LibSVMTrainer(SVMParameters<T>, long) - Constructor for class org.tribuo.common.libsvm.LibSVMTrainer
Constructs a LibSVMTrainer from the parameters.
LIMEBase - Class in org.tribuo.classification.explanations.lime
LIMEBase merges the lime_base.py and lime_tabular.py implementations, and deals with simple matrices of numerical or categorical data.
LIMEBase(SplittableRandom, Model<Label>, SparseTrainer<Regressor>, int) - Constructor for class org.tribuo.classification.explanations.lime.LIMEBase
Constructs a LIME explainer for a model which uses tabular data (i.e., no special treatment for text features).
LIMEColumnar - Class in org.tribuo.classification.explanations.lime
Uses the columnar data processing infrastructure to mix text and tabular data.
LIMEColumnar(SplittableRandom, Model<Label>, SparseTrainer<Regressor>, int, RowProcessor<Label>, Tokenizer) - Constructor for class org.tribuo.classification.explanations.lime.LIMEColumnar
Constructs a LIME explainer for a model which uses the columnar data processing system.
LIMEExplanation - Class in org.tribuo.classification.explanations.lime
An Explanation using LIME.
LIMEExplanation(SparseModel<Regressor>, Prediction<Label>, RegressionEvaluation) - Constructor for class org.tribuo.classification.explanations.lime.LIMEExplanation
Constructs a LIME explanation.
LIMEText - Class in org.tribuo.classification.explanations.lime
Uses a Tribuo TextFeatureExtractor to explain the prediction for a given piece of text.
LIMEText(SplittableRandom, Model<Label>, SparseTrainer<Regressor>, int, TextFeatureExtractor<Label>, Tokenizer) - Constructor for class org.tribuo.classification.explanations.lime.LIMEText
Constructs a LIME explainer for a model which uses text data.
LIMETextCLI - Class in org.tribuo.classification.explanations.lime
A CLI for interacting with LIMEText.
LIMETextCLI() - Constructor for class org.tribuo.classification.explanations.lime.LIMETextCLI
Constructs a LIME CLI.
LIMETextCLI.LIMETextCLIOptions - Class in org.tribuo.classification.explanations.lime
Command line options.
LIMETextCLIOptions() - Constructor for class org.tribuo.classification.explanations.lime.LIMETextCLI.LIMETextCLIOptions
 
Linear - Class in org.tribuo.math.kernel
A linear kernel, u.dot(v).
Linear() - Constructor for class org.tribuo.math.kernel.Linear
A linear kernel, u.dot(v).
LINEAR - Enum constant in enum class org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Uses a Linear kernel.
LINEAR - Enum constant in enum class org.tribuo.common.libsvm.KernelType
A linear kernel function (i.e., a dot product).
LINEAR - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
A boosted linear model.
LINEAR - Enum constant in enum class org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Squared error loss function.
LinearAnomalyType - Class in org.tribuo.anomaly.liblinear
The carrier type for liblinear anomaly detection modes.
LinearAnomalyType(LinearAnomalyType.LinearType) - Constructor for class org.tribuo.anomaly.liblinear.LinearAnomalyType
Constructs the type of the liblinear anomaly detector.
LinearAnomalyType.LinearType - Enum Class in org.tribuo.anomaly.liblinear
The different model types available for classification.
LinearClassificationType - Class in org.tribuo.classification.liblinear
The carrier type for liblinear classification modes.
LinearClassificationType(LinearClassificationType.LinearType) - Constructor for class org.tribuo.classification.liblinear.LinearClassificationType
Constructs a LinearClassificationType using the supplied algorithm.
LinearClassificationType.LinearType - Enum Class in org.tribuo.classification.liblinear
The different model types available for classification.
LinearParameters - Class in org.tribuo.math
A Parameters for producing linear models.
LinearParameters(int, int) - Constructor for class org.tribuo.math.LinearParameters
Constructor.
LinearParameters(DenseMatrix) - Constructor for class org.tribuo.math.LinearParameters
Constructs a LinearParameters wrapped around a weight matrix.
LinearRegressionType - Class in org.tribuo.regression.liblinear
The carrier type for liblinear linear regression modes.
LinearRegressionType(LinearRegressionType.LinearType) - Constructor for class org.tribuo.regression.liblinear.LinearRegressionType
Constructs a LinearRegressionType with the specified LibLinear algorithm.
LinearRegressionType.LinearType - Enum Class in org.tribuo.regression.liblinear
The type of linear regression algorithm.
LinearScalingTransformation - Class in org.tribuo.transform.transformations
A Transformation which takes an observed distribution and rescales it so all values are between the desired min and max.
LinearScalingTransformation() - Constructor for class org.tribuo.transform.transformations.LinearScalingTransformation
Defaults to zero - one.
LinearScalingTransformation(double, double) - Constructor for class org.tribuo.transform.transformations.LinearScalingTransformation
Constructs a LinearScalingTransformation which puts feature values into the specified range.
LinearScalingTransformation.LinearScalingTransformationProvenance - Class in org.tribuo.transform.transformations
LinearScalingTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
Deserialization constructor.
LINEARSGD - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
SGD with a linear-decay learning rate.
LinearSGDModel - Class in org.tribuo.classification.sgd.linear
The inference time version of a linear model trained using SGD.
LinearSGDModel - Class in org.tribuo.multilabel.sgd.linear
The inference time version of a multi-label linear model trained using SGD.
LinearSGDModel - Class in org.tribuo.regression.sgd.linear
The inference time version of a linear model trained using SGD.
linearSGDOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for Linear SGD trainers.
LinearSGDOptions - Class in org.tribuo.classification.sgd.linear
CLI options for training a linear classifier.
LinearSGDOptions - Class in org.tribuo.multilabel.sgd.linear
CLI options for training a linear classifier.
LinearSGDOptions() - Constructor for class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
LinearSGDOptions() - Constructor for class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
LinearSGDOptions.LossEnum - Enum Class in org.tribuo.classification.sgd.linear
Available loss types.
LinearSGDOptions.LossEnum - Enum Class in org.tribuo.multilabel.sgd.linear
Available loss types.
LinearSGDTrainer - Class in org.tribuo.classification.sgd.linear
A trainer for a linear classifier using SGD.
LinearSGDTrainer - Class in org.tribuo.multilabel.sgd.linear
A trainer for a multi-label linear model which uses SGD.
LinearSGDTrainer - Class in org.tribuo.regression.sgd.linear
A trainer for a linear regression model which uses SGD.
LinearSGDTrainer(LabelObjective, StochasticGradientOptimiser, int, int, int, long) - Constructor for class org.tribuo.classification.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(LabelObjective, StochasticGradientOptimiser, int, int, long) - Constructor for class org.tribuo.classification.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(LabelObjective, StochasticGradientOptimiser, int, long) - Constructor for class org.tribuo.classification.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(MultiLabelObjective, StochasticGradientOptimiser, int, int, int, long) - Constructor for class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(MultiLabelObjective, StochasticGradientOptimiser, int, int, long) - Constructor for class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(MultiLabelObjective, StochasticGradientOptimiser, int, long) - Constructor for class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(RegressionObjective, StochasticGradientOptimiser, int, int, int, long) - Constructor for class org.tribuo.regression.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(RegressionObjective, StochasticGradientOptimiser, int, int, long) - Constructor for class org.tribuo.regression.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
LinearSGDTrainer(RegressionObjective, StochasticGradientOptimiser, int, long) - Constructor for class org.tribuo.regression.sgd.linear.LinearSGDTrainer
Constructs an SGD trainer for a linear model.
list - Variable in class org.tribuo.transform.TransformationMap.TransformationList
The list of transformations.
ListDataSource<T extends Output<T>> - Class in org.tribuo.datasource
A data source which wraps up a list of Examples along with their DataSourceProvenance and an OutputFactory.
ListDataSource(List<Example<T>>, OutputFactory<T>, DataSourceProvenance) - Constructor for class org.tribuo.datasource.ListDataSource
Constructs an in-memory data source wrapping the supplied examples.
ListExample<T extends Output<T>> - Class in org.tribuo.impl
This class will not be performant until value types are available in Java.
ListExample(Example<T>) - Constructor for class org.tribuo.impl.ListExample
Copies the supplied example's features, weight, output and metadata into this example.
ListExample(T) - Constructor for class org.tribuo.impl.ListExample
Constructs a ListExample for the specified output with a weight of Example.DEFAULT_WEIGHT.
ListExample(T, float) - Constructor for class org.tribuo.impl.ListExample
Constructs a ListExample for the specified output and weight.
ListExample(T, String[], double[]) - Constructor for class org.tribuo.impl.ListExample
Constructs a ListExample from the specified output, feature names and feature values.
ListExample(T, List<? extends Feature>) - Constructor for class org.tribuo.impl.ListExample
Constructs a ListExample using the specified output and feature list.
listIterator() - Method in class org.tribuo.util.infotheory.impl.RowList
 
listIterator(int) - Method in class org.tribuo.util.infotheory.impl.RowList
 
load(Path, String) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv file then wraps it in a dataset.
load(Path, String, String[]) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv file then wraps it in a dataset.
load(Path, Set<String>) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv file then wraps it in a dataset.
load(Path, Set<String>, String[]) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv file then wraps it in a dataset.
load(Test.ConfigurableTestOptions) - Static method in class org.tribuo.classification.experiments.Test
Loads in the model and the dataset from the options.
load(OutputFactory<T>) - Method in class org.tribuo.data.DataOptions
Loads the training and testing data from DataOptions.trainingPath and DataOptions.testingPath according to the other parameters specified in this class.
loadDataset(CommandInterpreter, File) - Method in class org.tribuo.data.DatasetExplorer
Loads a serialized dataset.
loadDataSource(URL, String) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(URL, String, String[]) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(URL, Set<String>) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(URL, Set<String>, String[]) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(Path, String) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(Path, String, String[]) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(Path, Set<String>) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(Path, Set<String>, String[]) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadModel(CommandInterpreter, File) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Loads a model in from disk.
loadModel(CommandInterpreter, File) - Method in class org.tribuo.ModelExplorer
Loads a model.
loadModel(CommandInterpreter, File) - Method in class org.tribuo.sequence.SequenceModelExplorer
Loads a model.
localValues - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainCliqueValues
The per element values.
log - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Logs the inputs (base_e)
log() - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that applies Math.log(double).
LOG - Enum constant in enum class org.tribuo.classification.sgd.fm.FMClassificationOptions.LossEnum
Log loss (i.e., a logistic regression).
LOG - Enum constant in enum class org.tribuo.classification.sgd.linear.LinearSGDOptions.LossEnum
Log loss, i.e., cross-entropy.
LOG_2 - Static variable in class org.tribuo.util.infotheory.InformationTheory
Log base 2.
LOG_2 - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
Log base 2.
LOG_BASE - Static variable in class org.tribuo.util.infotheory.InformationTheory
Sets the base of the logarithm used in the information theoretic calculations.
LOG_BASE - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
Sets the base of the logarithm used in the information theoretic calculations.
LOG_E - Static variable in class org.tribuo.util.infotheory.InformationTheory
Log base e.
LOG_E - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
Log base e.
loggingInterval - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Log the objective after n examples.
loggingInterval - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
loggingInterval - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
loggingInterval - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Interval between logging the loss.
loggingInterval - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Log the objective after n examples.
loggingInterval - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
Log the objective after n examples.
LogisticRegressionTrainer - Class in org.tribuo.classification.sgd.linear
A logistic regression trainer that uses a reasonable objective, optimiser, number of epochs and minibatch size.
LogisticRegressionTrainer() - Constructor for class org.tribuo.classification.sgd.linear.LogisticRegressionTrainer
Constructs a simple logistic regression, using AdaGrad with a learning rate of 1.0 as the gradient optimizer, training for 5 epochs.
logModel - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Print out feature, label and other model details.
LogMulticlass - Class in org.tribuo.classification.sgd.objectives
A multiclass version of the log loss.
LogMulticlass() - Constructor for class org.tribuo.classification.sgd.objectives.LogMulticlass
Constructs a multiclass log loss.
logVector(Logger, Level, double[]) - Static method in class org.tribuo.util.Util
Logs the supplied array to the supplied logger at the specified level.
logVector(Logger, Level, float[]) - Static method in class org.tribuo.util.Util
Logs the supplied array to the supplied logger at the specified level.
logZ - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainBPResults
The normalization constant.
LongPair() - Constructor for class org.tribuo.util.MurmurHash3.LongPair
 
lookup(String) - Method in class org.tribuo.Example
Returns the Feature in this Example which has the supplied name, if it's present.
lookup(String) - Method in class org.tribuo.impl.ArrayExample
 
lookup(String) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
lookup(String) - Method in class org.tribuo.impl.ListExample
 
loss - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Loss function.
loss - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
Loss function.
loss() - Method in class org.tribuo.interop.tensorflow.LabelConverter
Returns a cross-entropy loss.
loss() - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
Returns a sigmoid cross-entropy loss.
loss() - Method in interface org.tribuo.interop.tensorflow.OutputConverter
The loss function associated with this prediction type.
loss() - Method in class org.tribuo.interop.tensorflow.RegressorConverter
Returns a mean squared error loss.
loss(DenseVector, SGDVector) - Method in class org.tribuo.regression.sgd.objectives.AbsoluteLoss
Deprecated.
loss(DenseVector, SGDVector) - Method in class org.tribuo.regression.sgd.objectives.Huber
Deprecated.
loss(DenseVector, SGDVector) - Method in class org.tribuo.regression.sgd.objectives.SquaredLoss
Deprecated.
loss(DenseVector, SGDVector) - Method in interface org.tribuo.regression.sgd.RegressionObjective
Deprecated.
In 4.1 to move to the new name, lossAndGradient.
lossAndGradient(Integer, SGDVector) - Method in interface org.tribuo.classification.sgd.LabelObjective
 
lossAndGradient(Integer, SGDVector) - Method in class org.tribuo.classification.sgd.objectives.Hinge
Returns a Pair of Double and SGDVector representing the loss and per label gradients respectively.
lossAndGradient(Integer, SGDVector) - Method in class org.tribuo.classification.sgd.objectives.LogMulticlass
Returns a Pair of Double and SGDVector representing the loss and per label gradients respectively.
lossAndGradient(DenseVector, SGDVector) - Method in class org.tribuo.regression.sgd.objectives.AbsoluteLoss
 
lossAndGradient(DenseVector, SGDVector) - Method in class org.tribuo.regression.sgd.objectives.Huber
 
lossAndGradient(DenseVector, SGDVector) - Method in class org.tribuo.regression.sgd.objectives.SquaredLoss
 
lossAndGradient(DenseVector, SGDVector) - Method in interface org.tribuo.regression.sgd.RegressionObjective
 
lossAndGradient(SGDVector, SGDVector) - Method in class org.tribuo.multilabel.sgd.objectives.BinaryCrossEntropy
Returns a Pair of Double and SGDVector representing the loss and per label gradients respectively.
lossAndGradient(SGDVector, SGDVector) - Method in class org.tribuo.multilabel.sgd.objectives.Hinge
Returns a Pair of Double and SGDVector representing the loss and per label gradients respectively.
lossAndGradient(T, SGDVector) - Method in interface org.tribuo.common.sgd.SGDObjective
Scores a prediction, returning the loss and a vector of per output dimension gradients.
LOWERCASE - Enum constant in enum class org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Lowercase the input text.

M

m - Variable in class org.tribuo.FeatureMap
Map from the feature names to their info.
MACRO - Enum constant in enum class org.tribuo.evaluation.metrics.EvaluationMetric.Average
The macro average.
macroAveragedF1() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the macro averaged F_1 across all the labels.
macroAveragedF1() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The macro averaged F1.
macroAveragedF1() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
macroAveragedPrecision() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the macro averaged precision.
macroAveragedPrecision() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The macro averaged precision.
macroAveragedPrecision() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
macroAveragedRecall() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the macro averaged recall.
macroAveragedRecall() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The macro averaged recall.
macroAveragedRecall() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
macroAverageTarget() - Static method in class org.tribuo.evaluation.metrics.MetricTarget
Get the singleton MetricTarget which contains the EvaluationMetric.Average.MACRO.
macroFN() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the macro averaged number of false negatives.
macroFN() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the macro averaged false negative count.
macroFN() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
macroFP() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the macro averaged number of false positives, averaged across the labels.
macroFP() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the macro averaged false positive count.
macroFP() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
macroTN() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the macro averaged number of true negatives.
macroTN() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the macro averaged true negative count.
macroTN() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
macroTP() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the macro averaged number of true positives, averaged across the labels.
macroTP() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the macro averaged true positive count.
macroTP() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
mae() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates the Mean Absolute Error for all dimensions.
mae(MetricTarget<Regressor>, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the Mean Absolute Error based on the supplied statistics.
mae(Regressor) - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates the Mean Absolute Error for that dimension.
mae(Regressor, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the Mean Absolute Error based on the supplied statistics for a single dimension.
MAE - Enum constant in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the Mean Absolute Error of the predictions.
MAE - Enum constant in enum class org.tribuo.regression.rtree.TrainTest.ImpurityType
main(String[]) - Static method in class org.tribuo.classification.dtree.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.classification.experiments.ConfigurableTrainTest
 
main(String[]) - Static method in class org.tribuo.classification.experiments.RunAll
Runs the RunALL CLI.
main(String[]) - Static method in class org.tribuo.classification.experiments.Test
Runs the Test CLI.
main(String[]) - Static method in class org.tribuo.classification.experiments.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Runs a LIMETextCLI.
main(String[]) - Static method in class org.tribuo.classification.liblinear.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.classification.libsvm.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.classification.mnb.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.classification.sequence.SeqTrainTest
 
main(String[]) - Static method in class org.tribuo.classification.sgd.crf.SeqTest
 
main(String[]) - Static method in class org.tribuo.classification.sgd.fm.TrainTest
 
main(String[]) - Static method in class org.tribuo.classification.sgd.kernel.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.classification.sgd.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.classification.xgboost.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.clustering.hdbscan.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.clustering.kmeans.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.data.CompletelyConfigurableTrainTest
 
main(String[]) - Static method in class org.tribuo.data.ConfigurableTrainTest
 
main(String[]) - Static method in class org.tribuo.data.DatasetExplorer
Runs a dataset explorer.
main(String[]) - Static method in class org.tribuo.data.PreprocessAndSerialize
Run the PreprocessAndSerialize CLI.
main(String[]) - Static method in class org.tribuo.data.sql.SQLToCSV
Reads an SQL query from the standard input and writes the results of the query to the standard output.
main(String[]) - Static method in class org.tribuo.data.text.SplitTextData
Runs the SplitTextData CLI.
main(String[]) - Static method in class org.tribuo.interop.oci.OCIModelCLI
Entry point for the OCIModelCLI.
main(String[]) - Static method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Test harness for running a BERT model and inspecting the output.
main(String[]) - Static method in class org.tribuo.interop.tensorflow.TrainTest
CLI entry point.
main(String[]) - Static method in class org.tribuo.json.StripProvenance
Runs StripProvenance.
main(String[]) - Static method in class org.tribuo.ModelExplorer
Entry point.
main(String[]) - Static method in class org.tribuo.regression.liblinear.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.regression.libsvm.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.regression.rtree.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.regression.sgd.fm.TrainTest
 
main(String[]) - Static method in class org.tribuo.regression.sgd.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.regression.slm.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.regression.xgboost.TrainTest
Runs a TrainTest CLI.
main(String[]) - Static method in class org.tribuo.sequence.SequenceModelExplorer
Runs the sequence model explorer.
main(String[]) - Static method in class org.tribuo.util.infotheory.example.InformationTheoryDemo
Runs a simple demo of the information theory functions.
MAJOR_VERSION - Static variable in class org.tribuo.Tribuo
The major version number.
makeAuthProvider(Path, String) - Static method in class org.tribuo.interop.oci.OCIModel
Makes an authentication provider from the config file and profile.
makeDefaultSource(int, long) - Static method in class org.tribuo.multilabel.example.MultiLabelGaussianDataSource
Generates a multi label output drawn from a series of functions.
makeIDInfo(int) - Method in class org.tribuo.CategoricalIDInfo
 
makeIDInfo(int) - Method in class org.tribuo.CategoricalInfo
 
makeIDInfo(int) - Method in class org.tribuo.RealIDInfo
 
makeIDInfo(int) - Method in class org.tribuo.RealInfo
 
makeIDInfo(int) - Method in interface org.tribuo.VariableInfo
Generates a VariableIDInfo subclass which represents the same feature.
makeTokens() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Make one or more tokens from our current collected characters.
mandatoryAttributeNames - Variable in enum class org.tribuo.util.onnx.ONNXOperators
The mandatory attribute names.
map(String, List<Feature>) - Method in interface org.tribuo.data.text.FeatureTransformer
Transforms features into a new list of features
map(String, List<Feature>) - Method in class org.tribuo.data.text.impl.FeatureHasher
 
MAP_TYPE - Enum constant in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
MAP_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto
 
mapScore - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainViterbiResults
The score for this result.
mapValues - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainViterbiResults
The viterbi states.
MASK_VALUE - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Mask value.
MATCH_ALL - Enum constant in enum class org.tribuo.data.columnar.processors.field.RegexFieldProcessor.Mode
Triggers feature generation if the whole string matches.
MATCH_CONTAINS - Enum constant in enum class org.tribuo.data.columnar.processors.field.RegexFieldProcessor.Mode
Triggers feature generation if the string contains a match.
Matrix - Interface in org.tribuo.math.la
Interface for 2 dimensional Tensors.
MatrixHeapMerger - Class in org.tribuo.math.util
Merges each DenseSparseMatrix using a PriorityQueue as a heap on the MatrixIterator.
MatrixHeapMerger() - Constructor for class org.tribuo.math.util.MatrixHeapMerger
 
MatrixIterator - Interface in org.tribuo.math.la
matrixMultiply(Matrix) - Method in class org.tribuo.math.la.DenseMatrix
 
matrixMultiply(Matrix) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
matrixMultiply(Matrix) - Method in interface org.tribuo.math.la.Matrix
Multiplies this Matrix by another Matrix returning a matrix of the appropriate size.
matrixMultiply(Matrix, boolean, boolean) - Method in class org.tribuo.math.la.DenseMatrix
 
matrixMultiply(Matrix, boolean, boolean) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
matrixMultiply(Matrix, boolean, boolean) - Method in interface org.tribuo.math.la.Matrix
Multiplies this Matrix by another Matrix returning a matrix of the appropriate size.
MatrixTuple - Class in org.tribuo.math.la
A mutable tuple used to avoid allocation when iterating a matrix.
MatrixTuple() - Constructor for class org.tribuo.math.la.MatrixTuple
Constructs an empty matrix tuple.
MatrixTuple(int, int, int) - Constructor for class org.tribuo.math.la.MatrixTuple
Constructs a matrix tuple with the specified values.
max - Variable in class org.tribuo.RealInfo
The maximum observed feature value.
max() - Static method in interface org.tribuo.util.Merger
A merger which takes the maximum element.
MAX - Enum constant in enum class org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Select the maximum feature value in the list.
maxDepth - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
Maximum tree depth.
maxIterations - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
maxIterations - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
Max iterations over the data.
maxMap - Variable in class org.tribuo.regression.RegressionInfo
 
maxNumFeatures - Variable in class org.tribuo.regression.slm.SLMTrainer
 
maxNumFeatures - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
Set the maximum number of features.
maxTokenLength - Variable in class org.tribuo.util.tokens.universal.UniversalTokenizer
The length of the longest token that we will generate.
maxValue() - Method in class org.tribuo.math.la.DenseVector
 
maxValue() - Method in interface org.tribuo.math.la.SGDVector
Returns the maximum value.
maxValue() - Method in class org.tribuo.math.la.SparseVector
 
maxValue() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
MCSVM_CS - Enum constant in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
multi-class support vector classification by Crammer and Singer
mean - Variable in class org.tribuo.RealInfo
The feature mean.
mean(double[]) - Static method in class org.tribuo.util.Util
Returns the mean of the input array.
mean(double[], int) - Static method in class org.tribuo.util.Util
Computes the mean of the first length elements of array.
mean(Collection<V>) - Static method in class org.tribuo.util.Util
Computes the mean of the collection.
MEAN - Enum constant in enum class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.OutputPooling
Takes the average of all the token embeddings
MEAN - Enum constant in enum class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns the mean of the training data outputs.
MeanAbsoluteError - Class in org.tribuo.regression.rtree.impurity
Measures the mean absolute error over a set of inputs.
MeanAbsoluteError() - Constructor for class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
 
meanAndVariance(double[]) - Static method in class org.tribuo.util.Util
Returns the mean and variance of the input.
meanAndVariance(double[], int) - Static method in class org.tribuo.util.Util
Returns the mean and variance of the input's first length elements.
meanMap - Variable in class org.tribuo.regression.RegressionInfo
 
MeanSquaredError - Class in org.tribuo.regression.rtree.impurity
Measures the mean squared error over a set of inputs.
MeanSquaredError() - Constructor for class org.tribuo.regression.rtree.impurity.MeanSquaredError
 
MeanStdDevTransformation - Class in org.tribuo.transform.transformations
A Transformation which takes an observed distribution and rescales it so it has the desired mean and standard deviation.
MeanStdDevTransformation() - Constructor for class org.tribuo.transform.transformations.MeanStdDevTransformation
Defaults to zero mean, one std dev.
MeanStdDevTransformation(double, double) - Constructor for class org.tribuo.transform.transformations.MeanStdDevTransformation
Constructs a MeanStdDevTransformation targetting the specified mean and standard deviation.
MeanStdDevTransformation.MeanStdDevTransformationProvenance - Class in org.tribuo.transform.transformations
Provenance for MeanStdDevTransformation.
MeanStdDevTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
Deserialization constructor.
MeanVarianceAccumulator - Class in org.tribuo.util
An accumulator for online calculation of the mean and variance of a stream of doubles.
MeanVarianceAccumulator() - Constructor for class org.tribuo.util.MeanVarianceAccumulator
Constructs an empty mean/variance accumulator.
MeanVarianceAccumulator(double[]) - Constructor for class org.tribuo.util.MeanVarianceAccumulator
Constructs a mean/variance accumulator and observes the supplied array.
MeanVarianceAccumulator(MeanVarianceAccumulator) - Constructor for class org.tribuo.util.MeanVarianceAccumulator
Copy constructor.
measureDistance(ImmutableFeatureMap, long, SparseVector, SparseVector) - Static method in class org.tribuo.classification.explanations.lime.LIMEBase
Measures the distance between an input point and a sampled point.
MEDIAN - Enum constant in enum class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns the median of the training data outputs.
MEMBERS - Static variable in class org.tribuo.provenance.EnsembleModelProvenance
The name of the provenance field where the member provenances are stored.
merge(double, double) - Method in interface org.tribuo.util.Merger
Merges first and second.
merge(List<int[]>, IntArrayContainer, IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
Merges the list of int arrays into a single int array, using the two supplied buffers.
merge(List<SparseVector>, int, int[], double[]) - Static method in class org.tribuo.math.util.HeapMerger
Merges a list of sparse vectors into a single sparse vector, summing the values.
merge(IntArrayContainer, int[], IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
Merges input and otherArray writing to output.
merge(DenseSparseMatrix[]) - Method in class org.tribuo.math.util.HeapMerger
 
merge(DenseSparseMatrix[]) - Method in class org.tribuo.math.util.MatrixHeapMerger
 
merge(DenseSparseMatrix[]) - Method in interface org.tribuo.math.util.Merger
Merges an array of DenseSparseMatrix into a single DenseSparseMatrix.
merge(SparseVector[]) - Method in class org.tribuo.math.util.HeapMerger
 
merge(SparseVector[]) - Method in class org.tribuo.math.util.MatrixHeapMerger
 
merge(SparseVector[]) - Method in interface org.tribuo.math.util.Merger
Merges an array of SparseVector into a single SparseVector.
merge(Tensor[][], int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
 
merge(Tensor[][], int) - Method in class org.tribuo.common.sgd.FMParameters
 
merge(Tensor[][], int) - Method in class org.tribuo.math.LinearParameters
 
merge(Tensor[][], int) - Method in interface org.tribuo.math.Parameters
Merge together an array of gradient arrays.
mergeAlgorithm(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
mergeElemType(OnnxMl.TypeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
mergeFrom(OnnxMl.AttributeProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
mergeFrom(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
mergeFrom(OnnxMl.ModelProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
mergeFrom(OnnxMl.NodeProto) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
mergeFrom(OnnxMl.OperatorSetIdProto) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
mergeFrom(OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
mergeFrom(OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
mergeFrom(OnnxMl.TensorAnnotation) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
mergeFrom(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
mergeFrom(OnnxMl.TensorProto.Segment) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
mergeFrom(OnnxMl.TensorShapeProto) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
mergeFrom(OnnxMl.TensorShapeProto.Dimension) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
mergeFrom(OnnxMl.TrainingInfoProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
mergeFrom(OnnxMl.TypeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
mergeFrom(OnnxMl.TypeProto.Map) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
mergeFrom(OnnxMl.TypeProto.Opaque) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
mergeFrom(OnnxMl.TypeProto.Sequence) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
mergeFrom(OnnxMl.TypeProto.SparseTensor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
mergeFrom(OnnxMl.TypeProto.Tensor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
mergeFrom(OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
mergeFrom(CodedInputStream, ExtensionRegistryLite) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
mergeFrom(Message) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
mergeG(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
mergeGraph(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
mergeIndices(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
mergeInitialization(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
mergeMapType(OnnxMl.TypeProto.Map) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
mergeOpaqueType(OnnxMl.TypeProto.Opaque) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
Merger - Interface in org.tribuo.math.util
An interface for merging an array of DenseSparseMatrix into a single DenseSparseMatrix.
Merger - Interface in org.tribuo.util
An interface which can merge double values.
mergeSegment(OnnxMl.TensorProto.Segment) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
mergeSequenceType(OnnxMl.TypeProto.Sequence) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
mergeShape(OnnxMl.TensorShapeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
mergeShape(OnnxMl.TensorShapeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
mergeSparseTensor(OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
mergeSparseTensorType(OnnxMl.TypeProto.SparseTensor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
mergeT(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
mergeTensorType(OnnxMl.TypeProto.Tensor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
mergeType(OnnxMl.TypeProto) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
mergeUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
mergeValues(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
mergeValueType(OnnxMl.TypeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
MessageDigestHasher - Class in org.tribuo.hash
Hashes Strings using the supplied MessageDigest type.
MessageDigestHasher(String, String) - Constructor for class org.tribuo.hash.MessageDigestHasher
Constructs a message digest hasher.
MessageDigestHasher.MessageDigestHasherProvenance - Class in org.tribuo.hash
Provenance for MessageDigestHasher.
MessageDigestHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
Deserialization constructor.
metadata - Variable in class org.tribuo.Example
The example metadata.
METADATA_PROPS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
metadataName - Variable in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
 
MetricContext<T extends Output<T>> - Class in org.tribuo.evaluation.metrics
The context for a metric or set of metrics.
MetricContext(Model<T>, List<Prediction<T>>) - Constructor for class org.tribuo.evaluation.metrics.MetricContext
 
MetricContext(SequenceModel<T>, List<Prediction<T>>) - Constructor for class org.tribuo.evaluation.metrics.MetricContext
 
MetricID<T extends Output<T>> - Class in org.tribuo.evaluation.metrics
Just an easier-to-read alias for Pair<MetricTarget<T>, String>.
MetricID(MetricTarget<T>, String) - Constructor for class org.tribuo.evaluation.metrics.MetricID
Constructs a metric id.
MetricTarget<T extends Output<T>> - Class in org.tribuo.evaluation.metrics
Used by a given EvaluationMetric to determine whether it should compute its value for a specific Output value or whether it should average them.
MetricTarget(EvaluationMetric.Average) - Constructor for class org.tribuo.evaluation.metrics.MetricTarget
Builds a metric target for an average.
MetricTarget(T) - Constructor for class org.tribuo.evaluation.metrics.MetricTarget
Builds a metric target for an output.
mi(ArrayList<T1>, ArrayList<T2>, ArrayList<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted mutual information, using histogram probability estimators.
mi(List<T1>, List<T2>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon mutual information, using histogram probability estimators.
mi(Set<List<T1>>, Set<List<T2>>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the mutual information between the two sets of random variables.
mi(PairDistribution<T1, T2>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon mutual information, using histogram probability estimators.
mi(PairDistribution<T1, T2>, Map<?, Double>, WeightedInformationTheory.VariableSelector) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted mutual information, using histogram probability estimators.
mi(WeightedPairDistribution<T1, T2>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete weighted mutual information, using histogram probability estimators.
MICRO - Enum constant in enum class org.tribuo.evaluation.metrics.EvaluationMetric.Average
The micro average.
microAveragedF1() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the micro averaged F_1 across all labels.
microAveragedF1() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The micro averaged F1.
microAveragedF1() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
microAveragedPrecision() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the micro averaged precision.
microAveragedPrecision() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The micro averaged precision.
microAveragedPrecision() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
microAveragedRecall() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the micro averaged recall.
microAveragedRecall() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The micro averaged recall.
microAveragedRecall() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
microAverageTarget() - Static method in class org.tribuo.evaluation.metrics.MetricTarget
Get the singleton MetricTarget which contains the EvaluationMetric.Average.MICRO.
min - Variable in class org.tribuo.RealInfo
The minimum observed feature value.
min() - Static method in interface org.tribuo.util.Merger
A merger which takes the minimum element.
MIN - Enum constant in enum class org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Select the minimum feature value in the list.
MIN_EXAMPLES - Static variable in class org.tribuo.common.tree.AbstractCARTTrainer
Default minimum weight of examples allowed in a leaf node.
MIN_LENGTH - Static variable in class org.tribuo.hash.Hasher
The minimum length of the salt.
minChildWeight - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
Minimum weight of examples allowed in a leaf.
minChildWeight - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Minimum child weight.
minClusterSize - Variable in class org.tribuo.clustering.hdbscan.HdbscanOptions
The minimum number of points required to form a cluster.
minCount - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
Remove features which occur fewer than m times.
minCount - Variable in class org.tribuo.data.DataOptions
Minimum cardinality of the features.
minCount(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Shows the number of features that occurred more than minCount times.
minCount(CommandInterpreter, int) - Method in class org.tribuo.data.DatasetExplorer
Shows the number of features which occurred more than minCount times in the dataset.
minCount(CommandInterpreter, int) - Method in class org.tribuo.ModelExplorer
Shows the number of features which occurred more than min count times.
minCount(CommandInterpreter, int) - Method in class org.tribuo.sequence.SequenceModelExplorer
Shows the number of features which occurred more than minCount times in the training data.
minibatchSize - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
minibatchSize - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
minibatchSize - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Minibatch size.
minibatchSize - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
Minibatch size.
minImpurityDecrease - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
Minimum impurity decrease.
minImpurityDecrease - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Minimumum decrease in impurity required in order for the node to be split.
MinimumCardinalityDataset<T extends Output<T>> - Class in org.tribuo.dataset
This class creates a pruned dataset in which low frequency features that occur less than the provided minimum cardinality have been removed.
MinimumCardinalityDataset(Dataset<T>, int) - Constructor for class org.tribuo.dataset.MinimumCardinalityDataset
 
MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance - Class in org.tribuo.dataset
MinimumCardinalityDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.dataset.MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance
Deserialization constructor.
MinimumCardinalitySequenceDataset<T extends Output<T>> - Class in org.tribuo.sequence
This class creates a pruned dataset in which low frequency features that occur less than the provided minimum cardinality have been removed.
MinimumCardinalitySequenceDataset(SequenceDataset<T>, int) - Constructor for class org.tribuo.sequence.MinimumCardinalitySequenceDataset
 
MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance - Class in org.tribuo.sequence
MinimumCardinalitySequenceDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
Deserialization constructor.
minMap - Variable in class org.tribuo.regression.RegressionInfo
 
MINOR_VERSION - Static variable in class org.tribuo.Tribuo
The minor version number.
minValue() - Method in class org.tribuo.math.la.DenseVector
 
minValue() - Method in interface org.tribuo.math.la.SGDVector
Returns the minimum value.
minValue() - Method in class org.tribuo.math.la.SparseVector
 
minValue() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
minWeight - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Minimum sum of instance weights needed in a leaf (default 1, range [0,inf]).
minWeight - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Minimum sum of instance weights needed in a leaf (default 1, range [0,inf]).
mkTrainingNode(Dataset<Label>, AbstractTrainingNode.LeafDeterminer) - Method in class org.tribuo.classification.dtree.CARTClassificationTrainer
 
mkTrainingNode(Dataset<Regressor>, AbstractTrainingNode.LeafDeterminer) - Method in class org.tribuo.regression.rtree.CARTJointRegressionTrainer
 
mkTrainingNode(Dataset<Regressor>, AbstractTrainingNode.LeafDeterminer) - Method in class org.tribuo.regression.rtree.CARTRegressionTrainer
 
mkTrainingNode(Dataset<T>, AbstractTrainingNode.LeafDeterminer) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
Makes the initial training node.
MLPExamples - Class in org.tribuo.interop.tensorflow.example
Static factory methods which produce Multi-Layer Perceptron architectures.
MNB - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
mnbAlpha - Variable in class org.tribuo.classification.mnb.MultinomialNaiveBayesOptions
Smoothing parameter for the conditional probabilities.
mnbOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for Multinomial Naive Bayes trainers.
mnbOptions - Variable in class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
The multinomial naive bayes options.
MOD - Enum constant in enum class org.tribuo.hash.HashingOptions.ModelHashingType
Takes the String hash code mod some value.
mode - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Deploy or score an OCI DS model.
model - Variable in class org.tribuo.common.xgboost.XGBoostExternalModel
Transient as we rely upon the native serialisation mechanism to bytes rather than Java serializing the Booster.
model() - Method in record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Returns the value of the model record component.
Model<T extends Output<T>> - Class in org.tribuo
A prediction model, which is used to predict outputs for unseen instances.
Model(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean) - Constructor for class org.tribuo.Model
Constructs a new model, storing the supplied fields.
MODEL_VERSION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
modelDeploymentId - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
The id of the model deployment.
modelDescription - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
The model description.
modelDescription(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Shows the model description.
modelDescription(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer
Shows the model description.
modelDisplayName - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Model display name.
modelEquals(svm_model, svm_model) - Static method in class org.tribuo.common.libsvm.LibSVMModel
Checks for equality between two svm_models.
ModelExplorer - Class in org.tribuo
A command line interface for loading in models and inspecting their feature and output spaces.
ModelExplorer() - Constructor for class org.tribuo.ModelExplorer
Builds a new model explorer shell.
ModelExplorer.ModelExplorerOptions - Class in org.tribuo
CLI options for ModelExplorer.
ModelExplorerOptions() - Constructor for class org.tribuo.ModelExplorer.ModelExplorerOptions
 
modelFilename - Variable in class org.tribuo.classification.explanations.lime.LIMETextCLI.LIMETextCLIOptions
Model file to load.
modelFilename - Variable in class org.tribuo.data.DatasetExplorer.DatasetExplorerOptions
Dataset file to load.
modelFilename - Variable in class org.tribuo.ModelExplorer.ModelExplorerOptions
Model file to load.
modelFilename - Variable in class org.tribuo.sequence.SequenceModelExplorer.SequenceModelExplorerOptions
Model file to load.
modelGraph - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
modelHashingAlgorithm - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Hash the model during training.
modelHashingAlgorithm - Variable in class org.tribuo.hash.HashingOptions
Hash the model during training, options are {NONE,MOD,HC,SHA1,SHA256}
modelHashingSalt - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Salt for hashing the model.
modelHashingSalt - Variable in class org.tribuo.hash.HashingOptions
Salt for hashing the model
modelId - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
The id of the model.
modelID - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelDeploymentConfig
The ID of the model artifact to deploy.
modelName - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
The model display name.
modelParameters - Variable in class org.tribuo.common.sgd.AbstractSGDModel
The weights for this model.
modelPath - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Load a trainer from the config file.
modelPath - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Path to the serialized model to deploy to OCI DS.
modelProvenance(CommandInterpreter) - Method in class org.tribuo.ModelExplorer
Displays the model provenance.
ModelProvenance - Class in org.tribuo.provenance
Contains provenance information for an instance of a Model.
ModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance) - Constructor for class org.tribuo.provenance.ModelProvenance
Creates a model provenance tracking the class name, creation time, dataset provenance and trainer provenance.
ModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>) - Constructor for class org.tribuo.provenance.ModelProvenance
Creates a model provenance tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance.
ModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>, boolean) - Constructor for class org.tribuo.provenance.ModelProvenance
Creates a model provenance tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance.
ModelProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.ModelProvenance
Used by the provenance unmarshalling system.
ModelReproduction(Model<T>, ReproUtil.FeatureDiff, ReproUtil.OutputDiff<T>, String) - Constructor for record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Creates an instance of a ModelReproduction record class.
models - Variable in class org.tribuo.common.liblinear.LibLinearModel
The list of LibLinear models.
models - Variable in class org.tribuo.common.libsvm.LibSVMModel
The LibSVM models.
models - Variable in class org.tribuo.common.xgboost.XGBoostModel
The XGBoost4J Boosters.
models - Variable in class org.tribuo.ensemble.EnsembleModel
 
modelType - Variable in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
OCI DS model type string.
ModHashCodeHasher - Class in org.tribuo.hash
Hashes names using String.hashCode(), then reduces the dimension.
ModHashCodeHasher(int, String) - Constructor for class org.tribuo.hash.ModHashCodeHasher
Constructs a ModHashCodeHasher with the supplied parameters.
ModHashCodeHasher(String) - Constructor for class org.tribuo.hash.ModHashCodeHasher
Constructs a ModHashCodeHasher with a fixed dimensionality of 100.
ModHashCodeHasher.ModHashCodeHasherProvenance - Class in org.tribuo.hash
Provenance for the ModHashCodeHasher.
ModHashCodeHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
Deserialization constructor.
momentum - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
Use momentum in SGD.
MOMENTUM - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
Gradient descent with momentum.
MONTH - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The month.
MOST_FREQUENT - Enum constant in enum class org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Returns the most frequent training label.
MSE - Enum constant in enum class org.tribuo.regression.rtree.TrainTest.ImpurityType
mStep(ForkJoinPool, DenseVector[], Map<Integer, List<Integer>>, SGDVector[], double[]) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
Runs the mStep, writing to the centroidVectors array.
mul - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Multiplies by the specified constant.
mul(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that multiplies each value by the operand.
MUL - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Element-wise multiplication with broadcasting.
multiDimDenseTrainTest() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}.
multiDimDenseTrainTest(double) - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}.
multiDimSparseTrainTest() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
multiDimSparseTrainTest(double) - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
MultiLabel - Class in org.tribuo.multilabel
A class for multi-label classification.
MultiLabel(String) - Constructor for class org.tribuo.multilabel.MultiLabel
Builds a MultiLabel with a single String label.
MultiLabel(Set<Label>) - Constructor for class org.tribuo.multilabel.MultiLabel
Builds a MultiLabel object from a Set of Labels.
MultiLabel(Set<Label>, double) - Constructor for class org.tribuo.multilabel.MultiLabel
Builds a MultiLabel object from a Set of Labels, when the whole set has a score as well as (optionally) the individual labels.
MultiLabel(Label) - Constructor for class org.tribuo.multilabel.MultiLabel
Builds a MultiLabel from a single Label.
MultiLabelConfusionMatrix - Class in org.tribuo.multilabel.evaluation
A ConfusionMatrix which accepts MultiLabels.
MultiLabelConfusionMatrix(Model<MultiLabel>, List<Prediction<MultiLabel>>) - Constructor for class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
Constructs a multi-label confusion matrix for the specified model and predictions.
MultiLabelConverter - Class in org.tribuo.interop.tensorflow
Can convert a MultiLabel into a Tensor containing a binary encoding of the label vector and can convert a TFloat16 or TFloat32 into a Prediction or a MultiLabel.
MultiLabelConverter() - Constructor for class org.tribuo.interop.tensorflow.MultiLabelConverter
Constructs a MultiLabelConverter.
MultiLabelDataGenerator - Class in org.tribuo.multilabel.example
Generates three example train and test datasets, used for unit testing.
MultiLabelEvaluation - Interface in org.tribuo.multilabel.evaluation
MultiLabelEvaluationImpl - Class in org.tribuo.multilabel.evaluation
The implementation of a MultiLabelEvaluation using the default metrics.
MultiLabelEvaluator - Class in org.tribuo.multilabel.evaluation
An Evaluator for MultiLabel problems.
MultiLabelEvaluator() - Constructor for class org.tribuo.multilabel.evaluation.MultiLabelEvaluator
 
MultiLabelFactory - Class in org.tribuo.multilabel
A factory for generating MultiLabel objects and their associated OutputInfo and Evaluator objects.
MultiLabelFactory() - Constructor for class org.tribuo.multilabel.MultiLabelFactory
Construct a MultiLabelFactory.
MultiLabelFactory.MultiLabelFactoryProvenance - Class in org.tribuo.multilabel
Provenance for MultiLabelFactory.
MultiLabelFactoryProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.multilabel.MultiLabelFactory.MultiLabelFactoryProvenance
Constructs a multi-label factory provenance from the empty marshalled form.
MultiLabelGaussianDataSource - Class in org.tribuo.multilabel.example
Generates a multi label output drawn from a series of functions.
MultiLabelGaussianDataSource(int, float[], float[], float[], float[], boolean[], float, float[], float[], long) - Constructor for class org.tribuo.multilabel.example.MultiLabelGaussianDataSource
Generates a multi-label output drawn from three gaussian functions.
MultiLabelGaussianDataSource.MultiLabelGaussianDataSourceProvenance - Class in org.tribuo.multilabel.example
MultiLabelGaussianDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.multilabel.example.MultiLabelGaussianDataSource.MultiLabelGaussianDataSourceProvenance
Constructs a provenance from the marshalled form.
MultiLabelInfo - Class in org.tribuo.multilabel
The base class for information about MultiLabel outputs.
MultiLabelMetric - Class in org.tribuo.multilabel.evaluation
A EvaluationMetric for evaluating MultiLabel problems.
MultiLabelMetric(MetricTarget<MultiLabel>, String, BiFunction<MetricTarget<MultiLabel>, MultiLabelMetric.Context, Double>) - Constructor for class org.tribuo.multilabel.evaluation.MultiLabelMetric
Constructs a multi-label metric.
MultiLabelMetrics - Enum Class in org.tribuo.multilabel.evaluation
An enum of the default MultiLabelMetrics supported by the multi-label classification evaluation package.
MultiLabelObjective - Interface in org.tribuo.multilabel.sgd
An interface for multi-label prediction objectives.
MultiLabelTransformer - Class in org.tribuo.interop.onnx
Can convert an OnnxValue into a Prediction or a MultiLabel.
MultiLabelTransformer() - Constructor for class org.tribuo.interop.onnx.MultiLabelTransformer
Constructs a MultiLabelTransformer with a threshold of MultiLabelTransformer.DEFAULT_THRESHOLD which assumes the model emits probabilities.
MultiLabelTransformer(double, boolean) - Constructor for class org.tribuo.interop.onnx.MultiLabelTransformer
Constructs a MultiLabelTransformer with the supplied threshold.
MultiLabelVotingCombiner - Class in org.tribuo.multilabel.ensemble
A combiner which performs a weighted or unweighted vote independently across the predicted labels in each multi-label.
MultiLabelVotingCombiner() - Constructor for class org.tribuo.multilabel.ensemble.MultiLabelVotingCombiner
Constructs a voting combiner.
MULTINOMIAL_CLASSIFICATION - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Multi-class classification, maps to Tribuo's Label.
MultinomialNaiveBayesModel - Class in org.tribuo.classification.mnb
A Model for multinomial Naive Bayes with Laplace smoothing.
MultinomialNaiveBayesOptions - Class in org.tribuo.classification.mnb
CLI options for a multinomial naive bayes model.
MultinomialNaiveBayesOptions() - Constructor for class org.tribuo.classification.mnb.MultinomialNaiveBayesOptions
 
MultinomialNaiveBayesTrainer - Class in org.tribuo.classification.mnb
A Trainer which trains a multinomial Naive Bayes model with Laplace smoothing.
MultinomialNaiveBayesTrainer() - Constructor for class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
Constructs a multinomial naive bayes trainer using a smoothing value of 1.0.
MultinomialNaiveBayesTrainer(double) - Constructor for class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
Constructs a multinomial naive bayes trainer with the specified smoothing value.
MULTIPLY - Enum constant in enum class org.tribuo.classification.sequence.viterbi.ViterbiModel.ScoreAggregation
Multiplies the scores.
MULTIPLY - Enum constant in enum class org.tribuo.classification.sgd.crf.CRFModel.ConfidenceType
Belief Propagation
multiplyWeights(List<Prediction<Label>>, List<SUB>) - Static method in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel
A scoring method which multiplies together the per prediction scores.
MurmurHash3 - Class in org.tribuo.util
The MurmurHash3 algorithm was created by Austin Appleby and placed in the public domain.
MurmurHash3() - Constructor for class org.tribuo.util.MurmurHash3
 
murmurhash3_x64_128(byte[], int, int, int, MurmurHash3.LongPair) - Static method in class org.tribuo.util.MurmurHash3
Returns the MurmurHash3_x64_128 hash, placing the result in "out".
murmurhash3_x86_32(byte[], int, int, int) - Static method in class org.tribuo.util.MurmurHash3
Returns the MurmurHash3_x86_32 hash.
murmurhash3_x86_32(CharSequence, int, int, int) - Static method in class org.tribuo.util.MurmurHash3
Returns the MurmurHash3_x86_32 hash of the UTF-8 bytes of the String without actually encoding the string to a temporary buffer.
MurmurHash3.LongPair - Class in org.tribuo.util
128 bits of state
MutableAnomalyInfo - Class in org.tribuo.anomaly
An MutableOutputInfo object for Events.
MutableClusteringInfo - Class in org.tribuo.clustering
A mutable ClusteringInfo.
MutableDataset<T extends Output<T>> - Class in org.tribuo
A MutableDataset is a Dataset with a MutableFeatureMap which grows over time.
MutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.MutableDataset
Creates a dataset from a data source.
MutableDataset(DataSource<T>) - Constructor for class org.tribuo.MutableDataset
Creates a dataset from a data source.
MutableDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.MutableDataset
Creates an empty dataset.
MutableFeatureMap - Class in org.tribuo
A feature map that can record new feature value observations.
MutableFeatureMap() - Constructor for class org.tribuo.MutableFeatureMap
Creates an empty feature map which converts high cardinality categorical variable infos into reals.
MutableFeatureMap(boolean) - Constructor for class org.tribuo.MutableFeatureMap
Creates an empty feature map which can optionally convert high cardinality categorical variable infos into reals.
MutableLabelInfo - Class in org.tribuo.classification
A mutable LabelInfo.
MutableLabelInfo(LabelInfo) - Constructor for class org.tribuo.classification.MutableLabelInfo
Constructs a mutable deep copy of the supplied label info.
MutableMultiLabelInfo - Class in org.tribuo.multilabel
A MutableOutputInfo for working with multi-label tasks.
MutableMultiLabelInfo(MultiLabelInfo) - Constructor for class org.tribuo.multilabel.MutableMultiLabelInfo
Construct a MutableMultiLabelInfo with it's state copied from another MultiLabelInfo.
MutableOutputInfo<T extends Output<T>> - Interface in org.tribuo
A mutable OutputInfo that can record observed output values.
MutableRegressionInfo - Class in org.tribuo.regression
MutableRegressionInfo(RegressionInfo) - Constructor for class org.tribuo.regression.MutableRegressionInfo
Constructs a mutable copy of the supplied regression info.
MutableSequenceDataset<T extends Output<T>> - Class in org.tribuo.sequence
A MutableSequenceDataset is a SequenceDataset with a MutableFeatureMap which grows over time.
MutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
Creates a dataset from a data source.
MutableSequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
Creates an empty sequence dataset.
MutableSequenceDataset(ImmutableSequenceDataset<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
Copies the immutable dataset into a mutable dataset.
MutableSequenceDataset(SequenceDataSource<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
Builds a dataset from the supplied data source.

N

NADAM - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The Nadam optimiser.
name - Variable in class org.tribuo.Feature
The feature name.
name - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple
The feature name.
name - Variable in class org.tribuo.Model
The model's name.
name - Variable in class org.tribuo.sequence.SequenceModel
 
name - Variable in class org.tribuo.SkeletalVariableInfo
The name of the feature.
NAME - Static variable in class org.tribuo.Example
By convention the example name is stored using this metadata key.
NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
 
NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
nameFeature(String, int) - Method in class org.tribuo.classification.explanations.lime.LIMEText
Generate the feature name by combining the word and index.
nameFeature(String, String, int) - Method in class org.tribuo.classification.explanations.lime.LIMEColumnar
Generate the feature name by combining the word and index.
NAMESPACE - Static variable in interface org.tribuo.data.columnar.FieldProcessor
The namespacing separator.
NEG - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Element-wise negation.
NEGATIVE_LABEL - Static variable in class org.tribuo.multilabel.MultiLabel
A Label representing the binary negative label.
NEGATIVE_LABEL_STRING - Static variable in class org.tribuo.multilabel.MultiLabel
The string for the binary negative label.
NEGATIVE_NAME - Static variable in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
The default negative response.
NER - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Named Entity Recognition, no strict Tribuo mapping.
NESTEROV - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
Gradient descent with Nesterov momentum.
NESTEROV - Enum constant in enum class org.tribuo.math.optimisers.SGD.Momentum
Nesterov momentum.
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
newBuilder() - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
newBuilder(OnnxMl.AttributeProto) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
newBuilder(OnnxMl.GraphProto) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
newBuilder(OnnxMl.ModelProto) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
newBuilder(OnnxMl.NodeProto) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
newBuilder(OnnxMl.OperatorSetIdProto) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
newBuilder(OnnxMl.SparseTensorProto) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
newBuilder(OnnxMl.StringStringEntryProto) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
newBuilder(OnnxMl.TensorAnnotation) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
newBuilder(OnnxMl.TensorProto) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
newBuilder(OnnxMl.TensorProto.Segment) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
newBuilder(OnnxMl.TensorShapeProto) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
newBuilder(OnnxMl.TensorShapeProto.Dimension) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
newBuilder(OnnxMl.TrainingInfoProto) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
newBuilder(OnnxMl.TypeProto) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
newBuilder(OnnxMl.TypeProto.Map) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
newBuilder(OnnxMl.TypeProto.Opaque) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
newBuilder(OnnxMl.TypeProto.Sequence) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
newBuilder(OnnxMl.TypeProto.SparseTensor) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
newBuilder(OnnxMl.TypeProto.Tensor) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
newBuilder(OnnxMl.ValueInfoProto) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
newBuilderForType() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
newBuilderForType(GeneratedMessageV3.BuilderParent) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
newCapacity(int) - Method in class org.tribuo.impl.ArrayExample
Returns a capacity at least as large as the given minimum capacity.
newCapacity(int) - Method in class org.tribuo.impl.BinaryFeaturesExample
Returns a capacity at least as large as the given minimum capacity.
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
newInstance(GeneratedMessageV3.UnusedPrivateParameter) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
NewsPreprocessor - Class in org.tribuo.data.text.impl
A document pre-processor for 20 newsgroup data.
NewsPreprocessor() - Constructor for class org.tribuo.data.text.impl.NewsPreprocessor
Constructor.
newWeights(SLMTrainer.SLMState) - Method in class org.tribuo.regression.slm.LARSLassoTrainer
 
newWeights(SLMTrainer.SLMState) - Method in class org.tribuo.regression.slm.LARSTrainer
 
newWeights(SLMTrainer.SLMState) - Method in class org.tribuo.regression.slm.SLMTrainer
 
next() - Method in class org.tribuo.data.columnar.ColumnarIterator
 
ngram - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Ngram size to generate when using standard text format.
ngram - Variable in class org.tribuo.data.DataOptions
Ngram size to generate when using standard text format.
NGRAM - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
An NGRAM corresponds to a token that might correspond to a character ngram - i.e.
NgramProcessor - Class in org.tribuo.data.text.impl
A text processor that will generate token ngrams of a particular size.
NgramProcessor(Tokenizer, int, double) - Constructor for class org.tribuo.data.text.impl.NgramProcessor
Creates a processor that will generate token ngrams of size n.
NO_SPLIT - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
the current character is added to the in-progress token (i.e.
NO_SPLIT_INFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is infix.
NO_SPLIT_NGRAM - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is a ngram.
NO_SPLIT_PREFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is a prefix.
NO_SPLIT_PUNCTUATION - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is punctuation.
NO_SPLIT_SUFFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is a suffix.
NO_SPLIT_UNKNOWN - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is unknown.
NO_SPLIT_WHITESPACE - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is whitespace.
NO_SPLIT_WORD - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Not a split, is a word.
Node<T extends Output<T>> - Interface in org.tribuo.common.tree
A node in a decision tree.
NODE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
NoisyInterlockingCrescentsDataSource - Class in org.tribuo.classification.example
A data source of two interleaved half circles with some zero mean Gaussian noise applied to each point.
NoisyInterlockingCrescentsDataSource(int, long, double) - Constructor for class org.tribuo.classification.example.NoisyInterlockingCrescentsDataSource
Constructs a noisy interlocking crescents data source.
NON - Enum constant in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
Creates a NonTokenizer.
NONE - Enum constant in enum class org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions.ViterbiLabelFeatures
No label features.
NONE - Enum constant in enum class org.tribuo.classification.sgd.crf.CRFModel.ConfidenceType
No confidence predction.
NONE - Enum constant in enum class org.tribuo.hash.HashingOptions.ModelHashingType
No hashing applied.
NONE - Enum constant in enum class org.tribuo.math.optimisers.SGD.Momentum
No momentum.
NonlinearGaussianDataSource - Class in org.tribuo.regression.example
Generates a single dimensional output drawn from N(w_0*x_0 + w_1*x_1 + w_2*x_1*x_0 + w_3*x_1*x_1*x_1 + intercept,variance).
NonlinearGaussianDataSource(int, float[], float, float, float, float, float, float, long) - Constructor for class org.tribuo.regression.example.NonlinearGaussianDataSource
Generates a single dimensional output drawn from N(w_0*x_0 + w_1*x_1 + w_2*x_1*x_0 + w_3*x_1*x_1*x_1 + intercept,variance).
NonlinearGaussianDataSource(int, long) - Constructor for class org.tribuo.regression.example.NonlinearGaussianDataSource
Generates a single dimensional output drawn from N(w_0*x_0 + w_1*x_1 + w_2*x_1*x_0 + w_3*x_1*x_1*x_1 + intercept,variance).
NonlinearGaussianDataSource.NonlinearGaussianDataSourceProvenance - Class in org.tribuo.regression.example
NonlinearGaussianDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.regression.example.NonlinearGaussianDataSource.NonlinearGaussianDataSourceProvenance
Constructs a provenance from the marshalled form.
NonTokenizer - Class in org.tribuo.util.tokens.impl
A convenience class for when you are required to provide a tokenizer but you don't actually want to split up the text into tokens.
NonTokenizer() - Constructor for class org.tribuo.util.tokens.impl.NonTokenizer
Constructs a NonTokenizer.
NoopFeatureExtractor - Class in org.tribuo.classification.sequence.viterbi
A label feature extractor that doesn't produce any label based features.
NoopFeatureExtractor() - Constructor for class org.tribuo.classification.sequence.viterbi.NoopFeatureExtractor
 
NoopNormalizer - Class in org.tribuo.math.util
NoopNormalizer returns a copy in NoopNormalizer.normalize(double[]) and is a no-op in place.
NoopNormalizer() - Constructor for class org.tribuo.math.util.NoopNormalizer
 
normaliseWeights(Map<T, WeightCountTuple>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Normalizes the weights in the map, i.e., divides each weight by it's count.
normalize - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Normalize the leaf outputs so each leaf sums to 1.0.
normalize - Variable in class org.tribuo.regression.slm.SLMTrainer
 
normalize(double[]) - Method in class org.tribuo.math.util.ExpNormalizer
 
normalize(double[]) - Method in class org.tribuo.math.util.NoopNormalizer
 
normalize(double[]) - Method in class org.tribuo.math.util.Normalizer
 
normalize(double[]) - Method in class org.tribuo.math.util.SigmoidNormalizer
 
normalize(double[]) - Method in interface org.tribuo.math.util.VectorNormalizer
Normalizes the input array in some fashion specified by the class.
normalize(VectorNormalizer) - Method in class org.tribuo.math.la.DenseVector
 
normalize(VectorNormalizer) - Method in interface org.tribuo.math.la.SGDVector
Normalizes the vector using the supplied vector normalizer.
normalize(VectorNormalizer) - Method in class org.tribuo.math.la.SparseVector
 
NORMALIZED_MI - Enum constant in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
The normalized mutual information between the two clusterings
normalizedMI() - Method in interface org.tribuo.clustering.evaluation.ClusteringEvaluation
Calculates the normalized MI between the ground truth clustering ids and the predicted ones.
normalizedMI(ClusteringMetric.Context) - Static method in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
Calculates the normalized mutual information between two clusterings.
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.ExpNormalizer
 
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.NoopNormalizer
 
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.Normalizer
 
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.SigmoidNormalizer
 
normalizeInPlace(double[]) - Method in interface org.tribuo.math.util.VectorNormalizer
In place normalization of the array.
Normalizer - Class in org.tribuo.math.util
Normalizes, but first subtracts the minimum value (to ensure positivity).
Normalizer() - Constructor for class org.tribuo.math.util.Normalizer
 
normalizeRows(VectorNormalizer) - Method in class org.tribuo.math.la.DenseMatrix
Normalizes each row using the supplied normalizer in place.
normalizeToDistribution(double[]) - Static method in class org.tribuo.util.Util
Generates a normalized version of the input array.
normalizeToDistribution(float[]) - Static method in class org.tribuo.util.Util
Generates a normalized version of the input array.
nsplits - Variable in class org.tribuo.evaluation.KFoldSplitter
 
NU_SVC - Enum constant in enum class org.tribuo.classification.libsvm.SVMClassificationType.SVMMode
Classification SVM, optimization in dual space.
NU_SVR - Enum constant in enum class org.tribuo.regression.libsvm.SVMRegressionType.SVMMode
optimization in dual space.
numActiveElements() - Method in class org.tribuo.math.la.DenseVector
 
numActiveElements() - Method in interface org.tribuo.math.la.SGDVector
Returns the number of non-zero elements (on construction, an element could be set to zero and it would still remain active).
numActiveElements() - Method in class org.tribuo.math.la.SparseVector
 
numActiveElements(int) - Method in class org.tribuo.math.la.DenseMatrix
 
numActiveElements(int) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
numActiveElements(int) - Method in interface org.tribuo.math.la.Matrix
The number of non-zero elements in that row.
numActiveFeatures - Variable in class org.tribuo.common.sgd.AbstractSGDModel.PredAndActive
The number of active features used in the prediction.
numExamples - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
numExamples(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
Shows the number of examples in this dataset.
numFeatures(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Shows the number of features.
numFeatures(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
Shows the number of features in this dataset.
numFeatures(CommandInterpreter) - Method in class org.tribuo.ModelExplorer
Displays the number of features.
numFeatures(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer
Shows the number of features in this model.
numFolds - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
The number of cross validation folds.
numInputs - Variable in enum class org.tribuo.util.onnx.ONNXOperators
The number of inputs.
numMembers - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
numMembers - Variable in class org.tribuo.ensemble.BaggingTrainer
 
numOptionalInputs - Variable in enum class org.tribuo.util.onnx.ONNXOperators
The number of optional inputs.
numOutputs - Variable in enum class org.tribuo.util.onnx.ONNXOperators
The number of outputs.
numSamples - Variable in class org.tribuo.classification.example.DemoLabelDataSource
 
numSamples - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
numStates - Variable in class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
The number of states.
numThreads - Variable in class org.tribuo.clustering.hdbscan.HdbscanOptions
Number of threads to use for training the hdbscan model.
numThreads - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
Number of computation threads in K-Means.
numThreads - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
Number of threads to use (range (1, num hw threads)).
numThreads - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Number of threads to use (default 4, range (1, num hw threads)).
numThreads - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Number of threads to use (default 4, range (1, num hw threads)).
numTrainingExamples - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
numTrees - Variable in class org.tribuo.common.xgboost.XGBoostTrainer
 
numValidFeatures - Variable in class org.tribuo.common.xgboost.XGBoostTrainer.DMatrixTuple
 

O

OBJECT_LOCALIZATION - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Object localization, no Tribuo mapping.
observe(double) - Method in class org.tribuo.CategoricalInfo
 
observe(double) - Method in class org.tribuo.RealInfo
 
observe(double) - Method in class org.tribuo.SkeletalVariableInfo
Records the value.
observe(double) - Method in class org.tribuo.util.MeanVarianceAccumulator
Observes a value, i.e., updates the sufficient statistics for computing mean, variance, max and min.
observe(double[]) - Method in class org.tribuo.util.MeanVarianceAccumulator
Observes a value, i.e., updates the sufficient statistics for computing mean, variance, max and min.
observe(List<Prediction<T>>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Records all the supplied predictions.
observe(Event) - Method in class org.tribuo.anomaly.MutableAnomalyInfo
 
observe(Label) - Method in class org.tribuo.classification.MutableLabelInfo
 
observe(ClusterID) - Method in class org.tribuo.clustering.MutableClusteringInfo
 
observe(MultiLabel) - Method in class org.tribuo.multilabel.MutableMultiLabelInfo
Throws IllegalStateException if the MultiLabel contains a Label which has a "," in it.
observe(Prediction<T>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Records the supplied prediction.
observe(Regressor) - Method in class org.tribuo.regression.MutableRegressionInfo
 
observe(T) - Method in interface org.tribuo.MutableOutputInfo
Records an output value or statistics thereof.
observed() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The values this confusion matrix has seen.
observed() - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
observed() - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
observedCount - Variable in class org.tribuo.CategoricalInfo
The count of the observed value if it's only seen a single one.
observedValue - Variable in class org.tribuo.CategoricalInfo
The observed value if it's only seen a single one.
observeSparse() - Method in class org.tribuo.transform.transformations.SimpleTransform
Deprecated.
observeSparse() - Method in interface org.tribuo.transform.TransformStatistics
Deprecated.
in 4.1 as it's unnecessary.
observeSparse(int) - Method in class org.tribuo.transform.transformations.SimpleTransform
No-op on this TransformStatistics.
observeSparse(int) - Method in interface org.tribuo.transform.TransformStatistics
Observes count sparse values.
observeValue(double) - Method in class org.tribuo.transform.transformations.SimpleTransform
No-op on this TransformStatistics.
observeValue(double) - Method in interface org.tribuo.transform.TransformStatistics
Observes a value and updates the statistics.
observeValue(double, int) - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Observes a value for this feature.
ociConfigFile - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
OCI config file path.
ociConfigProfile - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
OCI profile in the config file.
OCIDSConfig(String, String) - Constructor for class org.tribuo.interop.oci.OCIUtil.OCIDSConfig
Constructs an OCIDSConfig.
OCILabelConverter - Class in org.tribuo.interop.oci
A converter for DenseMatrix and DenseVector into Label Predictions.
OCILabelConverter(boolean) - Constructor for class org.tribuo.interop.oci.OCILabelConverter
Constructs an OCILabelConverter with the specified parameters.
OCIModel<T extends Output<T>> - Class in org.tribuo.interop.oci
A wrapper class around an OCI Data Science Model Deployment endpoint which sends off inputs for scoring and converts the output into a Tribuo prediction.
OCIModel.PredictionJson - Class in org.tribuo.interop.oci
Carrier type for easy deserialization from JSON.
OCIModelArtifactConfig(OCIUtil.OCIDSConfig, String, String, String, int, String, String) - Constructor for class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
Constructs an OCIModelArtifactConfig, used to create an OCI DS model.
OCIModelCLI - Class in org.tribuo.interop.oci
This class provides a CLI for deploying and scoring a Tribuo Classification model.
OCIModelCLI.OCIModelOptions - Class in org.tribuo.interop.oci
Options for the OCIModelCLI.
OCIModelCLI.OCIModelOptions.Mode - Enum Class in org.tribuo.interop.oci
Mode for the CLI.
OCIModelDeploymentConfig(OCIUtil.OCIDSConfig, String, String, String, int, int) - Constructor for class org.tribuo.interop.oci.OCIUtil.OCIModelDeploymentConfig
Constructs an OCI DS Model Deployment configuration.
OCIModelOptions() - Constructor for class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
 
OCIMultiLabelConverter - Class in org.tribuo.interop.oci
A converter for DenseMatrix and DenseVector into MultiLabel Predictions.
OCIMultiLabelConverter(double, boolean) - Constructor for class org.tribuo.interop.oci.OCIMultiLabelConverter
Constructs an OCILabelConverter with the specified parameters.
OCIOutputConverter<T extends Output<T>> - Interface in org.tribuo.interop.oci
Converter for a DenseMatrix received from OCI Data Science Model Deployment.
OCIRegressorConverter - Class in org.tribuo.interop.oci
A converter for DenseMatrix and DenseVector into Regressor Predictions.
OCIRegressorConverter() - Constructor for class org.tribuo.interop.oci.OCIRegressorConverter
Constructs an OCIRegressorConverter.
OCIUtil - Class in org.tribuo.interop.oci
Utils for uploading and deploying models to OCI Data Science.
OCIUtil.OCIDSConfig - Class in org.tribuo.interop.oci
Configuration for OCI DS.
OCIUtil.OCIModelArtifactConfig - Class in org.tribuo.interop.oci
Configuration for an OCI DS Model artifact.
OCIUtil.OCIModelDeploymentConfig - Class in org.tribuo.interop.oci
Configuration for an OCI DS Model Deployment.
OCIUtil.OCIModelType - Enum Class in org.tribuo.interop.oci
Enum for OCI model types.
of(TType) - Static method in class org.tribuo.interop.tensorflow.TensorFlowUtil.TensorTuple
Makes a TensorTuple out of this tensor.
OffsetDateTimeExtractor - Class in org.tribuo.data.columnar.extractors
Extracts the field value and translates it to an OffsetDateTime based on the specified DateTimeFormatter.
OffsetDateTimeExtractor(String, String, String) - Constructor for class org.tribuo.data.columnar.extractors.OffsetDateTimeExtractor
Constructs a date time extractor that emits an OffsetDateTime by applying the supplied format to the specified field.
OffsetDateTimeExtractor(String, String, String, String, String) - Constructor for class org.tribuo.data.columnar.extractors.OffsetDateTimeExtractor
Constructs a date time extractor that emits an OffsetDateTime by applying the supplied format to the specified field.
ONE_CLASS - Enum constant in enum class org.tribuo.anomaly.libsvm.SVMAnomalyType.SVMMode
Anomaly detection SVM.
ONECLASS_SVM - Enum constant in enum class org.tribuo.anomaly.liblinear.LinearAnomalyType.LinearType
Linear one-class SVM
oneNorm() - Method in class org.tribuo.math.la.DenseVector
 
oneNorm() - Method in interface org.tribuo.math.la.SGDVector
Calculates the Manhattan norm for this vector.
oneNorm() - Method in class org.tribuo.math.la.SparseVector
 
OnlineEvaluator<T extends Output<T>,E extends Evaluation<T>> - Class in org.tribuo.evaluation
An evaluator which aggregates predictions and produces Evaluations covering all the Predictions it has seen or created.
OnlineEvaluator(Evaluator<T, E>, Model<T>, DataProvenance) - Constructor for class org.tribuo.evaluation.OnlineEvaluator
Constructs an OnlineEvaluator which accumulates predictions.
ONNXAttribute - Class in org.tribuo.util.onnx
The spec for an attribute, used to produce the attribute proto at construction time.
ONNXAttribute(String, OnnxMl.AttributeProto.AttributeType, boolean) - Constructor for class org.tribuo.util.onnx.ONNXAttribute
Constructs an attribute placeholder of the appropriate name and type.
onnxContext() - Method in class org.tribuo.util.onnx.ONNXRef
The context this reference operates in.
ONNXContext - Class in org.tribuo.util.onnx
Context object used to scope and manage the creation of ONNX OnnxMl.GraphProto and OnnxMl.ModelProto instances.
ONNXContext() - Constructor for class org.tribuo.util.onnx.ONNXContext
Creates an empty ONNX context.
onnxDomain - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
The ONNX domain name.
ONNXExportable - Interface in org.tribuo
An interface which denotes this Model can be exported as an ONNX model.
ONNXExternalModel<T extends Output<T>> - Class in org.tribuo.interop.onnx
A Tribuo wrapper around a ONNX model.
ONNXInitializer - Class in org.tribuo.util.onnx
A subclass of ONNXRef specialized for OnnxMl.TensorProto.
ONNXMathUtils - Class in org.tribuo.math.onnx
Tribuo Math specific helper functions for building ONNX protos.
OnnxMl - Class in ai.onnx.proto
 
OnnxMl.AttributeProto - Class in ai.onnx.proto
Attributes A named attribute containing either singular float, integer, string, graph, and tensor values, or repeated float, integer, string, graph, and tensor values.
OnnxMl.AttributeProto.AttributeType - Enum Class in ai.onnx.proto
Note: this enum is structurally identical to the OpSchema::AttrType enum defined in schema.h.
OnnxMl.AttributeProto.Builder - Class in ai.onnx.proto
Attributes A named attribute containing either singular float, integer, string, graph, and tensor values, or repeated float, integer, string, graph, and tensor values.
OnnxMl.AttributeProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.GraphProto - Class in ai.onnx.proto
Graphs A graph defines the computational logic of a model and is comprised of a parameterized list of nodes that form a directed acyclic graph based on their inputs and outputs.
OnnxMl.GraphProto.Builder - Class in ai.onnx.proto
Graphs A graph defines the computational logic of a model and is comprised of a parameterized list of nodes that form a directed acyclic graph based on their inputs and outputs.
OnnxMl.GraphProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.ModelProto - Class in ai.onnx.proto
Models ModelProto is a top-level file/container format for bundling a ML model and associating its computation graph with metadata.
OnnxMl.ModelProto.Builder - Class in ai.onnx.proto
Models ModelProto is a top-level file/container format for bundling a ML model and associating its computation graph with metadata.
OnnxMl.ModelProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.NodeProto - Class in ai.onnx.proto
Nodes Computation graphs are made up of a DAG of nodes, which represent what is commonly called a "layer" or "pipeline stage" in machine learning frameworks.
OnnxMl.NodeProto.Builder - Class in ai.onnx.proto
Nodes Computation graphs are made up of a DAG of nodes, which represent what is commonly called a "layer" or "pipeline stage" in machine learning frameworks.
OnnxMl.NodeProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.OperatorSetIdProto - Class in ai.onnx.proto
Operator Sets OperatorSets are uniquely identified by a (domain, opset_version) pair.
OnnxMl.OperatorSetIdProto.Builder - Class in ai.onnx.proto
Operator Sets OperatorSets are uniquely identified by a (domain, opset_version) pair.
OnnxMl.OperatorSetIdProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.SparseTensorProto - Class in ai.onnx.proto
A serialized sparse-tensor value
OnnxMl.SparseTensorProto.Builder - Class in ai.onnx.proto
A serialized sparse-tensor value
OnnxMl.SparseTensorProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.StringStringEntryProto - Class in ai.onnx.proto
StringStringEntryProto follows the pattern for cross-proto-version maps.
OnnxMl.StringStringEntryProto.Builder - Class in ai.onnx.proto
StringStringEntryProto follows the pattern for cross-proto-version maps.
OnnxMl.StringStringEntryProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TensorAnnotation - Class in ai.onnx.proto
Protobuf type onnx.TensorAnnotation
OnnxMl.TensorAnnotation.Builder - Class in ai.onnx.proto
Protobuf type onnx.TensorAnnotation
OnnxMl.TensorAnnotationOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TensorProto - Class in ai.onnx.proto
Tensors A serialized tensor value.
OnnxMl.TensorProto.Builder - Class in ai.onnx.proto
Tensors A serialized tensor value.
OnnxMl.TensorProto.DataLocation - Enum Class in ai.onnx.proto
Location of the data for this tensor.
OnnxMl.TensorProto.DataType - Enum Class in ai.onnx.proto
Protobuf enum onnx.TensorProto.DataType
OnnxMl.TensorProto.Segment - Class in ai.onnx.proto
For very large tensors, we may want to store them in chunks, in which case the following fields will specify the segment that is stored in the current TensorProto.
OnnxMl.TensorProto.Segment.Builder - Class in ai.onnx.proto
For very large tensors, we may want to store them in chunks, in which case the following fields will specify the segment that is stored in the current TensorProto.
OnnxMl.TensorProto.SegmentOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TensorProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TensorShapeProto - Class in ai.onnx.proto
Defines a tensor shape.
OnnxMl.TensorShapeProto.Builder - Class in ai.onnx.proto
Defines a tensor shape.
OnnxMl.TensorShapeProto.Dimension - Class in ai.onnx.proto
Protobuf type onnx.TensorShapeProto.Dimension
OnnxMl.TensorShapeProto.Dimension.Builder - Class in ai.onnx.proto
Protobuf type onnx.TensorShapeProto.Dimension
OnnxMl.TensorShapeProto.Dimension.ValueCase - Enum Class in ai.onnx.proto
 
OnnxMl.TensorShapeProto.DimensionOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TensorShapeProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TrainingInfoProto - Class in ai.onnx.proto
Training information TrainingInfoProto stores information for training a model.
OnnxMl.TrainingInfoProto.Builder - Class in ai.onnx.proto
Training information TrainingInfoProto stores information for training a model.
OnnxMl.TrainingInfoProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TypeProto - Class in ai.onnx.proto
Types The standard ONNX data types.
OnnxMl.TypeProto.Builder - Class in ai.onnx.proto
Types The standard ONNX data types.
OnnxMl.TypeProto.Map - Class in ai.onnx.proto
map<K,V>
OnnxMl.TypeProto.Map.Builder - Class in ai.onnx.proto
map<K,V>
OnnxMl.TypeProto.MapOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TypeProto.Opaque - Class in ai.onnx.proto
Protobuf type onnx.TypeProto.Opaque
OnnxMl.TypeProto.Opaque.Builder - Class in ai.onnx.proto
Protobuf type onnx.TypeProto.Opaque
OnnxMl.TypeProto.OpaqueOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TypeProto.Sequence - Class in ai.onnx.proto
repeated T
OnnxMl.TypeProto.Sequence.Builder - Class in ai.onnx.proto
repeated T
OnnxMl.TypeProto.SequenceOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TypeProto.SparseTensor - Class in ai.onnx.proto
Protobuf type onnx.TypeProto.SparseTensor
OnnxMl.TypeProto.SparseTensor.Builder - Class in ai.onnx.proto
Protobuf type onnx.TypeProto.SparseTensor
OnnxMl.TypeProto.SparseTensorOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TypeProto.Tensor - Class in ai.onnx.proto
Protobuf type onnx.TypeProto.Tensor
OnnxMl.TypeProto.Tensor.Builder - Class in ai.onnx.proto
Protobuf type onnx.TypeProto.Tensor
OnnxMl.TypeProto.TensorOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.TypeProto.ValueCase - Enum Class in ai.onnx.proto
 
OnnxMl.TypeProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.ValueInfoProto - Class in ai.onnx.proto
Defines information on value, including the name, the type, and the shape of the value.
OnnxMl.ValueInfoProto.Builder - Class in ai.onnx.proto
Defines information on value, including the name, the type, and the shape of the value.
OnnxMl.ValueInfoProtoOrBuilder - Interface in ai.onnx.proto
 
OnnxMl.Version - Enum Class in ai.onnx.proto
Versioning ONNX versioning is specified in docs/IR.md and elaborated on in docs/Versioning.md To be compatible with both proto2 and proto3, we will use a version number that is not defined by the default value but an explicit enum number.
onnxModelName() - Method in class org.tribuo.classification.sgd.fm.FMClassificationModel
 
onnxModelName() - Method in class org.tribuo.classification.sgd.linear.LinearSGDModel
 
onnxModelName() - Method in class org.tribuo.common.sgd.AbstractFMModel
 
onnxModelName() - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
 
onnxModelName() - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelModel
 
onnxModelName() - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDModel
 
onnxModelName() - Method in class org.tribuo.regression.sgd.fm.FMRegressionModel
 
onnxModelName() - Method in class org.tribuo.regression.sgd.linear.LinearSGDModel
 
onnxModelVersion - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelArtifactConfig
The ONNX model version.
ONNXNode - Class in org.tribuo.util.onnx
A subclass of ONNXRef specialized for OnnxMl.NodeProto.
ONNXOperators - Enum Class in org.tribuo.util.onnx
The supported ONNX operators.
onnxOutput(ONNXNode) - Method in class org.tribuo.classification.sgd.fm.FMClassificationModel
 
onnxOutput(ONNXNode) - Method in class org.tribuo.classification.sgd.linear.LinearSGDModel
 
onnxOutput(ONNXNode) - Method in class org.tribuo.common.sgd.AbstractFMModel
Takes the unnormalized ONNX output of this model and applies an appropriate normalizer from the concrete class.
onnxOutput(ONNXNode) - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
Takes the unnormalized ONNX output of this model and applies an appropriate normalizer from the concrete class.
onnxOutput(ONNXNode) - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelModel
 
onnxOutput(ONNXNode) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDModel
 
onnxOutput(ONNXNode) - Method in class org.tribuo.regression.sgd.fm.FMRegressionModel
 
onnxOutput(ONNXNode) - Method in class org.tribuo.regression.sgd.linear.LinearSGDModel
 
ONNXPlaceholder - Class in org.tribuo.util.onnx
A subclass of ONNXRef specialized for OnnxMl.ValueInfoProto.
ONNXRef<T extends com.google.protobuf.GeneratedMessageV3> - Class in org.tribuo.util.onnx
An abstract reference that represents both a node in an ONNX computation graph and a container for a specific ONNX proto object that denotes that node.
ONNXUtils - Class in org.tribuo.util.onnx
Helper functions for building ONNX protos.
OP_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
 
OPAQUE_TYPE - Enum constant in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
OPAQUE_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto
 
operation(ONNXOperators, List<T>, String) - Method in class org.tribuo.util.onnx.ONNXContext
Method for creating ONNXNodes from ONNXOperators and inputs.
operation(ONNXOperators, List<T>, String, Map<String, Object>) - Method in class org.tribuo.util.onnx.ONNXContext
Method for creating ONNXNodes from ONNXOperators and inputs.
operation(ONNXOperators, List<T>, List<String>, Map<String, Object>) - Method in class org.tribuo.util.onnx.ONNXContext
Base method for creating ONNXNodes from ONNXOperators and inputs.
opName - Variable in enum class org.tribuo.util.onnx.ONNXOperators
The operator name.
OPSET_IMPORT_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
optimiser - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
optimiser - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
The gradient optimizer to use.
org.tribuo - package org.tribuo
Provides the core interfaces and classes for using Tribuo.
org.tribuo.anomaly - package org.tribuo.anomaly
Provides classes and infrastructure for anomaly detection problems.
org.tribuo.anomaly.evaluation - package org.tribuo.anomaly.evaluation
Evaluation classes for anomaly detection.
org.tribuo.anomaly.example - package org.tribuo.anomaly.example
Provides anomaly data generators used for demos and testing implementations.
org.tribuo.anomaly.liblinear - package org.tribuo.anomaly.liblinear
Provides an interface to LibLinear-java for anomaly detection problems.
org.tribuo.anomaly.libsvm - package org.tribuo.anomaly.libsvm
Provides an interface to LibSVM for anomaly detection problems.
org.tribuo.classification - package org.tribuo.classification
Provides classes and infrastructure for multiclass classification problems.
org.tribuo.classification.baseline - package org.tribuo.classification.baseline
Provides simple baseline multiclass classifiers.
org.tribuo.classification.dtree - package org.tribuo.classification.dtree
Provides implementations of decision trees for classification problems.
org.tribuo.classification.dtree.impl - package org.tribuo.classification.dtree.impl
Provides internal implementation classes for classification decision trees.
org.tribuo.classification.dtree.impurity - package org.tribuo.classification.dtree.impurity
Provides classification impurity metrics for decision trees.
org.tribuo.classification.ensemble - package org.tribuo.classification.ensemble
Provides majority vote ensemble combiners for classification along with an implementation of multiclass Adaboost.
org.tribuo.classification.evaluation - package org.tribuo.classification.evaluation
Evaluation classes for multi-class classification.
org.tribuo.classification.example - package org.tribuo.classification.example
Provides a multiclass data generator used for testing implementations, along with several synthetic data generators for 2d binary classification problems to be used in demos or tutorials.
org.tribuo.classification.experiments - package org.tribuo.classification.experiments
Provides a set of main methods for interacting with classification tasks.
org.tribuo.classification.explanations - package org.tribuo.classification.explanations
Provides core infrastructure for local model based explanations.
org.tribuo.classification.explanations.lime - package org.tribuo.classification.explanations.lime
Provides an implementation of LIME (Locally Interpretable Model Explanations).
org.tribuo.classification.liblinear - package org.tribuo.classification.liblinear
Provides an interface to LibLinear-java for classification problems.
org.tribuo.classification.libsvm - package org.tribuo.classification.libsvm
Provides an interface to LibSVM for classification problems.
org.tribuo.classification.mnb - package org.tribuo.classification.mnb
Provides an implementation of multinomial naive bayes (i.e., naive bayes for non-negative count data).
org.tribuo.classification.sequence - package org.tribuo.classification.sequence
Provides infrastructure for SequenceModels which emit Labels at each step of the sequence.
org.tribuo.classification.sequence.example - package org.tribuo.classification.sequence.example
Provides a classification sequence data generator for smoke testing implementations.
org.tribuo.classification.sequence.viterbi - package org.tribuo.classification.sequence.viterbi
Provides an implementation of Viterbi for generating structured outputs, which can sit on top of any Label based classification model.
org.tribuo.classification.sgd - package org.tribuo.classification.sgd
Provides infrastructure for Stochastic Gradient Descent for classification problems.
org.tribuo.classification.sgd.crf - package org.tribuo.classification.sgd.crf
Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
org.tribuo.classification.sgd.fm - package org.tribuo.classification.sgd.fm
Provides an implementation of a classification factorization machine using Stochastic Gradient Descent.
org.tribuo.classification.sgd.kernel - package org.tribuo.classification.sgd.kernel
Provides a SGD implementation of a Kernel SVM using the Pegasos algorithm.
org.tribuo.classification.sgd.linear - package org.tribuo.classification.sgd.linear
Provides an implementation of a classification linear model using Stochastic Gradient Descent.
org.tribuo.classification.sgd.objectives - package org.tribuo.classification.sgd.objectives
Provides classification loss functions for Stochastic Gradient Descent.
org.tribuo.classification.xgboost - package org.tribuo.classification.xgboost
Provides an interface to XGBoost for classification problems.
org.tribuo.clustering - package org.tribuo.clustering
Provides classes and infrastructure for working with clustering problems.
org.tribuo.clustering.evaluation - package org.tribuo.clustering.evaluation
Evaluation classes for clustering.
org.tribuo.clustering.example - package org.tribuo.clustering.example
Provides clustering data generators used for demos and testing implementations.
org.tribuo.clustering.hdbscan - package org.tribuo.clustering.hdbscan
Provides an implementation of HDBSCAN*.
org.tribuo.clustering.kmeans - package org.tribuo.clustering.kmeans
Provides a multithreaded implementation of K-Means, with a configurable distance function.
org.tribuo.common.liblinear - package org.tribuo.common.liblinear
Provides base classes for using liblinear from Tribuo.
org.tribuo.common.libsvm - package org.tribuo.common.libsvm
The base interface to LibSVM.
org.tribuo.common.nearest - package org.tribuo.common.nearest
Provides a K-Nearest Neighbours implementation which works across all Tribuo Output types.
org.tribuo.common.sgd - package org.tribuo.common.sgd
Provides the base classes for models trained with stochastic gradient descent.
org.tribuo.common.tree - package org.tribuo.common.tree
Provides common functionality for building decision trees, irrespective of the predicted Output.
org.tribuo.common.tree.impl - package org.tribuo.common.tree.impl
Provides internal implementation classes for building decision trees.
org.tribuo.common.xgboost - package org.tribuo.common.xgboost
Provides abstract classes for interfacing with XGBoost abstracting away all the Output dependent parts.
org.tribuo.data - package org.tribuo.data
Provides classes for loading in data from disk, processing it into examples, and splitting datasets for things like cross-validation and train-test splits.
org.tribuo.data.columnar - package org.tribuo.data.columnar
Provides classes for processing columnar data and generating Examples.
org.tribuo.data.columnar.extractors - package org.tribuo.data.columnar.extractors
Provides implementations of FieldExtractor.
org.tribuo.data.columnar.processors.feature - package org.tribuo.data.columnar.processors.feature
Provides implementations of FeatureProcessor.
org.tribuo.data.columnar.processors.field - package org.tribuo.data.columnar.processors.field
Provides implementations of FieldProcessor.
org.tribuo.data.columnar.processors.response - package org.tribuo.data.columnar.processors.response
Provides implementations of ResponseProcessor.
org.tribuo.data.csv - package org.tribuo.data.csv
Provides classes which can load columnar data (using a RowProcessor) from a CSV (or other character delimited format) file.
org.tribuo.data.sql - package org.tribuo.data.sql
Provides classes which can load columnar data (using a RowProcessor) from a SQL source.
org.tribuo.data.text - package org.tribuo.data.text
Provides interfaces for converting text inputs into Features and Examples.
org.tribuo.data.text.impl - package org.tribuo.data.text.impl
Provides implementations of text data processors.
org.tribuo.dataset - package org.tribuo.dataset
Provides utility datasets which subsample or otherwise transform the wrapped dataset.
org.tribuo.datasource - package org.tribuo.datasource
Simple data sources for ingesting or aggregating data.
org.tribuo.ensemble - package org.tribuo.ensemble
Provides an interface for model prediction combinations, two base classes for ensemble models, a base class for ensemble excuses, and a Bagging implementation.
org.tribuo.evaluation - package org.tribuo.evaluation
Evaluation base classes, along with code for train/test splits and cross validation.
org.tribuo.evaluation.metrics - package org.tribuo.evaluation.metrics
This package contains the infrastructure classes for building evaluation metrics.
org.tribuo.hash - package org.tribuo.hash
Provides the base interface and implementations of the Model hashing which obscures the feature names stored in a model.
org.tribuo.impl - package org.tribuo.impl
Provides implementations of base classes and interfaces from org.tribuo.
org.tribuo.interop - package org.tribuo.interop
This package contains the abstract implementation of an external model trained by something outside of Tribuo.
org.tribuo.interop.oci - package org.tribuo.interop.oci
Code for uploading models to Oracle Cloud Infrastructure Data Science, and also for scoring models deployed in Oracle Cloud Infrastructure Data Science.
org.tribuo.interop.onnx - package org.tribuo.interop.onnx
This package contains a Tribuo wrapper around the ONNX Runtime.
org.tribuo.interop.onnx.extractors - package org.tribuo.interop.onnx.extractors
Provides feature extraction implementations which use ONNX models.
org.tribuo.interop.tensorflow - package org.tribuo.interop.tensorflow
Provides an interface to TensorFlow, allowing the training of non-sequential models using any supported Tribuo output type.
org.tribuo.interop.tensorflow.example - package org.tribuo.interop.tensorflow.example
Example architectures for use with Tribuo's TF interface.
org.tribuo.interop.tensorflow.sequence - package org.tribuo.interop.tensorflow.sequence
Provides an interface for working with TensorFlow sequence models, using Tribuo's SequenceModel abstraction.
org.tribuo.json - package org.tribuo.json
Provides interop with JSON formatted data, along with tools for interacting with JSON provenance objects.
org.tribuo.math - package org.tribuo.math
Contains the implementation of Tribuo's math library, it's gradient descent optimisers, kernels and a set of math related utils.
org.tribuo.math.kernel - package org.tribuo.math.kernel
Provides a Kernel interface for Mercer kernels, along with implementations of standard kernels.
org.tribuo.math.la - package org.tribuo.math.la
Provides a linear algebra system used for numerical operations in Tribuo.
org.tribuo.math.onnx - package org.tribuo.math.onnx
 
org.tribuo.math.optimisers - package org.tribuo.math.optimisers
Provides implementations of StochasticGradientOptimiser.
org.tribuo.math.optimisers.util - package org.tribuo.math.optimisers.util
Provides some utility tensors for use in gradient optimisers.
org.tribuo.math.util - package org.tribuo.math.util
Provides math related util classes.
org.tribuo.multilabel - package org.tribuo.multilabel
Provides classes and infrastructure for working with multi-label classification problems.
org.tribuo.multilabel.baseline - package org.tribuo.multilabel.baseline
Provides implementations of binary relevance based multi-label classification algorithms.
org.tribuo.multilabel.ensemble - package org.tribuo.multilabel.ensemble
Provides a multi-label ensemble combiner that performs a (possibly weighted) majority vote among each label independently, along with an implementation of classifier chain ensembles.
org.tribuo.multilabel.evaluation - package org.tribuo.multilabel.evaluation
Evaluation classes for multi-label classification using MultiLabel.
org.tribuo.multilabel.example - package org.tribuo.multilabel.example
Provides a multi-label data generator for testing implementations and a configurable data source suitable for demos and tests.
org.tribuo.multilabel.sgd - package org.tribuo.multilabel.sgd
Provides infrastructure for Stochastic Gradient Descent for multi-label classification problems.
org.tribuo.multilabel.sgd.fm - package org.tribuo.multilabel.sgd.fm
Provides an implementation of a multi-label classification factorization machine model using Stochastic Gradient Descent.
org.tribuo.multilabel.sgd.linear - package org.tribuo.multilabel.sgd.linear
Provides an implementation of a multi-label classification linear model using Stochastic Gradient Descent.
org.tribuo.multilabel.sgd.objectives - package org.tribuo.multilabel.sgd.objectives
Provides multi-label classification loss functions for Stochastic Gradient Descent.
org.tribuo.provenance - package org.tribuo.provenance
Provides Tribuo specific infrastructure for the Provenance system which tracks models and datasets.
org.tribuo.provenance.impl - package org.tribuo.provenance.impl
Provides internal implementations for empty provenance classes and TrainerProvenance.
org.tribuo.regression - package org.tribuo.regression
Provides classes and infrastructure for regression problems with single or multiple output dimensions.
org.tribuo.regression.baseline - package org.tribuo.regression.baseline
Provides simple baseline regression predictors.
org.tribuo.regression.ensemble - package org.tribuo.regression.ensemble
Provides EnsembleCombiner implementations for working with multi-output regression problems.
org.tribuo.regression.evaluation - package org.tribuo.regression.evaluation
Evaluation classes for single or multi-dimensional regression.
org.tribuo.regression.example - package org.tribuo.regression.example
Provides some example regression data generators for testing implementations.
org.tribuo.regression.impl - package org.tribuo.regression.impl
Provides skeletal implementations of Regressor Trainer that can wrap a single dimension trainer/model and produce one prediction per dimension independently.
org.tribuo.regression.liblinear - package org.tribuo.regression.liblinear
Provides an interface to liblinear for regression problems.
org.tribuo.regression.libsvm - package org.tribuo.regression.libsvm
Provides an interface to LibSVM for regression problems.
org.tribuo.regression.rtree - package org.tribuo.regression.rtree
Provides an implementation of decision trees for regression problems.
org.tribuo.regression.rtree.impl - package org.tribuo.regression.rtree.impl
Provides internal implementation classes for the regression trees.
org.tribuo.regression.rtree.impurity - package org.tribuo.regression.rtree.impurity
Provides implementations of regression tree impurity metrics.
org.tribuo.regression.sgd - package org.tribuo.regression.sgd
Provides infrastructure for Stochastic Gradient Descent based regression models.
org.tribuo.regression.sgd.fm - package org.tribuo.regression.sgd.fm
Provides an implementation of factorization machines for regression using Stochastic Gradient Descent.
org.tribuo.regression.sgd.linear - package org.tribuo.regression.sgd.linear
Provides an implementation of linear regression using Stochastic Gradient Descent.
org.tribuo.regression.sgd.objectives - package org.tribuo.regression.sgd.objectives
Provides regression loss functions for Stochastic Gradient Descent.
org.tribuo.regression.slm - package org.tribuo.regression.slm
Provides implementations of sparse linear regression using various forms of regularisation penalty.
org.tribuo.regression.xgboost - package org.tribuo.regression.xgboost
Provides an interface to XGBoost for regression problems.
org.tribuo.reproducibility - package org.tribuo.reproducibility
Reproducibility utility based on Tribuo's provenance objects.
org.tribuo.sequence - package org.tribuo.sequence
Provides core classes for working with sequences of Examples.
org.tribuo.tests - package org.tribuo.tests
This package provides helper classes for Tribuo's unit tests.
org.tribuo.transform - package org.tribuo.transform
Provides infrastructure for applying transformations to a Dataset.
org.tribuo.transform.transformations - package org.tribuo.transform.transformations
Provides implementations of standard transformations like binning, scaling, taking logs and exponents.
org.tribuo.util - package org.tribuo.util
Provides utilities which don't have other Tribuo dependencies.
org.tribuo.util.infotheory - package org.tribuo.util.infotheory
This package provides static classes of information theoretic functions.
org.tribuo.util.infotheory.example - package org.tribuo.util.infotheory.example
This package provides demos for the information theoretic function classes in org.tribuo.util.infotheory.
org.tribuo.util.infotheory.impl - package org.tribuo.util.infotheory.impl
This package provides the implementations and helper classes for the information theoretic functions in org.tribuo.util.infotheory.
org.tribuo.util.onnx - package org.tribuo.util.onnx
Interfaces and utilities for writing ONNX models from Java.
org.tribuo.util.tokens - package org.tribuo.util.tokens
Core definitions for tokenization.
org.tribuo.util.tokens.impl - package org.tribuo.util.tokens.impl
Simple fixed rule tokenizers.
org.tribuo.util.tokens.impl.wordpiece - package org.tribuo.util.tokens.impl.wordpiece
Provides an implementation of a Wordpiece tokenizer which implements to the Tribuo Tokenizer API.
org.tribuo.util.tokens.options - package org.tribuo.util.tokens.options
OLCUT Options implementations which can construct Tokenizers of various types.
org.tribuo.util.tokens.universal - package org.tribuo.util.tokens.universal
An implementation of a "universal" tokenizer which will split on word boundaries or character boundaries for languages where word boundaries are contextual.
originalFeatures() - Method in record class org.tribuo.reproducibility.ReproUtil.FeatureDiff
Returns the value of the originalFeatures record component.
originalOutput() - Method in record class org.tribuo.reproducibility.ReproUtil.OutputDiff
Returns the value of the originalOutput record component.
OS_STRING - Static variable in class org.tribuo.provenance.ModelProvenance
 
osString - Variable in class org.tribuo.provenance.ModelProvenance
 
OTHER - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Other prediction types, currently used as the mapping for Tribuo's MultiLabel.
outer(SGDVector) - Method in class org.tribuo.math.la.DenseVector
 
outer(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Generates the matrix representing the outer product between the two vectors.
outer(SGDVector) - Method in class org.tribuo.math.la.SparseVector
This generates the outer product when dotted with another SparseVector.
output - Variable in class org.tribuo.data.PreprocessAndSerialize.PreprocessAndSerializeOptions
path to serialize the dataset
output - Variable in class org.tribuo.Example
The output associated with this example.
Output<T extends Output<T>> - Interface in org.tribuo
Output is the root interface for the supported prediction types.
OUTPUT_FACTORY - Static variable in interface org.tribuo.provenance.DataSourceProvenance
The name of the provenance field for the output factory.
OUTPUT_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
OUTPUT_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
 
OUTPUT_FILE_MODIFIED_TIME - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
The name of the output file modified time provenance field.
OUTPUT_RESOURCE_HASH - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
The name of the provenance field for the output file hash.
outputConverter - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceModel
 
outputConverter - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
outputConverter - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
OutputConverter<T extends Output<T>> - Interface in org.tribuo.interop.tensorflow
Converts the Output into a Tensor and vice versa.
outputCountsIterable() - Method in class org.tribuo.anomaly.AnomalyInfo
 
outputCountsIterable() - Method in class org.tribuo.classification.LabelInfo
 
outputCountsIterable() - Method in class org.tribuo.clustering.ClusteringInfo
 
outputCountsIterable() - Method in class org.tribuo.multilabel.MultiLabelInfo
 
outputCountsIterable() - Method in interface org.tribuo.OutputInfo
An Iterable over the possible outputs and the number of times they were observed.
outputCountsIterable() - Method in class org.tribuo.regression.RegressionInfo
 
outputDiff() - Method in record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Returns the value of the outputDiff record component.
OutputDiff(Set<T>, Set<T>) - Constructor for record class org.tribuo.reproducibility.ReproUtil.OutputDiff
Creates an instance of a OutputDiff record class.
outputFactory - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
The output factory to construct.
outputFactory - Variable in class org.tribuo.data.text.DirectoryFileSource
The factory that converts a String into an Output.
outputFactory - Variable in class org.tribuo.data.text.TextDataSource
The factory that converts a String into an Output.
outputFactory - Variable in class org.tribuo.Dataset
A factory for making OutputInfo and Output of the appropriate type.
outputFactory - Variable in class org.tribuo.sequence.SequenceDataset
A factory for making OutputInfo and Output of the appropriate type.
OutputFactory<T extends Output<T>> - Interface in org.tribuo
An interface associated with a specific Output, which can generate the appropriate Output subclass, and OutputInfo subclass.
OutputFactoryProvenance - Interface in org.tribuo.provenance
A tag provenance for an output factory.
outputFile - Variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.BERTFeatureExtractorOptions
Output json file.
outputID - Variable in class org.tribuo.impl.IndexedArrayExample
Output id from the internal output map.
outputIDInfo - Variable in class org.tribuo.ImmutableDataset
Output information, and id numbers for outputs found in this dataset.
outputIDInfo - Variable in class org.tribuo.Model
The outputs this model predicts.
outputIDInfo - Variable in class org.tribuo.sequence.ImmutableSequenceDataset
A map from labels to IDs for the labels found in this dataset.
outputIDMap - Variable in class org.tribuo.sequence.SequenceModel
 
outputInfo - Variable in class org.tribuo.sequence.MutableSequenceDataset
A map from labels to IDs for the labels found in this dataset.
outputInfo(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
Shows the output information.
outputInfo(CommandInterpreter) - Method in class org.tribuo.ModelExplorer
Displays the output info.
outputInfo(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer
Shows the output information.
OutputInfo<T extends Output<T>> - Interface in org.tribuo
Tracks relevant properties of the appropriate Output subclass.
outputMap - Variable in class org.tribuo.MutableDataset
Information about the outputs in this dataset.
outputModel - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
The location to write out the stripped model.
outputName - Variable in class org.tribuo.interop.tensorflow.example.GraphDefTuple
Name of the output operation.
outputName - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
outputName - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Name of the output operation.
outputPath - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
Path to serialize model to.
outputPath - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Path to serialize model to.
outputPath - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
Path to serialize model to.
outputPath - Variable in class org.tribuo.data.DataOptions
Path to serialize model to.
outputPath - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
File to write query results as CSV, defaults to stdout
outputPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Path to serialize model to.
outputRequired - Variable in class org.tribuo.data.columnar.ColumnarDataSource
 
OutputTransformer<T extends Output<T>> - Interface in org.tribuo.interop.onnx
Converts an OnnxValue into an Output or a Prediction.
outputTransformFunction() - Method in class org.tribuo.interop.tensorflow.LabelConverter
Applies a softmax.
outputTransformFunction() - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
Applies a softmax.
outputTransformFunction() - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Produces an output transformation function that applies the operation to the graph from the supplied Ops, taking a graph output operation.
outputTransformFunction() - Method in class org.tribuo.interop.tensorflow.RegressorConverter
Applies the identity function
overallCount - Variable in class org.tribuo.regression.RegressionInfo
 
overrideParameters - Variable in class org.tribuo.common.xgboost.XGBoostTrainer
 

P

pairDescendingValueComparator() - Static method in class org.tribuo.util.IntDoublePair
Compare pairs by value.
PairDistribution<T1,T2> - Class in org.tribuo.util.infotheory.impl
A count distribution over CachedPair objects.
PairDistribution(long, LinkedHashMap<CachedPair<T1, T2>, MutableLong>, LinkedHashMap<T1, MutableLong>, LinkedHashMap<T2, MutableLong>) - Constructor for class org.tribuo.util.infotheory.impl.PairDistribution
Constructs a pair distribution.
PairDistribution(long, Map<CachedPair<T1, T2>, MutableLong>, Map<T1, MutableLong>, Map<T2, MutableLong>) - Constructor for class org.tribuo.util.infotheory.impl.PairDistribution
Constructs a pair distribution.
pairIndexComparator() - Static method in class org.tribuo.util.IntDoublePair
Compare pairs by index.
pairValueComparator() - Static method in class org.tribuo.util.IntDoublePair
Compare pairs by value.
paramAve - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
Use parameter averaging.
ParameterAveraging - Class in org.tribuo.math.optimisers
Averages the parameters across a gradient run.
ParameterAveraging(StochasticGradientOptimiser) - Constructor for class org.tribuo.math.optimisers.ParameterAveraging
Adds parameter averaging around a gradient optimiser.
parameters - Variable in class org.tribuo.common.libsvm.LibSVMTrainer
The SVM parameters suitable for use by LibSVM.
parameters - Variable in class org.tribuo.common.libsvm.SVMParameters
 
parameters - Variable in class org.tribuo.common.xgboost.XGBoostTrainer
 
Parameters - Interface in org.tribuo.math
An interface to a Tensor[] array which accepts updates to the parameters.
paramName - Variable in enum class org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
The parameter value used by the XGBoost native library.
paramName - Variable in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
The parameter name used by the XGBoost native library.
paramName - Variable in enum class org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
The parameter name used by the XGBoost native library.
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseDelimitedFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseDelimitedFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseElement(int, String) - Static method in class org.tribuo.regression.Regressor
Parses a string of the form:
parseElement(String) - Static method in class org.tribuo.multilabel.MultiLabel
Parses a string of the form:
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(byte[]) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(byte[], ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(ByteString) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(ByteString, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(CodedInputStream) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(CodedInputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(InputStream) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(InputStream, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(ByteBuffer) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parseFrom(ByteBuffer, ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
parseLine(String, int) - Method in class org.tribuo.data.text.impl.SimpleTextDataSource
 
parser() - Static method in class ai.onnx.proto.OnnxMl.AttributeProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.GraphProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.ModelProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.NodeProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TensorProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TypeProto
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
parser() - Static method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
parser() - Static method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
PARSER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.NodeProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.SparseTensorProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.StringStringEntryProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TensorAnnotation
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto.Segment
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TensorShapeProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TrainingInfoProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Map
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
Deprecated.
PARSER - Static variable in class ai.onnx.proto.OnnxMl.ValueInfoProto
Deprecated.
parseString(String) - Static method in class org.tribuo.multilabel.MultiLabel
Parses a string of the form: dimension-name=output,...,dimension-name=output where output must be readable by Boolean.parseBoolean(String).
parseString(String) - Static method in class org.tribuo.regression.Regressor
Parses a string of the form:
parseString(String, char) - Static method in class org.tribuo.multilabel.MultiLabel
Parses a string of the form:
parseString(String, char) - Static method in class org.tribuo.regression.Regressor
Parses a string of the form:
partialExpandRegexMapping(Collection<String>) - Method in class org.tribuo.data.columnar.RowProcessor
Caveat Implementor! This method contains the logic of RowProcessor.expandRegexMapping(org.tribuo.Model<T>) without any of the checks that ensure the RowProcessor is in a valid state.
password - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
Password for the SQL database
path - Variable in class org.tribuo.data.text.TextDataSource
The path that data was read from.
Pegasos - Class in org.tribuo.math.optimisers
An implementation of the Pegasos gradient optimiser used primarily for solving the SVM problem.
Pegasos(double, double) - Constructor for class org.tribuo.math.optimisers.Pegasos
Constructs a Pegasos optimiser with the specified parameters.
PEGASOS - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
The Pegasos optimiser.
PLACEHOLDER - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
The name of the placeholder op.
PLUSPLUS - Enum constant in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation
KMeans++ initialisation.
POINT_VERSION - Static variable in class org.tribuo.Tribuo
The patch release number.
POLY - Enum constant in enum class org.tribuo.common.libsvm.KernelType
A polynomial kernel of the form (gamma*u'*v + coef0)^degree
Polynomial - Class in org.tribuo.math.kernel
A polynomial kernel, (gamma*u.dot(v) + intercept)^degree.
Polynomial(double, double, double) - Constructor for class org.tribuo.math.kernel.Polynomial
A polynomial kernel, (gamma*u.dot(v) + intercept)^degree.
POLYNOMIAL - Enum constant in enum class org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Uses a Polynomial kernel.
POSITIVE_NAME - Static variable in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
The default positive response.
postConfig() - Method in class org.tribuo.anomaly.example.GaussianAnomalyDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.baseline.DummyClassifierTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.ensemble.AdaBoostTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.example.CheckerboardDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.example.ConcentricCirclesDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.example.DemoLabelDataSource
Configures the class.
postConfig() - Method in class org.tribuo.classification.example.GaussianLabelDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.example.NoisyInterlockingCrescentsDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.sgd.crf.CRFTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.clustering.example.GaussianClusterDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.common.liblinear.LibLinearTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.common.libsvm.LibSVMTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.common.nearest.KNNTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.common.sgd.AbstractFMTrainer
 
postConfig() - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.common.tree.ExtraTreesTrainer
 
postConfig() - Method in class org.tribuo.common.tree.RandomForestTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.common.xgboost.XGBoostTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.columnar.extractors.DateExtractor
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.columnar.extractors.OffsetDateTimeExtractor
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.columnar.processors.field.DateFieldProcessor
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
 
postConfig() - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
postConfig() - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
postConfig() - Method in class org.tribuo.data.columnar.RowProcessor
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.csv.CSVDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.sql.SQLDBConfig
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.text.impl.BasicPipeline
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.text.impl.NgramProcessor
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.text.impl.SimpleStringDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.text.impl.SimpleTextDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.data.text.impl.TokenPipeline
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.datasource.IDXDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.datasource.LibSVMDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.ensemble.BaggingTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.hash.HashCodeHasher
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.hash.MessageDigestHasher
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.hash.ModHashCodeHasher
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
postConfig() - Method in class org.tribuo.interop.onnx.ImageTransformer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.interop.onnx.LabelOneVOneTransformer
 
postConfig() - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.interop.tensorflow.ImageConverter
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.json.JsonDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.math.optimisers.RMSProp
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
 
postConfig() - Method in class org.tribuo.multilabel.example.MultiLabelGaussianDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.example.GaussianDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.example.NonlinearGaussianDataSource
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.liblinear.LibLinearRegressionTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.RegressionFactory
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.sgd.objectives.Huber
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.slm.ElasticNetCDTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.TransformationMap
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.BinningTransformation
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.SimpleTransform
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
 
postConfig() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Used by the OLCUT configuration system, and should not be called by external code.
POW - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Element-wise exponentiation with broadcasting.
PRCurve(double[], double[], double[]) - Constructor for class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
Constructs a precision-recall curve.
precision - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
The precision at the corresponding threshold.
precision(double, double, double, double) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the precision based upon the supplied statistics.
precision(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The precision for this label.
precision(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the precision for this metric target.
precision(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
precision(T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the precision of this label, i.e., the number of true positives divided by the number of true positives plus false positives.
PRECISION - Enum constant in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
The precision, i.e., the true positives divided by the predicted positives.
PRECISION - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The precision, i.e., the number of true positives divided by the number of predicted positives.
PRECISION - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The precision, i.e., the number of true positives divided by the number of predicted positives.
precisionRecallCurve(Label) - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
Calculates the Precision Recall curve for a single label.
precisionRecallCurve(Label, List<Prediction<Label>>) - Static method in enum class org.tribuo.classification.evaluation.LabelMetrics
 
predict(CommandInterpreter, String[]) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Makes a prediction using the loaded model.
predict(Iterable<Example<T>>) - Method in class org.tribuo.common.xgboost.XGBoostModel
Uses the model to predict the label for multiple examples.
predict(Iterable<Example<T>>) - Method in class org.tribuo.Model
Uses the model to predict the output for multiple examples.
predict(Iterable<SequenceExample<T>>) - Method in class org.tribuo.sequence.SequenceModel
Uses the model to predict the output for multiple examples.
predict(Dataset<T>) - Method in class org.tribuo.common.xgboost.XGBoostModel
Uses the model to predict the labels for multiple examples contained in a data set.
predict(Dataset<T>) - Method in class org.tribuo.Model
Uses the model to predict the outputs for multiple examples contained in a data set.
predict(Dataset<T>) - Method in class org.tribuo.transform.TransformedModel
 
predict(Example<Event>) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyModel
 
predict(Example<Event>) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyModel
 
predict(Example<Label>) - Method in class org.tribuo.classification.baseline.DummyClassifierModel
 
predict(Example<Label>) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel
 
predict(Example<Label>) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationModel
 
predict(Example<Label>) - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesModel
 
predict(Example<Label>) - Method in class org.tribuo.classification.sgd.fm.FMClassificationModel
 
predict(Example<Label>) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMModel
 
predict(Example<Label>) - Method in class org.tribuo.classification.sgd.linear.LinearSGDModel
 
predict(Example<ClusterID>) - Method in class org.tribuo.clustering.hdbscan.HdbscanModel
 
predict(Example<ClusterID>) - Method in class org.tribuo.clustering.kmeans.KMeansModel
 
predict(Example<MultiLabel>) - Method in class org.tribuo.multilabel.baseline.ClassifierChainModel
 
predict(Example<MultiLabel>) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelModel
 
predict(Example<MultiLabel>) - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelModel
 
predict(Example<MultiLabel>) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.baseline.DummyRegressionModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.sgd.fm.FMRegressionModel
 
predict(Example<Regressor>) - Method in class org.tribuo.regression.sgd.linear.LinearSGDModel
 
predict(Example<T>) - Method in class org.tribuo.common.nearest.KNNModel
 
predict(Example<T>) - Method in class org.tribuo.common.tree.TreeModel
 
predict(Example<T>) - Method in class org.tribuo.common.xgboost.XGBoostModel
 
predict(Example<T>) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
 
predict(Example<T>) - Method in class org.tribuo.interop.ExternalModel
 
predict(Example<T>) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
 
predict(Example<T>) - Method in class org.tribuo.Model
Uses the model to predict the output for a single example.
predict(Example<T>) - Method in class org.tribuo.transform.TransformedModel
 
predict(SGDVector) - Method in class org.tribuo.common.sgd.FMParameters
Generates an unnormalised prediction by multiplying the weights with the incoming features, adding the bias and adding the feature factors.
predict(SGDVector) - Method in interface org.tribuo.math.FeedForwardParameters
Generates an un-normalized prediction by feeding the features through the parameters.
predict(SGDVector) - Method in class org.tribuo.math.LinearParameters
Generates an unnormalised prediction by leftMultiply'ing the weights with the incoming features.
predict(SGDVector[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Generate a prediction using Viterbi.
predict(SequenceDataset<Label>) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
 
predict(SequenceDataset<T>) - Method in class org.tribuo.sequence.SequenceModel
Uses the model to predict the labels for multiple examples contained in a data set.
predict(SequenceExample<Label>) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
 
predict(SequenceExample<Label>) - Method in class org.tribuo.classification.sgd.crf.CRFModel
 
predict(SequenceExample<T>) - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceModel
 
predict(SequenceExample<T>) - Method in class org.tribuo.sequence.IndependentSequenceModel
 
predict(SequenceExample<T>) - Method in class org.tribuo.sequence.SequenceModel
Uses the model to predict the output for a single example.
predictAndObserve(Iterable<Example<T>>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Feeds the examples to the model, records the predictions and returns them.
predictAndObserve(Example<T>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Feeds the example to the model, records the prediction and returns it.
predictConfidenceUsingCBP(SGDVector[], List<Chunk>) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
This predicts per chunk confidence using the constrained forward backward algorithm from Culotta and McCallum 2004.
prediction - Variable in class org.tribuo.common.sgd.AbstractSGDModel.PredAndActive
The vector prediction.
prediction - Variable in class org.tribuo.interop.oci.OCIModel.PredictionJson
 
Prediction<T extends Output<T>> - Class in org.tribuo
A prediction made by a Model.
Prediction(Prediction<T>, int, Example<T>) - Constructor for class org.tribuo.Prediction
Constructs a prediction from the supplied arguments.
Prediction(T, int, Example<T>) - Constructor for class org.tribuo.Prediction
Constructs a prediction from the supplied arguments.
Prediction(T, Map<String, T>, int, Example<T>, boolean) - Constructor for class org.tribuo.Prediction
Constructs a prediction from the supplied arguments.
PredictionJson(double[][]) - Constructor for class org.tribuo.interop.oci.OCIModel.PredictionJson
 
predictionPath - Variable in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
Path to write model predictions
predictionPath - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Path to write model predictions
predictMarginals(SGDVector[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Generate a prediction using Belief Propagation.
predictOp - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceModel
 
predictOp - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
predictSingle(Example<T>) - Method in class org.tribuo.common.sgd.AbstractSGDModel
Generates the dense vector prediction from the supplied example.
PREFIX - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
Some tokenizers produce "sub-word" tokens.
PreprocessAndSerialize - Class in org.tribuo.data
Reads in a Datasource, processes all the data, and writes it out as a serialized dataset.
PreprocessAndSerialize.PreprocessAndSerializeOptions - Class in org.tribuo.data
Command line options.
PreprocessAndSerializeOptions() - Constructor for class org.tribuo.data.PreprocessAndSerialize.PreprocessAndSerializeOptions
 
preprocessors - Variable in class org.tribuo.data.text.DirectoryFileSource
Document preprocessors that should be run on the documents that make up this data set.
preprocessors - Variable in class org.tribuo.data.text.TextDataSource
Document preprocessors that should be run on the documents that make up this data set.
preTrainingHook(Session, SequenceDataset<T>) - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
A hook for modifying the session state before training starts.
printFeatureMap(Map<String, List<Pair<String, Double>>>, List<String>, PrintStream) - Static method in class org.tribuo.util.HTMLOutput
Formats a feature ranking as a HTML table.
printTree - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Prints the decision tree.
probability - Variable in class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
The probability of that statistic.
process(String) - Method in interface org.tribuo.data.columnar.FieldProcessor
Processes the field value and generates a (possibly empty) list of ColumnarFeatures.
process(String) - Method in class org.tribuo.data.columnar.processors.field.DateFieldProcessor
 
process(String) - Method in class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
 
process(String) - Method in class org.tribuo.data.columnar.processors.field.IdentityProcessor
 
process(String) - Method in class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
 
process(String) - Method in class org.tribuo.data.columnar.processors.field.TextFieldProcessor
 
process(String) - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Deprecated.
process(String) - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
Deprecated.
process(String) - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Deprecated.
process(String) - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
Deprecated.
process(String) - Method in interface org.tribuo.data.columnar.ResponseProcessor
Deprecated.
use ResponseProcessor.process(List) and support multiple values instead. Returns Optional.empty() if it failed to process out a response.
process(String) - Method in class org.tribuo.data.text.impl.NgramProcessor
 
process(String) - Method in interface org.tribuo.data.text.TextProcessor
Extracts features from the supplied text.
process(String, String) - Method in class org.tribuo.data.text.impl.BasicPipeline
 
process(String, String) - Method in class org.tribuo.data.text.impl.NgramProcessor
 
process(String, String) - Method in class org.tribuo.data.text.impl.TokenPipeline
 
process(String, String) - Method in interface org.tribuo.data.text.TextPipeline
Extracts a list of features from the supplied text, using the tag to prepend the feature names.
process(String, String) - Method in interface org.tribuo.data.text.TextProcessor
Extracts features from the supplied text.
process(String, String) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Tokenizes the input using the loaded tokenizer, truncates the token list if it's longer than maxLength - 2 (to account for [CLS] and [SEP] tokens), and then passes the token list to BERTFeatureExtractor.extractExample(java.util.List<java.lang.String>).
process(List<String>) - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
 
process(List<String>) - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
This method always returns Optional.empty().
process(List<String>) - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
process(List<String>) - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
process(List<String>) - Method in interface org.tribuo.data.columnar.ResponseProcessor
Returns Optional.empty() if it failed to process out a response.This method has a default implementation for backwards compatibility with Tribuo 4.0 and 4.1.
process(List<ColumnarFeature>) - Method in interface org.tribuo.data.columnar.FeatureProcessor
Processes a list of ColumnarFeatures, transforming it by adding conjunctions or removing unnecessary features.
process(List<ColumnarFeature>) - Method in class org.tribuo.data.columnar.processors.feature.UniqueProcessor
 
processDoc(String) - Method in interface org.tribuo.data.text.DocumentPreprocessor
Processes the content of part of a document stored as a string, returning a new string.
processDoc(String) - Method in class org.tribuo.data.text.impl.CasingPreprocessor
 
processDoc(String) - Method in class org.tribuo.data.text.impl.NewsPreprocessor
 
processWeights(List<String>) - Static method in class org.tribuo.classification.experiments.ConfigurableTrainTest
Converts the weight text input format into an object suitable for use in a Trainer.
PRODUCER_NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
PRODUCER_VERSION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
projectID - Variable in class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions
Project ID.
projectID - Variable in class org.tribuo.interop.oci.OCIUtil.OCIDSConfig
OCI Data Science project ID.
protobufPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Path to the protobuf containing the network description.
provenance - Variable in class org.tribuo.data.text.impl.SimpleTextDataSource
 
provenance - Variable in class org.tribuo.Model
The model provenance.
PROVENANCE_METADATA_FIELD - Static variable in interface org.tribuo.ONNXExportable
The name of the ONNX metadata field where the provenance information is stored in exported models.
provenanceDiff() - Method in record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Returns the value of the provenanceDiff record component.
provenanceFile - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
Write out the stripped provenance as json.
provenanceOutput - Variable in class org.tribuo.Model
The cached toString of the model provenance.
provenanceOutput - Variable in class org.tribuo.sequence.SequenceModel
 
PSEUDOHUBER - Enum constant in enum class org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Pseudo-huber loss, a differentiable approximation to absolute error
punct(char, int) - Method in class org.tribuo.util.tokens.universal.Range
Sets this range to represent a punctuation character.
PUNCTUATION - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
A PUNCTUATION corresponds to tokens consisting of punctuation characters.
put(VariableInfo) - Method in class org.tribuo.MutableFeatureMap
Adds a variable info into the feature map.

Q

QUANT_PARAMETER_TENSOR_NAMES_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
QUANTIZATION_ANNOTATION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
Quartile - Class in org.tribuo.data.columnar.processors.response
A quartile to split data into 4 chunks.
Quartile(double, double, double) - Constructor for class org.tribuo.data.columnar.processors.response.Quartile
Constructs a quartile with the specified values.
QUARTILE - Enum constant in enum class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns the training data output at the specified fraction of the sorted output.
QuartileResponseProcessor<T extends Output<T>> - Class in org.tribuo.data.columnar.processors.response
Processes the response into quartiles and emits them as classification outputs.
QuartileResponseProcessor(String, String, Quartile, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
Constructs a response processor which emits 4 distinct bins for the output factory to process.
QuartileResponseProcessor(List<String>, List<Quartile>, OutputFactory<T>) - Constructor for class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
Constructs a response processor which emits 4 distinct bins for the output factory to process.
quiet - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Make the XGBoost training procedure quiet.
quiet - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Make the XGBoost training procedure quiet.
QUOTE - Static variable in class org.tribuo.data.csv.CSVIterator
Default quote character.

R

r2() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates R2 for all dimensions.
r2(MetricTarget<Regressor>, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates R^2 based on the supplied statistics.
r2(Regressor) - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates R2 for the supplied dimension.
r2(Regressor, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates R^2 based on the supplied statistics for a single dimension.
R2 - Enum constant in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the R^2 of the predictions.
RANDOM - Enum constant in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation
Initialize centroids by choosing uniformly at random from the data points.
RANDOM - Enum constant in enum class org.tribuo.util.infotheory.example.InformationTheoryDemo.DistributionType
Uniformly randomly generated data.
RandomForestTrainer<T extends Output<T>> - Class in org.tribuo.common.tree
A trainer which produces a random forest.
RandomForestTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int) - Constructor for class org.tribuo.common.tree.RandomForestTrainer
Constructs a RandomForestTrainer with the default seed Trainer.DEFAULT_SEED.
RandomForestTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int, long) - Constructor for class org.tribuo.common.tree.RandomForestTrainer
Constructs a RandomForestTrainer with the supplied seed, trainer, combining function and number of members.
randperm(int, Random) - Static method in class org.tribuo.util.Util
Shuffles the indices in the range [0,size).
randperm(int, SplittableRandom) - Static method in class org.tribuo.util.Util
Shuffles the indices in the range [0,size).
randpermInPlace(double[], SplittableRandom) - Static method in class org.tribuo.util.Util
Shuffles the input.
randpermInPlace(int[], Random) - Static method in class org.tribuo.util.Util
Shuffles the input.
randpermInPlace(int[], SplittableRandom) - Static method in class org.tribuo.util.Util
Shuffles the input.
Range - Class in org.tribuo.util.tokens.universal
A range currently being segmented.
RAW_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
rawLines - Variable in class org.tribuo.data.text.impl.SimpleStringDataSource
Used because OLCUT doesn't support generic Iterables.
RBF - Class in org.tribuo.math.kernel
A Radial Basis Function (RBF) kernel, exp(-gamma*|u-v|^2).
RBF - Enum constant in enum class org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Uses an RBF kernel.
RBF - Enum constant in enum class org.tribuo.common.libsvm.KernelType
An RBF kernel of the form exp(-gamma*|u-v|^2)
RBF(double) - Constructor for class org.tribuo.math.kernel.RBF
A Radial Basis Function (RBF) kernel, exp(-gamma*|u-v|^2).
read() - Method in class org.tribuo.data.text.impl.SimpleStringDataSource
 
read() - Method in class org.tribuo.data.text.impl.SimpleTextDataSource
 
read() - Method in class org.tribuo.data.text.TextDataSource
Reads the data from the Path.
REAL - Enum constant in enum class org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Real valued features.
RealIDInfo - Class in org.tribuo
Same as a RealInfo, but with an additional int id field.
RealIDInfo(String, int, double, double, double, double, int) - Constructor for class org.tribuo.RealIDInfo
Constructs a real id info from the supplied arguments.
RealIDInfo(RealInfo, int) - Constructor for class org.tribuo.RealIDInfo
Constructs a deep copy of the supplied real info and id.
RealInfo - Class in org.tribuo
Stores information about real valued features.
RealInfo(String) - Constructor for class org.tribuo.RealInfo
Creates an empty real info with the supplied name.
RealInfo(String, int) - Constructor for class org.tribuo.RealInfo
Creates a real info with the supplied starting conditions.
RealInfo(String, int, double, double, double, double) - Constructor for class org.tribuo.RealInfo
Creates a real info with the supplied starting conditions.
RealInfo(RealInfo) - Constructor for class org.tribuo.RealInfo
Copy constructor.
RealInfo(RealInfo, String) - Constructor for class org.tribuo.RealInfo
Copy constructor which renames the feature.
rebuild(OrtSession.SessionOptions) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
Closes the session and rebuilds it using the supplied options.
rebuildTensor() - Method in class org.tribuo.interop.tensorflow.TensorFlowUtil.TensorTuple
Recreates the Tensor from the serialized form.
recall - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
The recall at the corresponding threshold.
recall(double, double, double, double) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the recall based upon the supplied statistics.
recall(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The recall for this label.
recall(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the recall for this metric target.
recall(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
recall(T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the recall of this label, i.e., the number of true positives divided by the number of true positives plus false negatives.
RECALL - Enum constant in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
The recall, i.e., the true positives divided by the ground truth positives.
RECALL - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The recall, i.e., the number of true positives divided by the number of ground truth positives.
RECALL - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The recall, i.e., the number of true positives divided by the number of ground truth positives.
RECOMMENDER - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Recommender system, no Tribuo mapping.
reconfigureOrtSession(OrtSession.SessionOptions) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Reconstructs the OrtSession using the supplied options.
recoverDataset() - Method in class org.tribuo.reproducibility.ReproUtil
Return a Dataset used when a model was trained.
recoverTrainer() - Method in class org.tribuo.reproducibility.ReproUtil
Extract the trainer from this repro util.
reduce(double, DoubleUnaryOperator, DoubleBinaryOperator) - Method in class org.tribuo.math.la.DenseVector
Performs a reduction from left to right of this vector.
reduce(double, DoubleUnaryOperator, DoubleBinaryOperator) - Method in interface org.tribuo.math.la.SGDVector
Reduces the vector, applying the transformation to every value (including the implicit zeros) and reducing the output by applying the supplied reduction operator (where the right argument is the current reduction value, and the left argument is the transformed value).
reduce(double, DoubleUnaryOperator, DoubleBinaryOperator) - Method in class org.tribuo.math.la.SparseVector
 
REDUCE_MEAN - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Computes the mean of the input tensor's element along the provided axes.
REDUCE_MIN - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Compute the minimum along the specified axes of the tensor.
REDUCE_SUM - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Compute the sum along the specified axes of the tensor, the axes are the second input.
reduceByName(Merger) - Method in class org.tribuo.Example
Merges features with the same name using the supplied Merger.
reduceByName(Merger) - Method in class org.tribuo.impl.ArrayExample
 
reduceByName(Merger) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
reduceByName(Merger) - Method in class org.tribuo.impl.IndexedArrayExample
 
reduceByName(Merger) - Method in class org.tribuo.impl.ListExample
 
reduceByName(Merger) - Method in class org.tribuo.sequence.SequenceExample
Reduces the features in each example using the supplied Merger.
REF_ATTR_NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
regenerateFeatureInfo() - Method in class org.tribuo.MutableDataset
Rebuilds the feature info by inspecting each example.
regenerateOutputInfo() - Method in class org.tribuo.MutableDataset
Rebuilds the output info by inspecting each example.
RegexFieldProcessor - Class in org.tribuo.data.columnar.processors.field
A FieldProcessor which applies a regex to a field and generates ColumnarFeatures based on the matches.
RegexFieldProcessor(String, String, EnumSet<RegexFieldProcessor.Mode>) - Constructor for class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
Constructs a field processor which emits features when the field value matches the supplied regex.
RegexFieldProcessor(String, Pattern, EnumSet<RegexFieldProcessor.Mode>) - Constructor for class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
Constructs a field processor which emits features when the field value matches the supplied regex.
RegexFieldProcessor.Mode - Enum Class in org.tribuo.data.columnar.processors.field
Matching mode.
regexMappingProcessors - Variable in class org.tribuo.data.columnar.RowProcessor
 
registerAllExtensions(ExtensionRegistry) - Static method in class ai.onnx.proto.OnnxMl
 
registerAllExtensions(ExtensionRegistryLite) - Static method in class ai.onnx.proto.OnnxMl
 
REGRESSION - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Regression, maps to Tribuo's Regressor.
RegressionDataGenerator - Class in org.tribuo.regression.example
Generates two example train and test datasets, used for unit testing.
RegressionEvaluation - Interface in org.tribuo.regression.evaluation
Defines methods that calculate regression performance.
RegressionEvaluator - Class in org.tribuo.regression.evaluation
A Evaluator for multi-dimensional regression using Regressors.
RegressionEvaluator() - Constructor for class org.tribuo.regression.evaluation.RegressionEvaluator
By default, don't use example weights.
RegressionEvaluator(boolean) - Constructor for class org.tribuo.regression.evaluation.RegressionEvaluator
Construct an evaluator.
regressionFactory - Static variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
RegressionFactory - Class in org.tribuo.regression
A factory for creating Regressors and RegressionInfos.
RegressionFactory() - Constructor for class org.tribuo.regression.RegressionFactory
Builds a regression factory using the default split character RegressionFactory.DEFAULT_SPLIT_CHAR.
RegressionFactory(char) - Constructor for class org.tribuo.regression.RegressionFactory
Sets the split character used to parse Regressor instances from Strings.
RegressionFactory.RegressionFactoryProvenance - Class in org.tribuo.regression
Provenance for RegressionFactory.
RegressionFactoryProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.regression.RegressionFactory.RegressionFactoryProvenance
Constructs a provenance from it's marshalled form.
RegressionInfo - Class in org.tribuo.regression
The base class for regression information using Regressors.
RegressionMetric - Class in org.tribuo.regression.evaluation
A EvaluationMetric for Regressors which calculates the metric based on a the true values and the predicted values.
RegressionMetric(MetricTarget<Regressor>, String, ToDoubleBiFunction<MetricTarget<Regressor>, RegressionMetric.Context>) - Constructor for class org.tribuo.regression.evaluation.RegressionMetric
Construct a new RegressionMetric for the supplied metric target, using the supplied function.
RegressionMetric(MetricTarget<Regressor>, String, ToDoubleBiFunction<MetricTarget<Regressor>, RegressionMetric.Context>, boolean) - Constructor for class org.tribuo.regression.evaluation.RegressionMetric
Construct a new RegressionMetric for the supplied metric target, using the supplied function.
RegressionMetrics - Enum Class in org.tribuo.regression.evaluation
An enum of the default RegressionMetrics supported by the multi-dimensional regression evaluation package.
RegressionObjective - Interface in org.tribuo.regression.sgd
An interface for regression objectives.
RegressionSufficientStatistics - Class in org.tribuo.regression.evaluation
The sufficient statistics for regression metrics (i.e., each prediction and each true value).
RegressionSufficientStatistics(ImmutableOutputInfo<Regressor>, List<Prediction<Regressor>>, boolean) - Constructor for class org.tribuo.regression.evaluation.RegressionSufficientStatistics
Constructs the sufficient statistics for regression metrics.
RegressionTreeOptions() - Constructor for class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
Regressor - Class in org.tribuo.regression
An Output for n-dimensional real valued regression.
Regressor(String[], double[]) - Constructor for class org.tribuo.regression.Regressor
Constructs a regressor from the supplied named values.
Regressor(String[], double[], double[]) - Constructor for class org.tribuo.regression.Regressor
Constructs a regressor from the supplied named values.
Regressor(String, double) - Constructor for class org.tribuo.regression.Regressor
Constructs a regressor containing a single dimension, using Double.NaN as the variance.
Regressor(String, double, double) - Constructor for class org.tribuo.regression.Regressor
Constructs a regressor containing a single dimension.
Regressor(Regressor.DimensionTuple[]) - Constructor for class org.tribuo.regression.Regressor
Constructs a regressor from the supplied dimension tuples.
Regressor.DimensionTuple - Class in org.tribuo.regression
A Regressor which contains a single dimension, used internally when the model implementation doesn't natively support multi-dimensional regression outputs.
RegressorConverter - Class in org.tribuo.interop.tensorflow
Can convert a Regressor to a TFloat32 vector and a TFloat32 into a Prediction or Regressor.
RegressorConverter() - Constructor for class org.tribuo.interop.tensorflow.RegressorConverter
Constructs a RegressorConverter.
RegressorImpurity - Interface in org.tribuo.regression.rtree.impurity
Calculates a tree impurity score based on the regression targets.
RegressorImpurity.ImpurityTuple - Class in org.tribuo.regression.rtree.impurity
Tuple class for the impurity and summed weight.
RegressorTrainingNode - Class in org.tribuo.regression.rtree.impl
A decision tree node used at training time.
RegressorTrainingNode(RegressorImpurity, RegressorTrainingNode.InvertedData, int, String, int, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>, AbstractTrainingNode.LeafDeterminer) - Constructor for class org.tribuo.regression.rtree.impl.RegressorTrainingNode
Constructs a tree training node for regression problems.
RegressorTrainingNode.InvertedData - Class in org.tribuo.regression.rtree.impl
Tuple containing an inverted dataset (i.e., feature-wise not exmaple-wise).
RegressorTransformer - Class in org.tribuo.interop.onnx
Can convert an OnnxValue into a Prediction or Regressor.
RegressorTransformer() - Constructor for class org.tribuo.interop.onnx.RegressorTransformer
Constructs a RegressorTransformer.
remove(int) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
remove(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
removeAll(Collection<?>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
removeAttribute(int) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
removeDim(int) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
removeExternalData(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
removeFeatures(List<Feature>) - Method in class org.tribuo.Example
Removes all features in this list from the Example.
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.ArrayExample
 
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.IndexedArrayExample
 
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.ListExample
 
removeFeatures(List<Feature>) - Method in class org.tribuo.sequence.SequenceExample
Removes the features in the supplied list from each example contained in this sequence.
removeGraphs(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
removeInitializationBinding(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
removeInitializer(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
removeInput(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
removeMetadataProps(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
removeNode(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
removeOpsetImport(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
removeOther(IntArrayContainer, int[], IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
Copies from input to output excluding the values in otherArray.
removeOutput(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
removeProvenances - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
The provenances to remove
removeQuantizationAnnotation(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
removeQuantParameterTensorNames(int) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
removeSparseInitializer(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
removeSparseTensors(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
removeTensors(int) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
removeTrainingInfo(int) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
removeUpdateBinding(int) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
removeValueInfo(int) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
rename(String) - Method in class org.tribuo.CategoricalIDInfo
 
rename(String) - Method in class org.tribuo.CategoricalInfo
 
rename(String) - Method in class org.tribuo.RealIDInfo
 
rename(String) - Method in class org.tribuo.RealInfo
 
rename(String) - Method in interface org.tribuo.VariableInfo
Rename generates a fresh VariableInfo with the new name.
replaceNewlinesWithSpaces - Variable in class org.tribuo.data.columnar.RowProcessor
 
reproducedFeatures() - Method in record class org.tribuo.reproducibility.ReproUtil.FeatureDiff
Returns the value of the reproducedFeatures record component.
reproducedOutput() - Method in record class org.tribuo.reproducibility.ReproUtil.OutputDiff
Returns the value of the reproducedOutput record component.
reproduceFromModel() - Method in class org.tribuo.reproducibility.ReproUtil
Using a supplied Model object, recreates an identical model object that the provenance describes.
reproduceFromProvenance() - Method in class org.tribuo.reproducibility.ReproUtil
Recreates a model object using the ModelProvenance supplied when the ReproUtil object was created.
ReproUtil<T extends Output<T>> - Class in org.tribuo.reproducibility
Reproducibility utility based on Tribuo's provenance objects.
ReproUtil(Model<T>) - Constructor for class org.tribuo.reproducibility.ReproUtil
Creates a ReproUtil instance.
ReproUtil(ModelProvenance, Class<T>) - Constructor for class org.tribuo.reproducibility.ReproUtil
Creates a ReproUtil instance
ReproUtil.FeatureDiff - Record Class in org.tribuo.reproducibility
Record for any differences between feature sets.
ReproUtil.ModelReproduction<T extends Output<T>> - Record Class in org.tribuo.reproducibility
Record for a model reproduction.
ReproUtil.OutputDiff<T extends Output<T>> - Record Class in org.tribuo.reproducibility
Record for any differences between output domains.
reset() - Method in class org.tribuo.math.optimisers.AdaDelta
 
reset() - Method in class org.tribuo.math.optimisers.AdaGrad
 
reset() - Method in class org.tribuo.math.optimisers.AdaGradRDA
 
reset() - Method in class org.tribuo.math.optimisers.Adam
 
reset() - Method in class org.tribuo.math.optimisers.ParameterAveraging
 
reset() - Method in class org.tribuo.math.optimisers.Pegasos
 
reset() - Method in class org.tribuo.math.optimisers.RMSProp
 
reset() - Method in class org.tribuo.math.optimisers.SGD
 
reset() - Method in interface org.tribuo.math.StochasticGradientOptimiser
Resets the optimiser so it's ready to optimise a new Parameters.
reset() - Method in class org.tribuo.util.MeanVarianceAccumulator
Resets this accumulator to the starting state.
reset(CharSequence) - Method in class org.tribuo.util.tokens.impl.BreakIteratorTokenizer
 
reset(CharSequence) - Method in class org.tribuo.util.tokens.impl.NonTokenizer
 
reset(CharSequence) - Method in class org.tribuo.util.tokens.impl.ShapeTokenizer
 
reset(CharSequence) - Method in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
reset(CharSequence) - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
 
reset(CharSequence) - Method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
 
reset(CharSequence) - Method in interface org.tribuo.util.tokens.Tokenizer
Resets the tokenizer so that it operates on a new sequence of characters.
reset(CharSequence) - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Reset state of tokenizer to clean slate.
reshape(int[]) - Method in class org.tribuo.math.la.DenseMatrix
 
reshape(int[]) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
reshape(int[]) - Method in class org.tribuo.math.la.DenseVector
 
reshape(int[]) - Method in class org.tribuo.math.la.SparseVector
 
reshape(int[]) - Method in interface org.tribuo.math.la.Tensor
Reshapes the Tensor to the supplied shape.
RESOURCE_HASH - Static variable in interface org.tribuo.provenance.DataSourceProvenance
The name of the provenance field for the resource hash.
Resources - Class in org.tribuo.tests
Utils for working with classpath resources at test time.
responseProcessor - Variable in class org.tribuo.data.columnar.RowProcessor
 
ResponseProcessor<T extends Output<T>> - Interface in org.tribuo.data.columnar
An interface that will take the response field and produce an Output.
restoreMarshalledVariables(Session, Map<String, TensorFlowUtil.TensorTuple>) - Static method in class org.tribuo.interop.tensorflow.TensorFlowUtil
Writes a map containing the name of each Tensorflow VariableV2 and the associated parameter array into the supplied session.
ResultSetIterator - Class in org.tribuo.data.sql
An iterator over a ResultSet returned from JDBC.
ResultSetIterator(ResultSet) - Constructor for class org.tribuo.data.sql.ResultSetIterator
Construct a result set iterator over the supplied result set.
ResultSetIterator(ResultSet, int) - Constructor for class org.tribuo.data.sql.ResultSetIterator
Constructs a result set iterator over the supplied result set using the specified fetch buffer size.
retainAll(Collection<?>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
RF - Enum constant in enum class org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
rho - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
Rho for RMSProp, AdaDelta, SGD with Momentum.
rho - Variable in class org.tribuo.math.optimisers.SGD
 
rightMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseMatrix
 
rightMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseSparseMatrix
rightMultiply is very inefficient on DenseSparseMatrix due to the storage format.
rightMultiply(SGDVector) - Method in interface org.tribuo.math.la.Matrix
Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
rmse() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates the RMSE for all dimensions.
rmse(MetricTarget<Regressor>, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the RMSE based on the supplied statistics.
rmse(Regressor) - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates the Root Mean Squared Error (i.e., the square root of the average squared errors across all data points) for the supplied dimension.
rmse(Regressor, RegressionSufficientStatistics) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the RMSE based on the supplied statistics for a single dimension.
RMSE - Enum constant in enum class org.tribuo.regression.evaluation.RegressionMetrics
Calculates the Root Mean Squared Error of the predictions.
RMSProp - Class in org.tribuo.math.optimisers
An implementation of the RMSProp gradient optimiser.
RMSProp(double, double) - Constructor for class org.tribuo.math.optimisers.RMSProp
Constructs an RMSProp gradient optimiser using the specified parameters with epsilon set to 1e-8 and decay to 0.0.
RMSProp(double, double, double, double) - Constructor for class org.tribuo.math.optimisers.RMSProp
Constructs an RMSProp gradient optimiser using the specified parameters.
RMSPROP - Enum constant in enum class org.tribuo.interop.tensorflow.GradientOptimiser
The RMSprop optimiser.
RMSPROP - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
The RMSProp optimiser.
rng - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
rng - Variable in class org.tribuo.classification.example.DemoLabelDataSource
 
rng - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
rng - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
rng - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
 
rng - Variable in class org.tribuo.ensemble.BaggingTrainer
 
rng - Variable in class org.tribuo.evaluation.KFoldSplitter
 
rng - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
ROC(double[], double[], double[]) - Constructor for class org.tribuo.classification.evaluation.LabelEvaluationUtil.ROC
Constructs an ROC curve.
ROUNDROBIN - Enum constant in enum class org.tribuo.datasource.AggregateDataSource.IterationOrder
Round-robins the iterators (i.e., chooses one from each in turn).
Row<T> - Class in org.tribuo.util.infotheory.impl
A row of values from a RowList.
Row(long, List<String>, Map<String, String>) - Constructor for class org.tribuo.data.columnar.ColumnarIterator.Row
Constructs a row from a columnar source.
rowIterator() - Method in class org.tribuo.data.columnar.ColumnarDataSource
The iterator that emits ColumnarIterator.Row objects from the underlying data source.
rowIterator() - Method in class org.tribuo.data.csv.CSVDataSource
 
rowIterator() - Method in class org.tribuo.data.sql.SQLDataSource
 
rowIterator() - Method in class org.tribuo.json.JsonDataSource
 
RowList<T> - Class in org.tribuo.util.infotheory.impl
An implementation of a List which wraps a set of lists.
RowList(Set<List<T>>) - Constructor for class org.tribuo.util.infotheory.impl.RowList
Constructs a RowList from a set of lists.
rowProcessor - Variable in class org.tribuo.data.columnar.ColumnarDataSource
 
rowProcessor - Variable in class org.tribuo.data.DataOptions
The name of the row processor from the config file.
RowProcessor<T extends Output<T>> - Class in org.tribuo.data.columnar
A processor which takes a Map of String to String and returns an Example.
RowProcessor() - Constructor for class org.tribuo.data.columnar.RowProcessor
For olcut.
RowProcessor(List<FieldExtractor<?>>, FieldExtractor<Float>, ResponseProcessor<T>, Map<String, FieldProcessor>, Map<String, FieldProcessor>, Set<FeatureProcessor>) - Constructor for class org.tribuo.data.columnar.RowProcessor
Constructs a RowProcessor using the supplied responseProcessor to extract the response variable, and the supplied fieldProcessorMap to control which fields are parsed and how they are parsed.
RowProcessor(List<FieldExtractor<?>>, FieldExtractor<Float>, ResponseProcessor<T>, Map<String, FieldProcessor>, Map<String, FieldProcessor>, Set<FeatureProcessor>, boolean) - Constructor for class org.tribuo.data.columnar.RowProcessor
Constructs a RowProcessor using the supplied responseProcessor to extract the response variable, and the supplied fieldProcessorMap to control which fields are parsed and how they are parsed.
RowProcessor(List<FieldExtractor<?>>, FieldExtractor<Float>, ResponseProcessor<T>, Map<String, FieldProcessor>, Set<FeatureProcessor>) - Constructor for class org.tribuo.data.columnar.RowProcessor
Constructs a RowProcessor using the supplied responseProcessor to extract the response variable, and the supplied fieldProcessorMap to control which fields are parsed and how they are parsed.
RowProcessor(List<FieldExtractor<?>>, ResponseProcessor<T>, Map<String, FieldProcessor>) - Constructor for class org.tribuo.data.columnar.RowProcessor
Constructs a RowProcessor using the supplied responseProcessor to extract the response variable, and the supplied fieldProcessorMap to control which fields are parsed and how they are parsed.
RowProcessor(ResponseProcessor<T>, Map<String, FieldProcessor>) - Constructor for class org.tribuo.data.columnar.RowProcessor
Constructs a RowProcessor using the supplied responseProcessor to extract the response variable, and the supplied fieldProcessorMap to control which fields are parsed and how they are parsed.
RowProcessor(ResponseProcessor<T>, Map<String, FieldProcessor>, Set<FeatureProcessor>) - Constructor for class org.tribuo.data.columnar.RowProcessor
Constructs a RowProcessor using the supplied responseProcessor to extract the response variable, and the supplied fieldProcessorMap to control which fields are parsed and how they are parsed.
rowScaleInPlace(DenseVector) - Method in class org.tribuo.math.la.DenseMatrix
 
rowScaleInPlace(DenseVector) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
rowScaleInPlace(DenseVector) - Method in interface org.tribuo.math.la.Matrix
Scales each row by the appropriate value in the DenseVector.
rowSum() - Method in class org.tribuo.math.la.DenseMatrix
 
rowSum() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
rowSum() - Method in interface org.tribuo.math.la.Matrix
Generates a DenseVector representing the sum of each row.
rowSum(int) - Method in class org.tribuo.math.la.DenseMatrix
Calculates the sum of the specified row.
rType - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Regression type to use.
rType - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Regression type to use.
run(ConfigurationManager, DataOptions, Trainer<Label>) - Static method in class org.tribuo.classification.TrainTestHelper
This method trains a model on the specified training data, and evaluates it on the specified test data.
RunAll - Class in org.tribuo.classification.experiments
Trains and tests a model using the supplied data, for each trainer inside a configuration file.
RunAll() - Constructor for class org.tribuo.classification.experiments.RunAll
 
RunAll.RunAllOptions - Class in org.tribuo.classification.experiments
Command line options.
RunAllOptions() - Constructor for class org.tribuo.classification.experiments.RunAll.RunAllOptions
 

S

S_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
sampleData(String, List<Token>) - Method in class org.tribuo.classification.explanations.lime.LIMEText
Samples a new dataset from the input text.
sampleFromCDF(double[], Random) - Static method in class org.tribuo.util.Util
Samples an index from the supplied cdf.
sampleFromCDF(double[], SplittableRandom) - Static method in class org.tribuo.util.Util
Samples an index from the supplied cdf.
sampleInts(Random, int, int) - Static method in class org.tribuo.util.Util
Samples an array of ints from the supplied rng in [0,range).
samplePoint(Random, ImmutableFeatureMap, long, SparseVector) - Static method in class org.tribuo.classification.explanations.lime.LIMEBase
Samples a single example from the supplied feature map and input vector.
SAMPLES_RATIO - Static variable in class org.tribuo.util.infotheory.InformationTheory
The ratio of samples to symbols before emitting a warning.
SAMPLES_RATIO - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
The ratio of samples to symbols before emitting a warning.
sampleStandardDeviation(Collection<V>) - Static method in class org.tribuo.util.Util
Computes the sample standard deviation of the collection.
sampleVariance(Collection<V>) - Static method in class org.tribuo.util.Util
Computes the sample variance of the collection.
save(Path, boolean) - Method in class org.tribuo.datasource.IDXDataSource.IDXData
Writes out this IDXData to the specified path.
save(Path, Dataset<T>, String) - Method in class org.tribuo.data.csv.CSVSaver
Saves the dataset to the specified path.
save(Path, Dataset<T>, Set<String>) - Method in class org.tribuo.data.csv.CSVSaver
Saves the dataset to the specified path.
saveCSV(CommandInterpreter, String) - Method in class org.tribuo.data.DatasetExplorer
Saves out the dataset as a CSV file.
saveModel(Model<T>) - Method in class org.tribuo.data.DataOptions
Saves the model out to the path in DataOptions.outputPath.
saveONNXModel(String, long, Path) - Method in interface org.tribuo.ONNXExportable
Exports this Model as an ONNX file.
scalarAddInPlace(double) - Method in interface org.tribuo.math.la.Tensor
Adds scalar to each element of this Tensor.
scalarBuilder(ONNXContext, String, double) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the scalar value.
scalarBuilder(ONNXContext, String, float) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the scalar value.
scalarBuilder(ONNXContext, String, int) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the scalar value.
scalarBuilder(ONNXContext, String, long) - Static method in class org.tribuo.util.onnx.ONNXUtils
Builds a TensorProto containing the scalar value.
scale(double) - Method in class org.tribuo.math.la.DenseVector
 
scale(double) - Method in interface org.tribuo.math.la.SGDVector
Generates a new vector with each element scaled by coefficient.
scale(double) - Method in class org.tribuo.math.la.SparseVector
 
scaleFeatures - Variable in class org.tribuo.data.DataOptions
Scales the features to the range 0-1 independently.
scaleIncZeros - Variable in class org.tribuo.data.DataOptions
Includes implicit zeros in the scale range calculation.
scaleInPlace(double) - Method in interface org.tribuo.math.la.Tensor
Scales each element of this Tensor by coefficient.
scaleInPlace(double) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
scaleInPlace(double) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
score - Variable in class org.tribuo.classification.Label
The score of the label.
SCORE - Enum constant in enum class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions.Mode
Score a deployed model.
scoreChunks(SequenceExample<Label>, List<Chunk>) - Method in class org.tribuo.classification.sgd.crf.CRFModel
Scores the chunks using constrained belief propagation.
scoreDimension(int, SparseVector) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionModel
Makes a prediction for a single dimension.
scoreDimension(int, SparseVector) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseModel
Makes a prediction for a single dimension.
scoreDimension(int, SparseVector) - Method in class org.tribuo.regression.slm.SparseLinearModel
 
scores - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainBPResults
The local clique scores (i.e., the linear model scores).
scores - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainViterbiResults
The pre-viterbi scores.
scoreSubsequences(SequenceExample<Label>, List<Prediction<Label>>, List<SUB>) - Method in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel
The scoring function for the subsequences.
scoreSubsequences(SequenceExample<Label>, List<Prediction<Label>>, List<SUB>) - Method in class org.tribuo.classification.sgd.crf.CRFModel
 
SECOND - Enum constant in enum class org.tribuo.util.infotheory.WeightedInformationTheory.VariableSelector
The second variable is weighted.
SECOND_CLASS - Static variable in class org.tribuo.classification.example.DemoLabelDataSource
The second class.
secondCount - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
The second marginal distribution.
secondDimensionName - Static variable in class org.tribuo.regression.example.RegressionDataGenerator
Name of the second output dimension.
seed - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
seed - Variable in class org.tribuo.classification.ensemble.ClassificationEnsembleOptions
RNG seed.
seed - Variable in class org.tribuo.classification.example.DemoLabelDataSource
 
seed - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
RNG seed.
seed - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
seed - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
 
seed - Variable in class org.tribuo.data.DataOptions
RNG seed.
seed - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
Seed for the RNG.
seed - Variable in class org.tribuo.ensemble.BaggingTrainer
 
seed - Variable in class org.tribuo.evaluation.KFoldSplitter
 
seed - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
SEGMENT_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
SEMICOLON - Enum constant in enum class org.tribuo.data.DataOptions.Delimiter
Semicolon separator.
SENTIMENT_ANALYSIS - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Sentiment analysis, no strict Tribuo mapping.
SEPARATOR - Static variable in class org.tribuo.data.csv.CSVIterator
Default separator character.
SEPARATOR_TOKEN - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Default separator token name.
SeqTest - Class in org.tribuo.classification.sgd.crf
Build and run a sequence classifier on a generated dataset.
SeqTest() - Constructor for class org.tribuo.classification.sgd.crf.SeqTest
 
SeqTest.CRFOptions - Class in org.tribuo.classification.sgd.crf
Command line options.
SeqTrainTest - Class in org.tribuo.classification.sequence
Build and run a sequence classifier on a generated or serialized dataset using the trainer specified in the configuration file.
SeqTrainTest() - Constructor for class org.tribuo.classification.sequence.SeqTrainTest
 
SeqTrainTest.SeqTrainTestOptions - Class in org.tribuo.classification.sequence
Command line options.
SeqTrainTestOptions() - Constructor for class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
 
SEQUENCE_TYPE - Enum constant in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
SEQUENCE_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto
 
SequenceDataGenerator - Class in org.tribuo.classification.sequence.example
A data generator for smoke testing sequence label models.
SequenceDataset<T extends Output<T>> - Class in org.tribuo.sequence
A class for sets of data, which are used to train and evaluate classifiers.
SequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.SequenceDataset
 
SequenceDataSource<T extends Output<T>> - Interface in org.tribuo.sequence
A interface for things that can be given to a SequenceDataset's constructor.
SequenceEvaluation<T extends Output<T>> - Interface in org.tribuo.sequence
An immutable evaluation of a specific sequence model and dataset.
SequenceEvaluator<T extends Output<T>,E extends SequenceEvaluation<T>> - Interface in org.tribuo.sequence
An evaluation factory which produces immutable SequenceEvaluations of a given SequenceDataset using the given SequenceModel.
SequenceExample<T extends Output<T>> - Class in org.tribuo.sequence
A sequence of examples, used for sequence classification.
SequenceExample() - Constructor for class org.tribuo.sequence.SequenceExample
Creates an empty sequence example.
SequenceExample(List<Example<T>>) - Constructor for class org.tribuo.sequence.SequenceExample
Creates a sequence example from the list of examples.
SequenceExample(List<Example<T>>, float) - Constructor for class org.tribuo.sequence.SequenceExample
Creates a sequence example from the list of examples, setting the weight.
SequenceExample(List<T>, List<? extends List<? extends Feature>>) - Constructor for class org.tribuo.sequence.SequenceExample
Creates a sequence example from the supplied outputs and list of list of features.
SequenceExample(List<T>, List<? extends List<? extends Feature>>, boolean) - Constructor for class org.tribuo.sequence.SequenceExample
Creates a sequence example from the supplied weight, outputs and list of list of features.
SequenceExample(List<T>, List<? extends List<? extends Feature>>, float) - Constructor for class org.tribuo.sequence.SequenceExample
Creates a sequence example from the supplied weight, outputs and list of list of features.
SequenceExample(List<T>, List<? extends List<? extends Feature>>, float, boolean) - Constructor for class org.tribuo.sequence.SequenceExample
Creates a sequence example from the supplied weight, outputs and list of list of features.
SequenceExample(SequenceExample<T>) - Constructor for class org.tribuo.sequence.SequenceExample
Creates a deep copy of the supplied sequence example.
SequenceFeatureConverter - Interface in org.tribuo.interop.tensorflow.sequence
Converts a sequence example into a feed dict suitable for TensorFlow.
SequenceModel<T extends Output<T>> - Class in org.tribuo.sequence
A prediction model, which is used to predict outputs for unseen instances.
SequenceModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.sequence.SequenceModel
Builds a SequenceModel.
SequenceModelExplorer - Class in org.tribuo.sequence
A CLI for interacting with a SequenceModel.
SequenceModelExplorer() - Constructor for class org.tribuo.sequence.SequenceModelExplorer
Builds a sequence model explorer shell.
SequenceModelExplorer.SequenceModelExplorerOptions - Class in org.tribuo.sequence
Command line options.
SequenceModelExplorerOptions() - Constructor for class org.tribuo.sequence.SequenceModelExplorer.SequenceModelExplorerOptions
 
SequenceOutputConverter<T extends Output<T>> - Interface in org.tribuo.interop.tensorflow.sequence
Converts a TensorFlow output tensor into a list of predictions, and a Tribuo sequence example into a Tensorflow tensor suitable for training.
SequenceTrainer<T extends Output<T>> - Interface in org.tribuo.sequence
An interface for things that can train sequence prediction models.
SEQUENTIAL - Enum constant in enum class org.tribuo.datasource.AggregateDataSource.IterationOrder
Iterates each dataset sequentially, in the order of the sources list.
SERIALIZED - Enum constant in enum class org.tribuo.data.DataOptions.InputFormat
Serialized Tribuo datasets.
serializeProvenance(ModelProvenance) - Method in interface org.tribuo.ONNXExportable
Serializes the model provenance to a String.
SERIALIZER - Static variable in interface org.tribuo.ONNXExportable
The provenance serializer.
session - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
set(char[], int, int) - Method in class org.tribuo.util.tokens.universal.Range
Sets the character range.
set(char, char, int) - Method in class org.tribuo.util.tokens.universal.Range
Sets the first two characters in the range, and the type to NGRAM.
set(char, int) - Method in class org.tribuo.util.tokens.universal.Range
Sets the first character in the range.
set(int, double) - Method in class org.tribuo.math.la.DenseVector
 
set(int, double) - Method in interface org.tribuo.math.la.SGDVector
Sets the index to the value.
set(int, double) - Method in class org.tribuo.math.la.SparseVector
 
set(int, int, double) - Method in class org.tribuo.math.la.DenseMatrix
 
set(int, int, double) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
set(int, int, double) - Method in interface org.tribuo.math.la.Matrix
Sets an element at the supplied location.
set(int, Row<T>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
set(Feature) - Method in class org.tribuo.Example
Overwrites the feature with the matching name.
set(Feature) - Method in class org.tribuo.impl.ArrayExample
 
set(Feature) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
set(Feature) - Method in class org.tribuo.impl.ListExample
 
set(Tensor[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
 
set(Tensor[]) - Method in class org.tribuo.common.sgd.FMParameters
 
set(Tensor[]) - Method in class org.tribuo.math.LinearParameters
 
set(Tensor[]) - Method in interface org.tribuo.math.Parameters
Set the underlying Tensor array to newWeights.
setAlgorithm(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
setAlgorithm(OnnxMl.GraphProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field represents a training algorithm step.
setAttribute(int, OnnxMl.AttributeProto) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
setAttribute(int, OnnxMl.AttributeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
Additional named attributes.
setBatchSize(int) - Method in class org.tribuo.interop.ExternalModel
Sets a new batch size.
setBatchSize(int) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Sets a new batch size.
setBegin(long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 begin = 1;
setCacheSize(double) - Method in class org.tribuo.common.libsvm.SVMParameters
Sets the cache size.
setCheckpointDirectory(String) - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Sets the checkpoint directory.
setCheckpointName(String) - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Sets the checkpoint name.
setCoeff(double) - Method in class org.tribuo.common.libsvm.SVMParameters
Sets the coefficient.
setConfidenceType(CRFModel.ConfidenceType) - Method in class org.tribuo.classification.sgd.crf.CRFModel
Sets the inference method used for confidence prediction.
setCost(double) - Method in class org.tribuo.common.libsvm.SVMParameters
Sets the cost for C_SVC.
setDataLocation(OnnxMl.TensorProto.DataLocation) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
setDataType(int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The data type of the tensor.
setDegree(int) - Method in class org.tribuo.common.libsvm.SVMParameters
Sets the degree of the polynomial kernel.
setDenotation(String) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
setDenotation(String) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
setDenotationBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
Standard denotation can optionally be used to denote tensor dimensions with standard semantic descriptions to ensure that operations are applied to the correct axis of a tensor.
setDenotationBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
An optional denotation can be used to denote the whole type with a standard semantic description as to what is stored inside.
setDim(int, OnnxMl.TensorShapeProto.Dimension) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
setDim(int, OnnxMl.TensorShapeProto.Dimension.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
repeated .onnx.TensorShapeProto.Dimension dim = 1;
setDimParam(String) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
namespace Shape
setDimParamBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
namespace Shape
setDims(int, long) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The shape of the underlying dense-tensor: [dim_1, dim_2, ...
setDims(int, long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
The shape of the tensor.
setDimValue(long) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
int64 dim_value = 1;
setDocString(String) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
A human-readable documentation for this attribute.
setDocString(String) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A human-readable documentation for this graph.
setDocString(String) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
A human-readable documentation for this model.
setDocString(String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
A human-readable documentation for this node.
setDocString(String) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
A human-readable documentation for this tensor.
setDocString(String) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
A human-readable documentation for this value.
setDocStringBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
A human-readable documentation for this attribute.
setDocStringBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A human-readable documentation for this graph.
setDocStringBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
A human-readable documentation for this model.
setDocStringBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
A human-readable documentation for this node.
setDocStringBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
A human-readable documentation for this tensor.
setDocStringBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
A human-readable documentation for this value.
setDomain(String) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Domain name of the model.
setDomain(String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The domain of the OperatorSet that specifies the operator named by op_type.
setDomain(String) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The domain of the operator set being identified.
setDomain(String) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
When missing, the domain is the same as the model's.
setDomainBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Domain name of the model.
setDomainBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The domain of the OperatorSet that specifies the operator named by op_type.
setDomainBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The domain of the operator set being identified.
setDomainBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
When missing, the domain is the same as the model's.
setDoubleData(int, double) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
setElements(DenseVector) - Method in class org.tribuo.math.la.DenseVector
Sets all the elements of this vector to be the same as other.
setElemType(int) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
setElemType(int) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
This field MUST NOT have the value of UNDEFINED This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
setElemType(OnnxMl.TypeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
setElemType(OnnxMl.TypeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
The type and optional shape of each element of the sequence.
setEnd(long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
optional int64 end = 2;
setEpsilon(double) - Method in class org.tribuo.common.libsvm.SVMParameters
Sets the termination closeness.
setExternalData(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
setExternalData(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Data can be stored inside the protobuf file using type-specific fields or raw_data.
setF(float) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
Exactly ONE of the following fields must be present for this version of the IR
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
setField(Descriptors.FieldDescriptor, Object) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
setFieldName(String) - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
Deprecated.
setFieldName(String) - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
Deprecated.
setFieldName(String) - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
Deprecated.
setFieldName(String) - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
Deprecated.
setFieldName(String) - Method in interface org.tribuo.data.columnar.ResponseProcessor
Deprecated.
Response processors should be immutable; downstream objects assume that they are Set the field name this ResponseProcessor uses.
setFloatData(int, float) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
setFloats(int, float) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of floats
setG(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
setG(OnnxMl.GraphProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
graph
setGamma(double) - Method in class org.tribuo.common.libsvm.SVMParameters
Sets gamma in the RBF kernel.
setGenerateNgrams(boolean) - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Controls if the tokenizer generates ngrams.
setGenerateUnigrams(boolean) - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Controls if the tokenizer generates unigrams.
setGraph(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
setGraph(OnnxMl.GraphProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The parameterized graph that is evaluated to execute the model.
setGraphs(int, OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
setGraphs(int, OnnxMl.GraphProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of graph
setI(long) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
int
setIndices(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
setIndices(OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The indices of the non-default values, which may be stored in one of two formats.
setInitialization(OnnxMl.GraphProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
setInitialization(OnnxMl.GraphProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field describes a graph to compute the initial tensors upon starting the training process.
setInitializationBinding(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
setInitializationBinding(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.
setInitializer(int, OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
setInitializer(int, OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
A list of named tensor values, used to specify constant inputs of the graph.
setInput(int, OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
setInput(int, OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The inputs and outputs of the graph.
setInput(int, String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
setInt32Data(int, int) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
setInt64Data(int, long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For int64.
setInts(int, long) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of ints
setInvocationCount(int) - Method in class org.tribuo.classification.baseline.DummyClassifierTrainer
 
setInvocationCount(int) - Method in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
setInvocationCount(int) - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
 
setInvocationCount(int) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
 
setInvocationCount(int) - Method in class org.tribuo.clustering.hdbscan.HdbscanTrainer
 
setInvocationCount(int) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
setInvocationCount(int) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
setInvocationCount(int) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
setInvocationCount(int) - Method in class org.tribuo.common.nearest.KNNTrainer
 
setInvocationCount(int) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
setInvocationCount(int) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
setInvocationCount(int) - Method in class org.tribuo.common.xgboost.XGBoostTrainer
 
setInvocationCount(int) - Method in class org.tribuo.ensemble.BaggingTrainer
 
setInvocationCount(int) - Method in class org.tribuo.hash.HashingTrainer
 
setInvocationCount(int) - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
setInvocationCount(int) - Method in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
 
setInvocationCount(int) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
 
setInvocationCount(int) - Method in class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
 
setInvocationCount(int) - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
 
setInvocationCount(int) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
 
setInvocationCount(int) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
 
setInvocationCount(int) - Method in class org.tribuo.regression.slm.ElasticNetCDTrainer
 
setInvocationCount(int) - Method in class org.tribuo.regression.slm.SLMTrainer
 
setInvocationCount(int) - Method in interface org.tribuo.Trainer
Set the internal state of the trainer to the provided number of invocations of the train method.
setInvocationCount(int) - Method in class org.tribuo.transform.TransformTrainer
 
setIrVersion(long) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the IR this model targets.
setKey(String) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string key = 1;
setKeyBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string key = 1;
setKeyType(int) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST have a valid TensorProto.DataType value This field MUST be present for this version of the IR.
setLabelOrder(List<Label>) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
Sets the label order used in LabelConfusionMatrix.toString().
setLabelOrder(List<MultiLabel>) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
Sets the label order used in MultiLabelConfusionMatrix.toString().
setLabelOrder(List<T>) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
Sets the label order this confusion matrix uses in toString.
setLabelWeights(Map<Label, Float>) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
 
setLabelWeights(Map<Label, Float>) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
 
setLabelWeights(Map<Label, Float>) - Method in interface org.tribuo.classification.WeightedLabels
Sets the label weights used by this trainer.
setMapType(OnnxMl.TypeProto.Map) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
setMapType(OnnxMl.TypeProto.Map.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a map.
setMaxTokenLength(int) - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
Sets the maximum token length this tokenizer will generate.
setMetadataProps(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
setMetadataProps(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Named metadata values; keys should be distinct.
setMetadataValue(String, Object) - Method in class org.tribuo.Example
Puts the specified key, value pair into the metadata.
setModelVersion(long) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the graph encoded.
setName(String) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The name field MUST be present for this version of the IR.
setName(String) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The name of the graph.
setName(String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
An optional identifier for this node in a graph.
setName(String) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Optionally, a name for the tensor.
setName(String) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
The name is optional but significant when provided.
setName(String) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR.
setName(String) - Method in class org.tribuo.Model
Sets the model name.
setName(String) - Method in class org.tribuo.sequence.SequenceModel
Sets the model name.
setName(String) - Method in class org.tribuo.util.onnx.ONNXContext
Sets the graph name.
setNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The name field MUST be present for this version of the IR.
setNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The name of the graph.
setNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
An optional identifier for this node in a graph.
setNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Optionally, a name for the tensor.
setNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
The name is optional but significant when provided.
setNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR.
setNode(int, OnnxMl.NodeProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
setNode(int, OnnxMl.NodeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
The nodes in the graph, sorted topologically.
setNu(double) - Method in class org.tribuo.common.libsvm.SVMParameters
Sets the value of nu for NU_SVM.
setNumFeatures(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Sets the number of features LIME should use in an explanation.
setNumSamples(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Sets the number of samples to use in LIME.
setNumThreads(int) - Method in class org.tribuo.common.xgboost.XGBoostModel
Sets the number of threads to use at prediction time.
setOpaqueType(OnnxMl.TypeProto.Opaque) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
setOpaqueType(OnnxMl.TypeProto.Opaque.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.Opaque opaque_type = 7;
setOpsetImport(int, OnnxMl.OperatorSetIdProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
setOpsetImport(int, OnnxMl.OperatorSetIdProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The OperatorSets this model relies on.
setOpType(String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The symbolic identifier of the Operator to execute.
setOpTypeBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
The symbolic identifier of the Operator to execute.
setOutput(int, OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
setOutput(int, OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
repeated .onnx.ValueInfoProto output = 12;
setOutput(int, String) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
namespace Value
setProbability() - Method in class org.tribuo.common.libsvm.SVMParameters
Makes the model that is built provide probability estimates.
setProducerName(String) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The name of the framework or tool used to generate this model.
setProducerNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The name of the framework or tool used to generate this model.
setProducerVersion(String) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the framework or tool used to generate this model.
setProducerVersionBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
The version of the framework or tool used to generate this model.
setQuantizationAnnotation(int, OnnxMl.TensorAnnotation) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
setQuantizationAnnotation(int, OnnxMl.TensorAnnotation.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors.
setQuantParameterTensorNames(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
setQuantParameterTensorNames(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
<key, value> pairs to annotate tensor specified by <tensor_name> above.
setRawData(ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
Serializations can either use one of the fields above, or use this raw bytes field.
setRefAttrName(String) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
setRefAttrNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
setRepeatedField(Descriptors.FieldDescriptor, int, Object) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
setS(ByteString) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
UTF-8 string
setSalt(String) - Method in class org.tribuo.hash.HashCodeHasher
 
setSalt(String) - Method in class org.tribuo.hash.HashedFeatureMap
The salt is not serialised with the Model.
setSalt(String) - Method in class org.tribuo.hash.Hasher
The salt is transient, it must be set **to the same value as it was trained with** after the Model is deserialized.
setSalt(String) - Method in class org.tribuo.hash.MessageDigestHasher
 
setSalt(String) - Method in class org.tribuo.hash.ModHashCodeHasher
 
setSegment(OnnxMl.TensorProto.Segment) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
setSegment(OnnxMl.TensorProto.Segment.Builder) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
optional .onnx.TensorProto.Segment segment = 3;
setSequenceType(OnnxMl.TypeProto.Sequence) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
setSequenceType(OnnxMl.TypeProto.Sequence.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a sequence.
setShape(OnnxMl.TensorShapeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
setShape(OnnxMl.TensorShapeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
setShape(OnnxMl.TensorShapeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
optional .onnx.TensorShapeProto shape = 2;
setShape(OnnxMl.TensorShapeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
optional .onnx.TensorShapeProto shape = 2;
setShuffle(boolean) - Method in class org.tribuo.classification.sgd.crf.CRFTrainer
Turn on or off shuffling of examples.
setShuffle(boolean) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
Turn on or off shuffling of examples.
setShuffle(boolean) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Turn on or off shuffling of examples.
setSparseInitializer(int, OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
setSparseInitializer(int, OnnxMl.SparseTensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Initializers (see above) stored in sparse format.
setSparseTensor(OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
setSparseTensor(OnnxMl.SparseTensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
sparse tensor value
setSparseTensors(int, OnnxMl.SparseTensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
setSparseTensors(int, OnnxMl.SparseTensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of sparse tensors
setSparseTensorType(OnnxMl.TypeProto.SparseTensor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
setSparseTensorType(OnnxMl.TypeProto.SparseTensor.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
.onnx.TypeProto.SparseTensor sparse_tensor_type = 8;
setStoreIndices(boolean) - Method in class org.tribuo.dataset.DatasetView
Set to true to store the indices in the provenance system.
setStringData(int, ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For strings.
setStrings(int, ByteString) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of UTF-8 strings
setT(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
setT(OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
tensor value
setTensorName(String) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
optional string tensor_name = 1;
setTensorNameBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
optional string tensor_name = 1;
setTensors(int, OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
setTensors(int, OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
list of tensors
setTensorType(OnnxMl.TypeProto.Tensor) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
setTensorType(OnnxMl.TypeProto.Tensor.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
The type of a tensor.
setTrainingInfo(int, OnnxMl.TrainingInfoProto) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
setTrainingInfo(int, OnnxMl.TrainingInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
Training-specific information.
setType(OnnxMl.AttributeProto.AttributeType) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
The type field MUST be present for this version of the IR.
setType(OnnxMl.TypeProto) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
setType(OnnxMl.TypeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
This field MUST be present in this version of the IR for inputs and outputs of the top-level graph.
setType(Token.TokenType) - Method in class org.tribuo.util.tokens.universal.Range
Sets the token type.
setUint64Data(int, long) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.AttributeProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.ModelProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.NodeProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor.Builder
 
setUnknownFields(UnknownFieldSet) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto.Builder
 
setUpdateBinding(int, OnnxMl.StringStringEntryProto) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
setUpdateBinding(int, OnnxMl.StringStringEntryProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Gradient-based training is usually an iterative procedure.
setupParameters(ImmutableOutputInfo<Event>) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
 
setupParameters(ImmutableOutputInfo<Label>) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
 
setupParameters(ImmutableOutputInfo<Label>) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
 
setupParameters(ImmutableOutputInfo<T>) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
Constructs the parameters.
setupParameters(ImmutableOutputInfo<T>) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
Constructs the svm_parameter.
setValue(String) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string value = 2;
setValueBytes(ByteString) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto.Builder
optional string value = 2;
setValueInfo(int, OnnxMl.ValueInfoProto) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
setValueInfo(int, OnnxMl.ValueInfoProto.Builder) - Method in class ai.onnx.proto.OnnxMl.GraphProto.Builder
Information for the values in the graph.
setValues(OnnxMl.TensorProto) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
setValues(OnnxMl.TensorProto.Builder) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto.Builder
The sequence of non-default values are encoded as a tensor of shape [NNZ].
setValueType(OnnxMl.TypeProto) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
setValueType(OnnxMl.TypeProto.Builder) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map.Builder
This field MUST be present for this version of the IR.
setVersion(long) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto.Builder
The version of the operator set being identified.
setWeight(float) - Method in class org.tribuo.Example
Sets the example's weight.
setWeight(float) - Method in class org.tribuo.sequence.SequenceExample
Sets the weight of this sequence.
setWeights(Map<T, Float>) - Method in class org.tribuo.MutableDataset
Sets the weights in each example according to their output.
SFS - Enum constant in enum class org.tribuo.regression.slm.TrainTest.SLMType
Creates a SLMTrainer which performs sequential forward selection of the features.
SFSN - Enum constant in enum class org.tribuo.regression.slm.TrainTest.SLMType
Creates a SLMTrainer which performs sequential forward selection on normalised features.
SGD - Class in org.tribuo.math.optimisers
An implementation of single learning rate SGD and optionally momentum.
SGD() - Constructor for class org.tribuo.math.optimisers.SGD
For olcut.
SGD_KERNEL - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
Creates a KernelSVMTrainer.
SGD_LINEAR - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
Creates a LinearSGDTrainer.
SGD.Momentum - Enum Class in org.tribuo.math.optimisers
Momentum types.
sgdEpochs - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
Number of SGD epochs.
sgdEpochs - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
Number of SGD epochs.
sgdLoggingInterval - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
Log the objective after n examples.
sgdLoggingInterval - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
Log the objective after n examples.
sgdMinibatchSize - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
Minibatch size.
sgdMinibatchSize - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
Minibatch size.
sgdObjective - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
Loss function.
sgdObjective - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
Loss function.
SGDObjective<T> - Interface in org.tribuo.common.sgd
An interface for a loss function that can produce the loss and gradient incurred by a single prediction.
SGDOptions() - Constructor for class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
sgdSeed - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
Sets the random seed for the LinearSGDTrainer.
sgdSeed - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
Sets the random seed for the LinearSGDTrainer.
sgdType() - Method in class org.tribuo.math.optimisers.SGD
Override to specify the kind of SGD.
SGDVector - Interface in org.tribuo.math.la
Interface for 1 dimensional Tensors.
sgoOptions - Variable in class org.tribuo.classification.sgd.crf.CRFOptions
Options for the gradient optimiser.
sgoOptions - Variable in class org.tribuo.classification.sgd.fm.FMClassificationOptions
 
sgoOptions - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
The gradient descent optimiser options.
sgoOptions - Variable in class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions
The gradient descent optimiser options.
sgoOptions - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
The gradient descent optimiser options.
SHA1 - Enum constant in enum class org.tribuo.hash.HashingOptions.ModelHashingType
Uses SHA-1.
SHA256 - Enum constant in enum class org.tribuo.hash.HashingOptions.ModelHashingType
Uses SHA-256.
shape - Variable in class org.tribuo.interop.oci.OCIUtil.OCIModelDeploymentConfig
The instance shape.
shape - Variable in class org.tribuo.interop.tensorflow.TensorFlowUtil.TensorTuple
The shape of the tensor.
SHAPE - Enum constant in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
Creates a ShapeTokenizer.
SHAPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
SHAPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
shapeCheck(Tensor, Tensor) - Static method in interface org.tribuo.math.la.Tensor
Checks that the two tensors have compatible shapes.
shapeSum(int[]) - Static method in interface org.tribuo.math.la.Tensor
The number of elements in this shape, i.e., the product of the shape array.
ShapeTokenizer - Class in org.tribuo.util.tokens.impl
This tokenizer is loosely based on the notion of word shape which is a common feature used in NLP.
ShapeTokenizer() - Constructor for class org.tribuo.util.tokens.impl.ShapeTokenizer
Constructs a ShapeTokenizer.
SHORT - Enum constant in enum class org.tribuo.datasource.IDXDataSource.IDXType
A 16-bit integer.
shouldMakeLeaf(double, float) - Method in class org.tribuo.common.tree.AbstractTrainingNode
Determines whether the node to be created should be a LeafNode.
showLabelStats(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Shows the output statistics.
showOutputStats(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
Shows the output statistics.
showProvenance(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
Shows the dataset provenance.
ShrinkingMatrix - Class in org.tribuo.math.optimisers.util
A subclass of DenseMatrix which shrinks the value every time a new value is added.
ShrinkingMatrix(DenseMatrix, double, boolean) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingMatrix
Constructs a shrinking matrix copy of the supplied dense matrix.
ShrinkingMatrix(DenseMatrix, double, double) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingMatrix
Constructs a shrinking matrix copy of the supplied dense matrix.
ShrinkingTensor - Interface in org.tribuo.math.optimisers.util
An interface which tags a Tensor with a convertToDense method.
ShrinkingVector - Class in org.tribuo.math.optimisers.util
A subclass of DenseVector which shrinks the value every time a new value is added.
ShrinkingVector(DenseVector, double, boolean) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingVector
Constructs a shrinking vector copy of the supplied dense matrix.
ShrinkingVector(DenseVector, double, double) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingVector
Constructs a shrinking vector copy of the supplied dense vector.
shuffle - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Shuffle the data each epoch (default: true).
shuffle - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
shuffle(boolean) - Method in class org.tribuo.Dataset
Shuffles the indices, or stops shuffling them.
shuffle(ArrayList<T>, SplittableRandom) - Static method in class org.tribuo.util.Util
Shuffles an ArrayList like Collections.shuffle(java.util.List<?>) but using a SplittableRandom.
shuffle(SGDVector[][], int[][], double[], SplittableRandom) - Static method in class org.tribuo.classification.sgd.Util
Shuffles a sequence of features, labels and weights, returning a tuple of the shuffled values.
shuffle(SparseVector[], int[], double[], SplittableRandom) - Static method in class org.tribuo.classification.sgd.Util
Shuffles the features, labels and weights returning a tuple of the shuffled inputs.
shuffleInPlace(SGDVector[][], int[][], double[], SplittableRandom) - Static method in class org.tribuo.classification.sgd.Util
In place shuffle used for sequence problems.
shuffleInPlace(SGDVector[], T[], double[], SplittableRandom) - Static method in class org.tribuo.common.sgd.AbstractSGDTrainer
Shuffles the features, outputs and weights in place.
shuffleInPlace(SparseVector[], int[], double[], int[], SplittableRandom) - Static method in class org.tribuo.classification.sgd.Util
In place shuffle of the features, labels, weights and indices.
shuffleInPlace(SparseVector[], int[], double[], SplittableRandom) - Static method in class org.tribuo.classification.sgd.Util
shuffleInPlace(SparseVector[], DenseVector[], double[], int[], SplittableRandom) - Static method in class org.tribuo.regression.sgd.Util
In place shuffle of the features, labels and weights.
shuffleInPlace(SparseVector[], DenseVector[], double[], SplittableRandom) - Static method in class org.tribuo.regression.sgd.Util
In place shuffle of the features, labels and weights.
sigmoid(double) - Static method in class org.tribuo.math.util.SigmoidNormalizer
A logistic sigmoid function.
Sigmoid - Class in org.tribuo.math.kernel
A sigmoid kernel, tanh(gamma*u.dot(v) + intercept).
Sigmoid(double, double) - Constructor for class org.tribuo.math.kernel.Sigmoid
A sigmoid kernel, tanh(gamma*u.dot(v) + intercept).
SIGMOID - Enum constant in enum class org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Uses a Sigmoid kernel.
SIGMOID - Enum constant in enum class org.tribuo.common.libsvm.KernelType
A sigmoid kernel of the form tanh(gamma*u'*v + coef0)
SIGMOID - Enum constant in enum class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions.LossEnum
Log loss, i.e., binary cross-entropy.
SIGMOID - Enum constant in enum class org.tribuo.multilabel.sgd.linear.LinearSGDOptions.LossEnum
Log loss, i.e., binary cross-entropy.
SIGMOID - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Sigmoid element-wise.
SigmoidNormalizer - Class in org.tribuo.math.util
Normalizes the input by applying a logistic sigmoid to each element.
SigmoidNormalizer() - Constructor for class org.tribuo.math.util.SigmoidNormalizer
 
SILENT - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
No logging.
similarity(SparseVector, SparseVector) - Method in interface org.tribuo.math.kernel.Kernel
Calculates the similarity between two SparseVectors.
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.Linear
 
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.Polynomial
 
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.RBF
 
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.Sigmoid
 
SIMPLE_DEFAULT_PATTERN - Static variable in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
The default split pattern, which is [\.,]?\s+.
SimpleDataSourceProvenance - Class in org.tribuo.provenance
This class stores a String describing the data source, along with a timestamp.
SimpleDataSourceProvenance(String, OffsetDateTime, OutputFactory<T>) - Constructor for class org.tribuo.provenance.SimpleDataSourceProvenance
This constructor initialises the provenance using the supplied description, time and output factory.
SimpleDataSourceProvenance(String, OutputFactory<T>) - Constructor for class org.tribuo.provenance.SimpleDataSourceProvenance
This constructor initialises the provenance using the current time in the system timezone.
SimpleDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.SimpleDataSourceProvenance
Used for provenance deserialization.
SimpleFieldExtractor<T> - Class in org.tribuo.data.columnar.extractors
Extracts a value from a single field to be placed in an Example's metadata field.
SimpleFieldExtractor() - Constructor for class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
For olcut.
SimpleFieldExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
Constructs a simple field extractor which reads from the supplied field name and writes out to a metadata field with the same name.
SimpleFieldExtractor(String, String) - Constructor for class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
Constructs a simple field extractor with the supplied field name and metadata field name.
SimpleStringDataSource<T extends Output<T>> - Class in org.tribuo.data.text.impl
A version of SimpleTextDataSource that accepts a List of Strings.
SimpleStringDataSource(List<String>, OutputFactory<T>, TextFeatureExtractor<T>) - Constructor for class org.tribuo.data.text.impl.SimpleStringDataSource
Constructs a simple string data source from the supplied lines.
SimpleStringDataSource.SimpleStringDataSourceProvenance - Class in org.tribuo.data.text.impl
Provenance for SimpleStringDataSource.
SimpleStringDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.text.impl.SimpleStringDataSource.SimpleStringDataSourceProvenance
Deserialization constructor.
SimpleTextDataSource<T extends Output<T>> - Class in org.tribuo.data.text.impl
A dataset for a simple data format for text classification experiments.
SimpleTextDataSource() - Constructor for class org.tribuo.data.text.impl.SimpleTextDataSource
for olcut
SimpleTextDataSource(File, OutputFactory<T>, TextFeatureExtractor<T>) - Constructor for class org.tribuo.data.text.impl.SimpleTextDataSource
Constructs a simple text data source by reading lines from the supplied file.
SimpleTextDataSource(Path, OutputFactory<T>, TextFeatureExtractor<T>) - Constructor for class org.tribuo.data.text.impl.SimpleTextDataSource
Constructs a simple text data source by reading lines from the supplied path.
SimpleTextDataSource(OutputFactory<T>, TextFeatureExtractor<T>) - Constructor for class org.tribuo.data.text.impl.SimpleTextDataSource
 
SimpleTextDataSource.SimpleTextDataSourceProvenance - Class in org.tribuo.data.text.impl
Provenance for SimpleTextDataSource.
SimpleTextDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.text.impl.SimpleTextDataSource.SimpleTextDataSourceProvenance
Deserialization constructor.
SimpleTransform - Class in org.tribuo.transform.transformations
This is used for stateless functions such as exp, log, addition or multiplication by a constant.
SimpleTransform.Operation - Enum Class in org.tribuo.transform.transformations
Operations understood by this Transformation.
SimpleTransform.SimpleTransformProvenance - Class in org.tribuo.transform.transformations
Provenance for SimpleTransform.
SimpleTransformProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
Deserialization constructor.
SINGLE_DIM_NAME - Static variable in class org.tribuo.regression.example.RegressionDataGenerator
Name of the single dimension.
size - Variable in class org.tribuo.common.tree.impl.IntArrayContainer
The number of elements in the array.
size - Variable in class org.tribuo.ImmutableFeatureMap
The number of features.
size - Variable in class org.tribuo.impl.ArrayExample
Number of valid features in this example.
size - Variable in class org.tribuo.impl.BinaryFeaturesExample
Number of valid features in this example.
size() - Method in class org.tribuo.anomaly.AnomalyInfo
The number of possible event types (i.e., 2).
size() - Method in class org.tribuo.classification.LabelInfo
The number of unique Labels this LabelInfo has seen.
size() - Method in class org.tribuo.clustering.ClusteringInfo
 
size() - Method in class org.tribuo.dataset.DatasetView
Gets the size of the data set.
size() - Method in class org.tribuo.Dataset
Gets the size of the data set.
size() - Method in class org.tribuo.datasource.IDXDataSource
The number of examples loaded.
size() - Method in class org.tribuo.datasource.LibSVMDataSource
The number of examples.
size() - Method in class org.tribuo.datasource.ListDataSource
Number of examples.
size() - Method in class org.tribuo.Example
Return how many features are in this example.
size() - Method in class org.tribuo.FeatureMap
Returns the number of features in the domain.
size() - Method in class org.tribuo.ImmutableFeatureMap
 
size() - Method in class org.tribuo.impl.ArrayExample
 
size() - Method in class org.tribuo.impl.BinaryFeaturesExample
 
size() - Method in class org.tribuo.impl.ListExample
 
size() - Method in class org.tribuo.math.la.DenseVector
 
size() - Method in interface org.tribuo.math.la.SGDVector
Returns the dimensionality of this vector.
size() - Method in class org.tribuo.math.la.SparseVector
 
size() - Method in class org.tribuo.multilabel.MultiLabelInfo
 
size() - Method in interface org.tribuo.OutputInfo
Returns the number of possible values this OutputInfo knows about.
size() - Method in class org.tribuo.regression.RegressionInfo
The number of dimensions this OutputInfo has seen.
size() - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
size() - Method in class org.tribuo.regression.Regressor
Returns the number of dimensions in this regressor.
size() - Method in class org.tribuo.sequence.SequenceDataset
Gets the size of the data set.
size() - Method in class org.tribuo.sequence.SequenceExample
Return how many examples are in this sequence.
size() - Method in class org.tribuo.transform.TransformerMap
Gets the size of the map.
size() - Method in class org.tribuo.util.infotheory.impl.RowList
 
SkeletalIndependentRegressionModel - Class in org.tribuo.regression.impl
A Model which wraps n independent regression models, where n is the size of the MultipleRegressor domain.
SkeletalIndependentRegressionModel(String, String[], ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>) - Constructor for class org.tribuo.regression.impl.SkeletalIndependentRegressionModel
models.size() must equal labelInfo.getDomain().size()
SkeletalIndependentRegressionSparseModel - Class in org.tribuo.regression.impl
A SparseModel which wraps n independent regression models, where n is the size of the MultipleRegressor domain.
SkeletalIndependentRegressionSparseModel(String, String[], ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>, Map<String, List<String>>) - Constructor for class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseModel
models.size() must equal labelInfo.getDomain().size()
SkeletalIndependentRegressionSparseTrainer<T> - Class in org.tribuo.regression.impl
Base class for training n independent sparse models, one per dimension.
SkeletalIndependentRegressionSparseTrainer() - Constructor for class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
for olcut.
SkeletalIndependentRegressionTrainer<T> - Class in org.tribuo.regression.impl
Trains n independent binary Models, each of which predicts a single Regressor.
SkeletalIndependentRegressionTrainer() - Constructor for class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
for olcut.
SkeletalTrainerProvenance - Class in org.tribuo.provenance
The skeleton of a TrainerProvenance that extracts the configured parameters.
SkeletalTrainerProvenance(SkeletalConfiguredObjectProvenance.ExtractedInfo) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance
 
SkeletalTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance
 
SkeletalTrainerProvenance(SequenceTrainer<T>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance
 
SkeletalTrainerProvenance(Trainer<T>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance
 
SkeletalVariableInfo - Class in org.tribuo
Contains information about a feature and can be stored in the feature map in a Dataset.
SkeletalVariableInfo(String) - Constructor for class org.tribuo.SkeletalVariableInfo
Constructs a variable info with the supplied name.
SkeletalVariableInfo(String, int) - Constructor for class org.tribuo.SkeletalVariableInfo
Constructs a variable info with the supplied name and initial count.
SLMOptions() - Constructor for class org.tribuo.regression.slm.TrainTest.SLMOptions
 
SLMTrainer - Class in org.tribuo.regression.slm
A trainer for a sparse linear regression model.
SLMTrainer() - Constructor for class org.tribuo.regression.slm.SLMTrainer
For OLCUT.
SLMTrainer(boolean) - Constructor for class org.tribuo.regression.slm.SLMTrainer
Constructs a trainer for a sparse linear model using sequential forward selection.
SLMTrainer(boolean, int) - Constructor for class org.tribuo.regression.slm.SLMTrainer
Constructs a trainer for a sparse linear model using sequential forward selection.
SOFTMAX - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Softmax.
sort() - Method in class org.tribuo.Example
Sorts the example by the string comparator.
sort() - Method in class org.tribuo.impl.ArrayExample
Sorts the feature list to maintain the lexicographic order invariant.
sort() - Method in class org.tribuo.impl.BinaryFeaturesExample
Sorts the feature list to maintain the lexicographic order invariant.
sort() - Method in class org.tribuo.impl.IndexedArrayExample
 
sort() - Method in class org.tribuo.impl.ListExample
Sorts the feature list to maintain the lexicographic order invariant.
sort() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Sort the list using InvertedFeature's natural ordering.
sortedDifference(int[], int[]) - Static method in class org.tribuo.util.Util
Expects sorted input arrays.
sourceProvenance - Variable in class org.tribuo.Dataset
The provenance of the data source, extracted on construction.
sourceProvenance - Variable in class org.tribuo.sequence.SequenceDataset
The provenance of the data source, extracted on construction.
SPARSE_INITIALIZER_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
SPARSE_TENSOR - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
SPARSE_TENSOR = 11;
SPARSE_TENSOR_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
SPARSE_TENSOR_TYPE - Enum constant in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
SPARSE_TENSOR_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto
 
SPARSE_TENSOR_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
SPARSE_TENSOR = 11;
SPARSE_TENSORS - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
SPARSE_TENSORS = 12;
SPARSE_TENSORS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
SPARSE_TENSORS_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
SPARSE_TENSORS = 12;
SparseLinearModel - Class in org.tribuo.regression.slm
The inference time version of a sparse linear regression model.
SparseModel<T extends Output<T>> - Class in org.tribuo
A model which uses a subset of the features it knows about to make predictions.
SparseModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, Map<String, List<String>>) - Constructor for class org.tribuo.SparseModel
Constructs a sparse model from the supplied arguments.
SparseTrainer<T extends Output<T>> - Interface in org.tribuo
Denotes this trainer emits a SparseModel.
sparseTrainTest() - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Makes a simple dataset for training and testing.
sparseTrainTest() - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
sparseTrainTest() - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
sparseTrainTest() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
sparseTrainTest(double) - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
sparseTrainTest(double) - Static method in class org.tribuo.classification.example.LabelledDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
sparseTrainTest(double) - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
sparseTrainTest(double) - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.
SparseVector - Class in org.tribuo.math.la
A sparse vector.
SparseVector(int, int[], double) - Constructor for class org.tribuo.math.la.SparseVector
Creates a sparse vector of the specified size, with the supplied value at each of the indices.
sparsify() - Method in class org.tribuo.math.la.DenseVector
Generates a SparseVector representation from this dense vector, removing all values with absolute value below VectorTuple.DELTA.
sparsify(double) - Method in class org.tribuo.math.la.DenseVector
Generates a SparseVector representation from this dense vector, removing all values with absolute value below the supplied tolerance.
split - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
split(int[], int[], IntArrayContainer, IntArrayContainer) - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Splits this tree feature into two.
split(CharSequence) - Method in interface org.tribuo.util.tokens.Tokenizer
Uses this tokenizer to split a string into it's component substrings.
split(IntArrayContainer, IntArrayContainer) - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
Relies upon allLeftIndices being sorted in ascending order.
split(Dataset<T>, boolean) - Method in class org.tribuo.evaluation.KFoldSplitter
Splits a dataset into k consecutive folds; for each fold, the remaining k-1 folds form the training set.
SPLIT_AFTER - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
The current character will cause the in-progress token to be completed after the current character is appended to the in-progress token.
SPLIT_AFTER_INFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after infix.
SPLIT_AFTER_NGRAM - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after a ngram.
SPLIT_AFTER_PREFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after a prefix.
SPLIT_AFTER_PUNCTUATION - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after punctuation.
SPLIT_AFTER_SUFFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after a suffix.
SPLIT_AFTER_UNKNOWN - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after an unknown value.
SPLIT_AFTER_WHITESPACE - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after whitespace.
SPLIT_AFTER_WORD - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split after a word.
SPLIT_AT - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split at.
SPLIT_AT - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
The current character will cause the in-progress token to be completed.
SPLIT_BEFORE - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before.
SPLIT_BEFORE - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
The current character will cause the in-progress token to be completed the current character will be included in the next token.
SPLIT_BEFORE_AND_AFTER - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
The current character should cause the in-progress token to be completed.
SPLIT_BEFORE_AND_AFTER_INFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after infix.
SPLIT_BEFORE_AND_AFTER_NGRAM - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after a ngram.
SPLIT_BEFORE_AND_AFTER_PREFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after prefix.
SPLIT_BEFORE_AND_AFTER_PUNCTUATION - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after punctuation.
SPLIT_BEFORE_AND_AFTER_SUFFIX - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after suffix.
SPLIT_BEFORE_AND_AFTER_UNKNOWN - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after unknown.
SPLIT_BEFORE_AND_AFTER_WHITESPACE - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after whitespace.
SPLIT_BEFORE_AND_AFTER_WORD - Enum constant in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Split before and after a word.
SPLIT_CHARACTERS - Enum constant in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
SPLIT_PATTERN - Enum constant in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
splitChar - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Character to split the CSV response on to generate multiple regression dimensions.
SplitCharactersSplitterFunction(char[], char[]) - Constructor for class org.tribuo.util.tokens.impl.SplitCharactersTokenizer.SplitCharactersSplitterFunction
Constructs a splitting function using the supplied split characters.
SplitCharactersTokenizer - Class in org.tribuo.util.tokens.impl
This implementation of Tokenizer is instantiated with an array of characters that are considered split characters.
SplitCharactersTokenizer() - Constructor for class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
SplitCharactersTokenizer(char[], char[]) - Constructor for class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
 
SplitCharactersTokenizer.SplitCharactersSplitterFunction - Class in org.tribuo.util.tokens.impl
Splits tokens at the supplied characters.
splitCharactersTokenizerOptions - Variable in class org.tribuo.util.tokens.options.CoreTokenizerOptions
Options for the split characters tokenizer.
SplitCharactersTokenizerOptions - Class in org.tribuo.util.tokens.options
CLI options for a SplitCharactersTokenizer.
SplitCharactersTokenizerOptions() - Constructor for class org.tribuo.util.tokens.options.SplitCharactersTokenizerOptions
 
splitChars - Variable in class org.tribuo.util.tokens.options.SplitCharactersTokenizerOptions
The characters to split on.
SplitDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
Deserialization constructor.
splitFraction - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
Split fraction.
splitFunction - Variable in class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
 
SplitFunctionTokenizer - Class in org.tribuo.util.tokens.impl
This class supports character-by-character (that is, codepoint-by-codepoint) iteration over input text to create tokens.
SplitFunctionTokenizer() - Constructor for class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
Constructs a tokenizer, used by OLCUT.
SplitFunctionTokenizer(SplitFunctionTokenizer.SplitFunction) - Constructor for class org.tribuo.util.tokens.impl.SplitFunctionTokenizer
Creates a new tokenizer using the supplied split function.
SplitFunctionTokenizer.SplitFunction - Interface in org.tribuo.util.tokens.impl
An interface for checking if the text should be split at the supplied codepoint.
SplitFunctionTokenizer.SplitResult - Enum Class in org.tribuo.util.tokens.impl
SplitFunctionTokenizer.SplitType - Enum Class in org.tribuo.util.tokens.impl
Defines different ways that a tokenizer can split the input text at a given character.
splitID - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
SplitNode<T extends Output<T>> - Class in org.tribuo.common.tree
An immutable Node with a split and two child nodes.
SplitNode(double, int, double, Node<T>, Node<T>) - Constructor for class org.tribuo.common.tree.SplitNode
Constructs a split node with the specified split value, feature id, impurity and child nodes.
SplitPatternTokenizer - Class in org.tribuo.util.tokens.impl
This implementation of Tokenizer is instantiated with a regular expression pattern which determines how to split a string into tokens.
SplitPatternTokenizer() - Constructor for class org.tribuo.util.tokens.impl.SplitPatternTokenizer
Initializes a case insensitive tokenizer with the pattern [\.,]?\s+
SplitPatternTokenizer(String) - Constructor for class org.tribuo.util.tokens.impl.SplitPatternTokenizer
Constructs a splitting tokenizer using the supplied regex.
splitPatternTokenizerOptions - Variable in class org.tribuo.util.tokens.options.CoreTokenizerOptions
Options for the split pattern tokenizer.
SplitPatternTokenizerOptions - Class in org.tribuo.util.tokens.options
CLI options for a SplitPatternTokenizer.
SplitPatternTokenizerOptions() - Constructor for class org.tribuo.util.tokens.options.SplitPatternTokenizerOptions
 
SplitTextData - Class in org.tribuo.data.text
Splits data in our standard text format into training and testing portions.
SplitTextData() - Constructor for class org.tribuo.data.text.SplitTextData
 
SplitTextData.TrainTestSplitOptions - Class in org.tribuo.data.text
Command line options.
splitType - Variable in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
The split type.
splitValue - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
splitValue() - Method in class org.tribuo.common.tree.SplitNode
The threshold value.
splitXDigitsChars - Variable in class org.tribuo.util.tokens.options.SplitCharactersTokenizerOptions
Characters to split on unless they appear between digits
SQLDataSource<T extends Output<T>> - Class in org.tribuo.data.sql
A DataSource for loading columnar data from a database and applying FieldProcessors to it.
SQLDataSource(String, SQLDBConfig, OutputFactory<T>, RowProcessor<T>, boolean) - Constructor for class org.tribuo.data.sql.SQLDataSource
Constructs a SQLDataSource.
SQLDataSource.SQLDataSourceProvenance - Class in org.tribuo.data.sql
Provenance for SQLDataSource.
SQLDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.sql.SQLDataSource.SQLDataSourceProvenance
Deserialization constructor.
SQLDBConfig - Class in org.tribuo.data.sql
N.B.
SQLDBConfig(String, String, String, String, String, Map<String, String>) - Constructor for class org.tribuo.data.sql.SQLDBConfig
Constructs a SQL database configuration.
SQLDBConfig(String, String, String, Map<String, String>) - Constructor for class org.tribuo.data.sql.SQLDBConfig
Constructs a SQL database configuration.
SQLDBConfig(String, Map<String, String>) - Constructor for class org.tribuo.data.sql.SQLDBConfig
Constructs a SQL database configuration.
SQLToCSV - Class in org.tribuo.data.sql
Read an SQL query in on the standard input, write a CSV file containing the results to the standard output.
SQLToCSV() - Constructor for class org.tribuo.data.sql.SQLToCSV
 
SQLToCSV.SQLToCSVOptions - Class in org.tribuo.data.sql
Command line options.
SQLToCSVOptions() - Constructor for class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
 
SQRTSGD - Enum constant in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
SGD with a square root decay learning rate.
SQUARED - Enum constant in enum class org.tribuo.regression.sgd.fm.TrainTest.LossEnum
SQUARED - Enum constant in enum class org.tribuo.regression.sgd.TrainTest.LossEnum
SquaredLoss - Class in org.tribuo.regression.sgd.objectives
Squared loss, i.e., l2.
SquaredLoss() - Constructor for class org.tribuo.regression.sgd.objectives.SquaredLoss
Constructs a SquaredLoss.
STANDARD - Enum constant in enum class org.tribuo.math.optimisers.SGD.Momentum
Standard momentum.
standardise - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Standardise the output regressors before model fitting.
standardize - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
Standardize the regression outputs internally to the SVM
standardize(double[]) - Method in class org.tribuo.util.MeanVarianceAccumulator
Standardizes the input using the computed mean and variance in this accumulator.
standardize(double[], double, double) - Static method in class org.tribuo.util.Util
Standardizes the input so it has zero mean and unit variance, i.e., subtracts the mean and divides by the variance.
standardizeInPlace(double[]) - Method in class org.tribuo.util.MeanVarianceAccumulator
Standardizes the input using the computed mean and variance in this accumulator.
standardizeInPlace(double[], double, double) - Static method in class org.tribuo.util.Util
Standardizes the input so it has zero mean and unit variance, i.e., subtracts the mean and divides by the variance.
start - Variable in class org.tribuo.util.tokens.Token
The start index.
start - Variable in class org.tribuo.util.tokens.universal.Range
The start index.
startShell() - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Start the command shell
startShell() - Method in class org.tribuo.data.DatasetExplorer
Start the command shell
startShell() - Method in class org.tribuo.ModelExplorer
Start the command shell
startShell() - Method in class org.tribuo.sequence.SequenceModelExplorer
Start the command shell
STD_DEVS - Enum constant in enum class org.tribuo.transform.transformations.BinningTransformation.BinningType
Creates bins based on the mean and then +/- multiples of standard deviations.
stdDevs(int) - Static method in class org.tribuo.transform.transformations.BinningTransformation
Returns a BinningTransformation which generates bins based on the observed standard deviation of the training data.
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.AdaDelta
 
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.AdaGrad
 
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.AdaGradRDA
 
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.Adam
 
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.ParameterAveraging
This passes the gradient update to the inner optimiser, then updates the average weight values.
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.Pegasos
 
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.RMSProp
 
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.SGD
 
step(Tensor[], double) - Method in interface org.tribuo.math.StochasticGradientOptimiser
Take a Tensor array of gradients and transform them according to the current weight and learning rates.
StochasticGradientOptimiser - Interface in org.tribuo.math
Interface for gradient based optimisation methods.
storeHash - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
Stores a hash of the model provenance in the stripped model.
storeIndicesInProvenance() - Method in class org.tribuo.dataset.DatasetView
Are the indices stored in the provenance system.
STRATIFIED - Enum constant in enum class org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Samples the label proprotional to the training label frequencies.
STREAMS - Enum constant in enum class org.tribuo.common.nearest.KNNModel.Backend
Uses the streams API for parallelism when scoring a batch of predictions.
STRING - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
STRING = 3;
STRING - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
string
STRING_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
STRING_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
STRING = 3;
STRING_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
string
STRINGS - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
STRINGS = 8;
STRINGS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
STRINGS_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
STRINGS = 8;
StripProvenance - Class in org.tribuo.json
A main class for stripping out and storing provenance from a model.
StripProvenance.ProvenanceTypes - Enum Class in org.tribuo.json
Types of provenance that can be removed.
StripProvenance.StripProvenanceOptions - Class in org.tribuo.json
Command line options.
StripProvenanceOptions() - Constructor for class org.tribuo.json.StripProvenance.StripProvenanceOptions
 
sub - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Subtracts the specified constant.
sub(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that subtracts the operand from each value.
SUB - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Element-wise subtraction with broadcasting.
subList(int, int) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
subsample - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Subsample size for each tree (default 1, range (0,1]).
subsample - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Subsample size for each tree (default 1, range (0,1]).
subsampleFeatures - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
Subsample features for each tree (default 1, range (0,1]).
subsampleFeatures - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
Subsample features for each tree (default 1, range (0,1]).
subSequence(int, int) - Method in class org.tribuo.util.tokens.universal.Range
 
Subsequence(int, int) - Constructor for class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
Constructs a subsequence for the fixed range, exclusive of the end.
subtract(SGDVector) - Method in class org.tribuo.math.la.DenseVector
Subtracts other from this vector, producing a new DenseVector.
subtract(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Subtracts other from this vector, producing a new SGDVector.
subtract(SGDVector) - Method in class org.tribuo.math.la.SparseVector
Subtracts other from this vector, producing a new SGDVector.
SUFFIX - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
Some tokenizers produce "sub-word" tokens.
sum() - Method in class org.tribuo.math.la.DenseVector
 
sum() - Method in interface org.tribuo.math.la.SGDVector
Calculates the sum of this vector.
sum() - Method in class org.tribuo.math.la.SparseVector
 
sum() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
sum(double[]) - Static method in class org.tribuo.util.Util
Computes the sum of the input vector.
sum(double[], int) - Static method in class org.tribuo.util.Util
Computes the sum of the input vector up to length elements.
sum(float[]) - Static method in class org.tribuo.util.Util
Computes the sum of the input vector.
sum(float[], int) - Static method in class org.tribuo.util.Util
Computes the sum of the input vector up to length elements.
sum(int[], float[]) - Static method in class org.tribuo.util.Util
Computes the sum of the specified indices in the input array.
sum(int[], int, float[]) - Static method in class org.tribuo.util.Util
Computes the sum of the specified indices in the input array.
sum(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
Sums this vector, applying the supplied function to each element first.
SUM - Enum constant in enum class org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Add together all the feature values.
SUM - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Element-wise summation across the supplied inputs with broadcasting.
SumAggregator - Class in org.tribuo.data.text.impl
A feature aggregator that aggregates occurrence counts across a number of feature lists.
SumAggregator() - Constructor for class org.tribuo.data.text.impl.SumAggregator
 
sumLogProbs(double[]) - Static method in class org.tribuo.classification.sgd.crf.ChainHelper
Sums the log probabilities.
sumLogProbs(DenseVector) - Static method in class org.tribuo.classification.sgd.crf.ChainHelper
Sums the log probabilities.
summarize(List<? extends EvaluationMetric<T, C>>, Model<T>, List<Prediction<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize model performance on dataset across several metrics.
summarize(List<? extends EvaluationMetric<T, C>>, Model<T>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize model performance on dataset across several metrics.
summarize(List<R>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize all fields of a list of evaluations.
summarize(List<R>, ToDoubleFunction<R>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize a single field of an evaluation across several evaluations.
summarize(Evaluator<T, R>, List<? extends Model<T>>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize performance using the supplied evaluator across several models on one dataset.
summarize(Evaluator<T, R>, Model<T>, List<? extends Dataset<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize performance according to evaluator for a single model across several datasets.
summarize(EvaluationMetric<T, C>, List<? extends Model<T>>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize performance w.r.t.
summarize(EvaluationMetric<T, C>, Model<T>, List<? extends Dataset<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize a model's performance w.r.t.
sumOverOutputs(ImmutableOutputInfo<T>, ToDoubleFunction<T>) - Static method in interface org.tribuo.classification.evaluation.ConfusionMatrix
Sums the supplied getter over the domain.
sumSquares - Variable in class org.tribuo.RealInfo
The sum of the squared feature values (used to compute the variance).
sumSquaresMap - Variable in class org.tribuo.regression.RegressionInfo
 
support() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of examples this confusion matrix has seen.
support() - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
support() - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
support(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
support(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
support(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of examples with this true label this confusion matrix has seen.
SVM_CLASSIFIER - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
SVM Classifier.
SVM_REGRESSOR - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
SVM Regressor.
SVMAnomalyType - Class in org.tribuo.anomaly.libsvm
The carrier type for LibSVM anomaly detection modes.
SVMAnomalyType(SVMAnomalyType.SVMMode) - Constructor for class org.tribuo.anomaly.libsvm.SVMAnomalyType
Constructs an SVM anomaly type wrapping the SVM algorithm choice.
SVMAnomalyType.SVMMode - Enum Class in org.tribuo.anomaly.libsvm
Valid SVM modes for anomaly detection.
SVMClassificationType - Class in org.tribuo.classification.libsvm
The carrier type for LibSVM classification modes.
SVMClassificationType(SVMClassificationType.SVMMode) - Constructor for class org.tribuo.classification.libsvm.SVMClassificationType
Constructs an SVMClassificationType using the supplied SVM algorithm.
SVMClassificationType.SVMMode - Enum Class in org.tribuo.classification.libsvm
The classification model types.
svmCoefficient - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
Intercept in kernel function.
svmDegree - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
Degree in polynomial kernel.
svmGamma - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
Gamma value in kernel function.
svmKernel - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
Type of SVM kernel.
SVMParameters<T extends Output<T>> - Class in org.tribuo.common.libsvm
A container for SVM parameters and the kernel.
SVMParameters(SVMType<T>, KernelType) - Constructor for class org.tribuo.common.libsvm.SVMParameters
Constructs the default SVMParameters using the specified SVMType and KernelType.
svmParamsToString(svm_parameter) - Static method in class org.tribuo.common.libsvm.SVMParameters
A sensible toString for svm_parameter.
SVMRegressionType - Class in org.tribuo.regression.libsvm
The carrier type for LibSVM regression modes.
SVMRegressionType(SVMRegressionType.SVMMode) - Constructor for class org.tribuo.regression.libsvm.SVMRegressionType
Constructs an SVMRegressionType using the specified SVM algorithm.
SVMRegressionType.SVMMode - Enum Class in org.tribuo.regression.libsvm
Type of regression SVM.
svmType - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
Type of SVM.
svmType - Variable in class org.tribuo.common.libsvm.LibSVMTrainer
The type of SVM algorithm.
svmType - Variable in class org.tribuo.common.libsvm.SVMParameters
 
svmType - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
Type of SVM.
SVMType<T extends Output<T>> - Interface in org.tribuo.common.libsvm
A carrier type for the SVM type.
SYSTEM - Enum constant in enum class org.tribuo.json.StripProvenance.ProvenanceTypes
Selects any system information provenance.

T

T_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
TAB - Enum constant in enum class org.tribuo.data.DataOptions.Delimiter
Tab separator.
TabularExplainer<T extends Output<T>> - Interface in org.tribuo.classification.explanations
An explainer for tabular data.
TAG_VERSION - Static variable in class org.tribuo.Tribuo
Any tag on the version number, e.g., SNAPSHOT, ALPHA, etc.
Tensor - Interface in org.tribuo.math.la
An interface for Tensors, currently Vectors and Matrices.
TENSOR - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
TENSOR = 4;
TENSOR_NAME_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
TENSOR_TYPE - Enum constant in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
TENSOR_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto
 
TENSOR_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
TENSOR = 4;
TensorFlowCheckpointModel<T extends Output<T>> - Class in org.tribuo.interop.tensorflow
This model encapsulates a simple model with an input feed dict, and produces a single output tensor.
TensorFlowFrozenExternalModel<T extends Output<T>> - Class in org.tribuo.interop.tensorflow
A Tribuo wrapper around a TensorFlow frozen model.
TensorFlowModel<T extends Output<T>> - Class in org.tribuo.interop.tensorflow
Base class for a TensorFlow model that operates on Examples.
TensorFlowModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, GraphDef, int, String, FeatureConverter, OutputConverter<T>) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowModel
Builds a TFModel.
TensorFlowNativeModel<T extends Output<T>> - Class in org.tribuo.interop.tensorflow
This model encapsulates a TensorFlow model running in graph mode with a single tensor output.
TensorflowOptions() - Constructor for class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
TensorFlowSavedModelExternalModel<T extends Output<T>> - Class in org.tribuo.interop.tensorflow
A Tribuo wrapper around a TensorFlow saved model bundle.
TensorFlowSequenceModel<T extends Output<T>> - Class in org.tribuo.interop.tensorflow.sequence
A TensorFlow model which implements SequenceModel, suitable for use in sequential prediction tasks.
TensorFlowSequenceTrainer<T extends Output<T>> - Class in org.tribuo.interop.tensorflow.sequence
A trainer for SequenceModels which use an underlying TensorFlow graph.
TensorFlowSequenceTrainer(Path, SequenceFeatureConverter, SequenceOutputConverter<T>, int, int, int, long, String, String, String) - Constructor for class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
Constructs a TensorFlowSequenceTrainer using the specified parameters.
TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance - Class in org.tribuo.interop.tensorflow.sequence
TensorFlowSequenceTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance
Deserialization constructor.
TensorFlowTrainer<T extends Output<T>> - Class in org.tribuo.interop.tensorflow
Trainer for TensorFlow.
TensorFlowTrainer(Path, String, GradientOptimiser, Map<String, Float>, FeatureConverter, OutputConverter<T>, int, int, int, int) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer
Constructs a Trainer for a TensorFlow graph.
TensorFlowTrainer(Path, String, GradientOptimiser, Map<String, Float>, FeatureConverter, OutputConverter<T>, int, int, int, int, Path) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer
Constructs a Trainer for a TensorFlow graph.
TensorFlowTrainer(Graph, String, GradientOptimiser, Map<String, Float>, FeatureConverter, OutputConverter<T>, int, int, int, int) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer
Constructs a Trainer for a TensorFlow graph.
TensorFlowTrainer(Graph, String, GradientOptimiser, Map<String, Float>, FeatureConverter, OutputConverter<T>, int, int, int, int, Path) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer
Constructs a Trainer for a TensorFlow graph.
TensorFlowTrainer(GraphDef, String, GradientOptimiser, Map<String, Float>, FeatureConverter, OutputConverter<T>, int, int, int, int) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer
Constructs a Trainer for a TensorFlow graph.
TensorFlowTrainer(GraphDef, String, GradientOptimiser, Map<String, Float>, FeatureConverter, OutputConverter<T>, int, int, int, int, Path) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer
Constructs a Trainer for a TensorFlow graph.
TensorFlowTrainer.TensorFlowTrainerProvenance - Class in org.tribuo.interop.tensorflow
Provenance for TensorFlowTrainer.
TensorFlowTrainer.TFModelFormat - Enum Class in org.tribuo.interop.tensorflow
The model format to emit.
TensorFlowTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
Deserialization constructor.
TensorFlowUtil - Class in org.tribuo.interop.tensorflow
Helper functions for working with TensorFlow.
TensorFlowUtil.TensorTuple - Class in org.tribuo.interop.tensorflow
A serializable tuple containing the tensor class name, the shape and the data.
TensorMap - Class in org.tribuo.interop.tensorflow
A map of names and tensors to feed into a session.
TensorMap(String, Tensor) - Constructor for class org.tribuo.interop.tensorflow.TensorMap
Creates a TensorMap containing the supplied mapping.
TensorMap(Map<String, Tensor>) - Constructor for class org.tribuo.interop.tensorflow.TensorMap
Creates a new TensorMap wrapping the supplied map.
TENSORS - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
TENSORS = 9;
TENSORS_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
TENSORS_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
TENSORS = 9;
TensorTuple(String, long[], byte[]) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowUtil.TensorTuple
Makes a TensorTuple.
termCounting - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Use term counts instead of boolean when using the standard text format.
termCounting - Variable in class org.tribuo.data.DataOptions
Use term counts instead of boolean when using the standard text format.
terminationCriterion - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
terminationCriterion - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
Tolerance of the optimization termination criterion.
test - Variable in class org.tribuo.evaluation.KFoldSplitter.TrainTestFold
The testing fold.
Test - Class in org.tribuo.classification.experiments
Test a classifier for a standard dataset.
Test() - Constructor for class org.tribuo.classification.experiments.Test
 
Test.ConfigurableTestOptions - Class in org.tribuo.classification.experiments
Command line options.
testBatchSize - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Test time minibatch size.
testDataset - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
Path to a serialised SequenceDataset used for testing.
testDataset - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Path to a serialised SequenceDataset used for testing.
testingPath - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Path to the testing file.
testingPath - Variable in class org.tribuo.data.DataOptions
Path to the testing file.
testingPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Path to the libsvm format testing file.
testSource - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
Load the testing DataSource from the config file.
text - Variable in class org.tribuo.util.tokens.Token
The token text.
TEXT - Enum constant in enum class org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Text features.
TEXT - Enum constant in enum class org.tribuo.data.DataOptions.InputFormat
Text data in Tribuo's standard format (i.e., each line is "output ## text data").
TextDataSource<T extends Output<T>> - Class in org.tribuo.data.text
A base class for textual data sets.
TextDataSource() - Constructor for class org.tribuo.data.text.TextDataSource
for olcut
TextDataSource(File, OutputFactory<T>, TextFeatureExtractor<T>, DocumentPreprocessor...) - Constructor for class org.tribuo.data.text.TextDataSource
Creates a text data set by reading it from a file.
TextDataSource(Path, OutputFactory<T>, TextFeatureExtractor<T>, DocumentPreprocessor...) - Constructor for class org.tribuo.data.text.TextDataSource
Creates a text data set by reading it from a path.
TextExplainer<T extends Output<T>> - Interface in org.tribuo.classification.explanations
An explainer for text data.
TextFeatureExtractor<T extends Output<T>> - Interface in org.tribuo.data.text
An interface for things that take text and turn them into examples that we can use to train or evaluate a classifier.
TextFeatureExtractorImpl<T extends Output<T>> - Class in org.tribuo.data.text.impl
An implementation of TextFeatureExtractor that takes a TextPipeline and generates ArrayExample.
TextFeatureExtractorImpl(TextPipeline) - Constructor for class org.tribuo.data.text.impl.TextFeatureExtractorImpl
Constructs a text feature extractor wrapping the supplied text pipeline.
TextFieldProcessor - Class in org.tribuo.data.columnar.processors.field
A FieldProcessor which takes a text field and runs a TextPipeline on it to generate features.
TextFieldProcessor(String, TextPipeline) - Constructor for class org.tribuo.data.columnar.processors.field.TextFieldProcessor
Constructs a field processor which uses the supplied text pipeline to process the field value.
TextPipeline - Interface in org.tribuo.data.text
A pipeline that takes a String and returns a List of Features.
TextProcessingException - Exception in org.tribuo.data.text
An exception thrown by the text processing system.
TextProcessingException(String) - Constructor for exception org.tribuo.data.text.TextProcessingException
Creates a TextProcessingException with the specified message.
TextProcessingException(String, Throwable) - Constructor for exception org.tribuo.data.text.TextProcessingException
Creates a TextProcessingException wrapping the supplied throwable with the specified message.
TextProcessingException(Throwable) - Constructor for exception org.tribuo.data.text.TextProcessingException
Creates a TextProcessingException wrapping the supplied throwable.
TextProcessor - Interface in org.tribuo.data.text
A TextProcessor takes some text and optionally a feature tag and generates a list of Features from that text.
THIRD - Enum constant in enum class org.tribuo.util.infotheory.WeightedInformationTheory.VariableSelector
The third variable is weighted.
thirdDimensionName - Static variable in class org.tribuo.regression.example.RegressionDataGenerator
Name of the third output dimension.
THREADPOOL - Enum constant in enum class org.tribuo.common.nearest.KNNModel.Backend
Uses a thread pool at the outer level (i.e., one thread per prediction).
threeDimDenseTrainTest(double, boolean) - Static method in class org.tribuo.regression.example.RegressionDataGenerator
Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}.
threshold - Enum constant in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Min and max thresholds applied to the input.
threshold() - Method in interface org.tribuo.multilabel.sgd.MultiLabelObjective
The default prediction threshold for creating the output.
threshold() - Method in class org.tribuo.multilabel.sgd.objectives.BinaryCrossEntropy
 
threshold() - Method in class org.tribuo.multilabel.sgd.objectives.Hinge
 
threshold(double, double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that sets values below min to min, and values above max to max.
THRESHOLD - Static variable in class org.tribuo.CategoricalInfo
The default threshold for converting a categorical info into a RealInfo.
THRESHOLD - Static variable in class org.tribuo.interop.onnx.DenseTransformer
Feature size beyond which a warning is generated (as ONNX requires dense features and large feature spaces are memory hungry).
THRESHOLD - Static variable in class org.tribuo.interop.tensorflow.DenseFeatureConverter
Feature size beyond which a warning is generated (as TensorFlow requires dense features and large feature spaces are memory hungry).
THRESHOLD - Static variable in class org.tribuo.interop.tensorflow.MultiLabelConverter
The threshold to determine if a label has been predicted.
thresholds - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
The threshold values.
thresholds - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.ROC
The threshold values.
time - Variable in class org.tribuo.provenance.ModelProvenance
 
TIME_SERIES - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Time series forecasting, no Tribuo mapping.
TimestampedTrainerProvenance - Class in org.tribuo.provenance.impl
A TrainerProvenance with a timestamp, used when there was no trainer involved in model construction (e.g., creating an EnsembleModel from existing models).
TimestampedTrainerProvenance() - Constructor for class org.tribuo.provenance.impl.TimestampedTrainerProvenance
Creates a TimestampedTrainerProvenance, tracking the creation time and Tribuo version.
TimestampedTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.TimestampedTrainerProvenance
Used for deserializing provenances from the marshalled form.
tn() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the total number of true negatives.
tn() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of true negatives.
tn() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the micro averaged true negative count.
tn() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
tn(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
tn(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
The true negative count for this label.
tn(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Returns the number of true negatives, possibly averaged depending on the metric target.
tn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
tn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
tn(T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the number of true negatives for that label, i.e., the number of times it wasn't predicted, and was not the true label.
tn(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of true negatives for the supplied label.
TN - Enum constant in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
The number of true negatives.
TN - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The number of true negatives.
TN - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The number of true negatives.
toArray() - Method in class org.tribuo.math.la.DenseVector
Generates a copy of the values in this DenseVector.
toArray() - Method in interface org.tribuo.math.la.SGDVector
Returns an array containing all the values in the vector (including any implicit zeros).
toArray() - Method in class org.tribuo.math.la.SparseVector
 
toArray() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
toArray() - Method in class org.tribuo.util.infotheory.impl.RowList
 
toArray(U[]) - Method in class org.tribuo.util.infotheory.impl.RowList
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
toBuilder() - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 
toDenseArray() - Method in class org.tribuo.math.la.SparseVector
Deprecated.
toDoubleArray(float[]) - Static method in class org.tribuo.util.Util
Convert an array of floats to an array of doubles.
toFloatArray(double[]) - Static method in class org.tribuo.util.Util
Convert an array of doubles to an array of floats.
toFormattedString(LabelEvaluation) - Static method in interface org.tribuo.classification.evaluation.LabelEvaluation
This method produces a nicely formatted String output, with appropriate tabs and newlines, suitable for display on a terminal.
toHTML() - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
Emits a HTML table representation of the Confusion Matrix.
toHTML() - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
Returns a HTML formatted String representing this evaluation.
toHTML() - Method in class org.tribuo.Feature
Returns the feature name formatted as a table cell.
toHTML(Pair<String, Double>) - Static method in class org.tribuo.util.HTMLOutput
Formats a pair as a HTML table entry.
toHTML(LabelEvaluation) - Static method in interface org.tribuo.classification.evaluation.LabelEvaluation
This method produces a HTML formatted String output, with appropriate tabs and newlines, suitable for integration into a webpage.
Token - Class in org.tribuo.util.tokens
A single token extracted from a String.
Token(String, int, int) - Constructor for class org.tribuo.util.tokens.Token
Constructs a token.
Token(String, int, int, Token.TokenType) - Constructor for class org.tribuo.util.tokens.Token
Constructs a token.
TOKEN_METADATA - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Metadata key for the token value stored in a Tribuo Example.
TOKEN_OUTPUT - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Output name for the token level outputs.
TOKEN_TYPE_IDS - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Input name for the token type ids.
TOKEN_TYPE_VALUE - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Token type value for the first sentence.
Token.TokenType - Enum Class in org.tribuo.util.tokens
Tokenizers may product multiple kinds of tokens, depending on the application to which they're being put.
TokenizationException - Exception in org.tribuo.util.tokens
Wraps exceptions thrown by tokenizers.
TokenizationException(String) - Constructor for exception org.tribuo.util.tokens.TokenizationException
Creates a TokenizationException with the specified message.
TokenizationException(String, Throwable) - Constructor for exception org.tribuo.util.tokens.TokenizationException
Creates a TokenizationException wrapping the supplied throwable with the specified message.
TokenizationException(Throwable) - Constructor for exception org.tribuo.util.tokens.TokenizationException
Creates a TokenizationException wrapping the supplied throwable.
tokenize(CharSequence) - Method in interface org.tribuo.util.tokens.Tokenizer
Uses this tokenizer to tokenize a string and return the list of tokens that were generated.
Tokenizer - Interface in org.tribuo.util.tokens
An interface for things that tokenize text: breaking it into words according to some set of rules.
TokenizerOptions - Interface in org.tribuo.util.tokens.options
CLI Options for creating a tokenizer.
TokenPipeline - Class in org.tribuo.data.text.impl
A pipeline for generating ngram features.
TokenPipeline(Tokenizer, int, boolean) - Constructor for class org.tribuo.data.text.impl.TokenPipeline
Creates a new token pipeline.
TokenPipeline(Tokenizer, int, boolean, int) - Constructor for class org.tribuo.data.text.impl.TokenPipeline
Creates a new token pipeline.
tokenType - Variable in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
The token type.
tolerance - Static variable in interface org.tribuo.math.optimisers.util.ShrinkingTensor
The tolerance below which the scale factor is applied to the stored values and reset to 1.0.
TOLERANCE - Static variable in class org.tribuo.regression.Regressor
The tolerance value for determining if two regressed values are equal.
toMaxLabels(List<Prediction<T>>) - Static method in class org.tribuo.sequence.SequenceModel
Extracts a list of the predicted outputs from the list of prediction objects.
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
Shows the top features of the loaded model.
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.ModelExplorer
Displays the top n features.
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.sequence.SequenceModelExplorer
Shows the top n features in this model.
TOPIC_MODELLING - Enum constant in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Topic modelling, no Tribuo mapping.
toPrimitiveDouble(List<Double>) - Static method in class org.tribuo.util.Util
Converts a boxed list of doubles into an array of primitive doubles.
toPrimitiveDoubleFromInteger(List<Integer>) - Static method in class org.tribuo.util.Util
Converts a boxed list of integers into an array of primitive doubles.
toPrimitiveFloat(List<Float>) - Static method in class org.tribuo.util.Util
Converts a boxed list of floats into an array of primitive floats.
toPrimitiveInt(List<Integer>) - Static method in class org.tribuo.util.Util
Converts a boxed list of integers into an array of primitive ints.
toPrimitiveLong(List<Long>) - Static method in class org.tribuo.util.Util
Converts a boxed list of longs into an array of primitive longs.
toReadableString() - Method in class org.tribuo.anomaly.AnomalyInfo
 
toReadableString() - Method in class org.tribuo.classification.ImmutableLabelInfo
 
toReadableString() - Method in class org.tribuo.classification.MutableLabelInfo
 
toReadableString() - Method in class org.tribuo.clustering.ClusteringInfo
 
toReadableString() - Method in class org.tribuo.FeatureMap
Same as the toString, but ordered by name, and with newlines.
toReadableString() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
toReadableString() - Method in class org.tribuo.multilabel.MutableMultiLabelInfo
 
toReadableString() - Method in interface org.tribuo.OutputInfo
Generates a String form of this OutputInfo.
toReadableString() - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
toReadableString() - Method in class org.tribuo.regression.MutableRegressionInfo
 
toString() - Method in class org.tribuo.anomaly.AnomalyFactory.AnomalyFactoryProvenance
 
toString() - Method in class org.tribuo.anomaly.AnomalyInfo
 
toString() - Method in class org.tribuo.anomaly.Event
 
toString() - Method in class org.tribuo.CategoricalIDInfo
 
toString() - Method in class org.tribuo.CategoricalInfo
 
toString() - Method in class org.tribuo.classification.baseline.DummyClassifierTrainer
 
toString() - Method in class org.tribuo.classification.dtree.CARTClassificationTrainer
 
toString() - Method in class org.tribuo.classification.dtree.impurity.Entropy
 
toString() - Method in class org.tribuo.classification.dtree.impurity.GiniIndex
 
toString() - Method in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
toString() - Method in class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
 
toString() - Method in class org.tribuo.classification.ensemble.VotingCombiner
 
toString() - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
toString() - Method in class org.tribuo.classification.evaluation.LabelMetric
 
toString() - Method in class org.tribuo.classification.example.CheckerboardDataSource
 
toString() - Method in class org.tribuo.classification.example.ConcentricCirclesDataSource
 
toString() - Method in class org.tribuo.classification.example.GaussianLabelDataSource
 
toString() - Method in class org.tribuo.classification.example.InterlockingCrescentsDataSource
 
toString() - Method in class org.tribuo.classification.example.NoisyInterlockingCrescentsDataSource
 
toString() - Method in class org.tribuo.classification.explanations.lime.LIMEExplanation
 
toString() - Method in class org.tribuo.classification.ImmutableLabelInfo
 
toString() - Method in class org.tribuo.classification.Label
 
toString() - Method in class org.tribuo.classification.LabelFactory.LabelFactoryProvenance
 
toString() - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
 
toString() - Method in class org.tribuo.classification.MutableLabelInfo
 
toString() - Method in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
 
toString() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
toString() - Method in class org.tribuo.classification.sequence.viterbi.DefaultFeatureExtractor
 
toString() - Method in class org.tribuo.classification.sequence.viterbi.NoopFeatureExtractor
 
toString() - Method in class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
 
toString() - Method in class org.tribuo.classification.sgd.crf.CRFTrainer
 
toString() - Method in class org.tribuo.classification.sgd.fm.FMClassificationTrainer
 
toString() - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
 
toString() - Method in class org.tribuo.classification.sgd.linear.LinearSGDTrainer
 
toString() - Method in class org.tribuo.classification.sgd.objectives.Hinge
 
toString() - Method in class org.tribuo.classification.sgd.objectives.LogMulticlass
 
toString() - Method in class org.tribuo.clustering.ClusterID
 
toString() - Method in class org.tribuo.clustering.ClusteringFactory.ClusteringFactoryProvenance
 
toString() - Method in class org.tribuo.clustering.ClusteringInfo
 
toString() - Method in class org.tribuo.clustering.evaluation.ClusteringMetric
 
toString() - Method in class org.tribuo.clustering.hdbscan.HdbscanTrainer
 
toString() - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
toString() - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
toString() - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
toString() - Method in class org.tribuo.common.libsvm.SVMParameters
 
toString() - Method in class org.tribuo.common.nearest.KNNTrainer
 
toString() - Method in class org.tribuo.common.tree.ExtraTreesTrainer
 
toString() - Method in class org.tribuo.common.tree.LeafNode
 
toString() - Method in class org.tribuo.common.tree.RandomForestTrainer
 
toString() - Method in class org.tribuo.common.tree.SplitNode
 
toString() - Method in class org.tribuo.common.tree.TreeModel
 
toString() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
 
toString() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
 
toString() - Method in class org.tribuo.common.xgboost.XGBoostTrainer
 
toString() - Method in class org.tribuo.data.columnar.ColumnarIterator.Row
 
toString() - Method in class org.tribuo.data.columnar.extractors.DateExtractor
 
toString() - Method in class org.tribuo.data.columnar.extractors.OffsetDateTimeExtractor
 
toString() - Method in class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
 
toString() - Method in class org.tribuo.data.columnar.processors.field.DateFieldProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.field.DoubleFieldProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.field.IdentityProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.field.RegexFieldProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.field.TextFieldProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.response.BinaryResponseProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
toString() - Method in class org.tribuo.data.columnar.processors.response.Quartile
 
toString() - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
toString() - Method in class org.tribuo.data.columnar.RowProcessor
 
toString() - Method in class org.tribuo.data.csv.CSVDataSource
 
toString() - Method in class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
Deprecated.
 
toString() - Method in class org.tribuo.data.sql.SQLDataSource
 
toString() - Method in class org.tribuo.data.sql.SQLDBConfig
 
toString() - Method in class org.tribuo.data.text.DirectoryFileSource
 
toString() - Method in class org.tribuo.data.text.impl.BasicPipeline
 
toString() - Method in class org.tribuo.data.text.impl.SimpleStringDataSource
 
toString() - Method in class org.tribuo.data.text.impl.TextFeatureExtractorImpl
 
toString() - Method in class org.tribuo.data.text.impl.TokenPipeline
 
toString() - Method in class org.tribuo.data.text.TextDataSource
 
toString() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
This toString doesn't put the indices in the string, as it's likely to be huge.
toString() - Method in class org.tribuo.dataset.DatasetView
 
toString() - Method in class org.tribuo.Dataset
 
toString() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
 
toString() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
 
toString() - Method in class org.tribuo.datasource.AggregateDataSource
 
toString() - Method in class org.tribuo.datasource.IDXDataSource
 
toString() - Method in class org.tribuo.datasource.LibSVMDataSource
 
toString() - Method in class org.tribuo.datasource.ListDataSource
 
toString() - Method in class org.tribuo.ensemble.BaggingTrainer
 
toString() - Method in class org.tribuo.evaluation.DescriptiveStats
 
toString() - Method in class org.tribuo.evaluation.metrics.MetricID
 
toString() - Method in class org.tribuo.evaluation.metrics.MetricTarget
 
toString() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
 
toString() - Method in class org.tribuo.Feature
 
toString() - Method in class org.tribuo.FeatureMap
 
toString() - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
 
toString() - Method in class org.tribuo.hash.HashCodeHasher
 
toString() - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
 
toString() - Method in class org.tribuo.hash.MessageDigestHasher
 
toString() - Method in class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
 
toString() - Method in class org.tribuo.hash.ModHashCodeHasher
 
toString() - Method in class org.tribuo.ImmutableDataset
 
toString() - Method in class org.tribuo.impl.ArrayExample
 
toString() - Method in class org.tribuo.impl.BinaryFeaturesExample
 
toString() - Method in class org.tribuo.impl.ListExample
 
toString() - Method in class org.tribuo.interop.ExternalTrainerProvenance
 
toString() - Method in class org.tribuo.interop.oci.OCILabelConverter
 
toString() - Method in class org.tribuo.interop.oci.OCIMultiLabelConverter
 
toString() - Method in class org.tribuo.interop.oci.OCIRegressorConverter
 
toString() - Method in class org.tribuo.interop.onnx.DenseTransformer
 
toString() - Method in class org.tribuo.interop.onnx.ImageTransformer
 
toString() - Method in class org.tribuo.interop.onnx.LabelOneVOneTransformer
 
toString() - Method in class org.tribuo.interop.onnx.LabelTransformer
 
toString() - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
 
toString() - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
toString() - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
toString() - Method in class org.tribuo.interop.tensorflow.ImageConverter
 
toString() - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
toString() - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
toString() - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
toString() - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
toString() - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
toString() - Method in class org.tribuo.interop.tensorflow.TensorMap
 
toString() - Method in class org.tribuo.json.JsonDataSource
 
toString() - Method in class org.tribuo.math.kernel.Linear
 
toString() - Method in class org.tribuo.math.kernel.Polynomial
 
toString() - Method in class org.tribuo.math.kernel.RBF
 
toString() - Method in class org.tribuo.math.kernel.Sigmoid
 
toString() - Method in class org.tribuo.math.la.DenseMatrix
 
toString() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
toString() - Method in class org.tribuo.math.la.DenseVector
 
toString() - Method in class org.tribuo.math.la.MatrixTuple
 
toString() - Method in class org.tribuo.math.la.SparseVector
 
toString() - Method in class org.tribuo.math.la.VectorTuple
 
toString() - Method in class org.tribuo.math.optimisers.AdaDelta
 
toString() - Method in class org.tribuo.math.optimisers.AdaGrad
 
toString() - Method in class org.tribuo.math.optimisers.AdaGradRDA
 
toString() - Method in class org.tribuo.math.optimisers.Adam
 
toString() - Method in class org.tribuo.math.optimisers.ParameterAveraging
 
toString() - Method in class org.tribuo.math.optimisers.Pegasos
 
toString() - Method in class org.tribuo.math.optimisers.RMSProp
 
toString() - Method in class org.tribuo.math.optimisers.SGD
 
toString() - Method in class org.tribuo.Model
 
toString() - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
 
toString() - Method in class org.tribuo.multilabel.ensemble.MultiLabelVotingCombiner
 
toString() - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
toString() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
This method produces a nicely formatted String output, with appropriate tabs and newlines, suitable for display on a terminal.
toString() - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
 
toString() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
toString() - Method in class org.tribuo.multilabel.MultiLabel
 
toString() - Method in class org.tribuo.multilabel.MultiLabelFactory.MultiLabelFactoryProvenance
 
toString() - Method in class org.tribuo.multilabel.MutableMultiLabelInfo
 
toString() - Method in class org.tribuo.multilabel.sgd.fm.FMMultiLabelTrainer
 
toString() - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
 
toString() - Method in class org.tribuo.multilabel.sgd.objectives.BinaryCrossEntropy
 
toString() - Method in class org.tribuo.multilabel.sgd.objectives.Hinge
 
toString() - Method in class org.tribuo.MutableDataset
 
toString() - Method in class org.tribuo.Prediction
 
toString() - Method in class org.tribuo.provenance.DatasetProvenance
 
toString() - Method in class org.tribuo.provenance.EnsembleModelProvenance
 
toString() - Method in class org.tribuo.provenance.EvaluationProvenance
 
toString() - Method in class org.tribuo.provenance.impl.EmptyDatasetProvenance
 
toString() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
 
toString() - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
 
toString() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
 
toString() - Method in class org.tribuo.provenance.ModelProvenance
 
toString() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
 
toString() - Method in class org.tribuo.RealIDInfo
 
toString() - Method in class org.tribuo.RealInfo
 
toString() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
 
toString() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
 
toString() - Method in class org.tribuo.regression.ensemble.AveragingCombiner
 
toString() - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
toString() - Method in class org.tribuo.regression.MutableRegressionInfo
 
toString() - Method in class org.tribuo.regression.RegressionFactory.RegressionFactoryProvenance
 
toString() - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
toString() - Method in class org.tribuo.regression.Regressor
 
toString() - Method in class org.tribuo.regression.rtree.CARTJointRegressionTrainer
 
toString() - Method in class org.tribuo.regression.rtree.CARTRegressionTrainer
 
toString() - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
 
toString() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
 
toString() - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
 
toString() - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
 
toString() - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
 
toString() - Method in class org.tribuo.regression.sgd.fm.FMRegressionTrainer
 
toString() - Method in class org.tribuo.regression.sgd.linear.LinearSGDTrainer
 
toString() - Method in class org.tribuo.regression.sgd.objectives.AbsoluteLoss
 
toString() - Method in class org.tribuo.regression.sgd.objectives.Huber
 
toString() - Method in class org.tribuo.regression.sgd.objectives.SquaredLoss
 
toString() - Method in class org.tribuo.regression.slm.ElasticNetCDTrainer
 
toString() - Method in class org.tribuo.regression.slm.LARSLassoTrainer
 
toString() - Method in class org.tribuo.regression.slm.LARSTrainer
 
toString() - Method in class org.tribuo.regression.slm.SLMTrainer
 
toString() - Method in record class org.tribuo.reproducibility.ReproUtil.FeatureDiff
Returns a string representation of this record class.
toString() - Method in record class org.tribuo.reproducibility.ReproUtil.ModelReproduction
Returns a string representation of this record class.
toString() - Method in record class org.tribuo.reproducibility.ReproUtil.OutputDiff
Returns a string representation of this record class.
toString() - Method in class org.tribuo.sequence.HashingSequenceTrainer
 
toString() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
 
toString() - Method in class org.tribuo.sequence.IndependentSequenceTrainer
 
toString() - Method in class org.tribuo.sequence.MutableSequenceDataset
 
toString() - Method in class org.tribuo.sequence.SequenceDataset
 
toString() - Method in class org.tribuo.sequence.SequenceModel
 
toString() - Method in class org.tribuo.SkeletalVariableInfo
 
toString() - Method in class org.tribuo.transform.TransformationMap
 
toString() - Method in class org.tribuo.transform.transformations.BinningTransformation
 
toString() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation
 
toString() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation
 
toString() - Method in class org.tribuo.transform.transformations.SimpleTransform
 
toString() - Method in class org.tribuo.transform.TransformerMap
 
toString() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
 
toString() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
 
toString() - Method in class org.tribuo.util.infotheory.impl.Row
 
toString() - Method in class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
 
toString() - Method in class org.tribuo.util.IntDoublePair
 
toString() - Method in class org.tribuo.util.MeanVarianceAccumulator
 
toString() - Method in class org.tribuo.util.onnx.ONNXAttribute
 
toString() - Method in class org.tribuo.util.tokens.Token
 
toString() - Method in class org.tribuo.util.tokens.universal.Range
 
totalCount - Variable in class org.tribuo.multilabel.MultiLabelInfo
 
totalObservations - Variable in class org.tribuo.CategoricalInfo
The total number of observations (including zeros).
totalSize() - Method in class org.tribuo.evaluation.TrainTestSplitter
The total amount of data in train and test combined.
tp() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the micro average of the number of true positives across all the labels, i.e., the total number of true positives.
tp() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of true positives.
tp() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the micro averaged true positive count.
tp() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
tp(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
tp(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
Gets the true positive count for that label.
tp(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Returns the number of true positives, possibly averaged depending on the metric target.
tp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
tp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
tp(T) - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the number of true positives, i.e., the number of times the label was correctly predicted.
tp(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of true positives for the supplied label.
TP - Enum constant in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
The number of true positives.
TP - Enum constant in enum class org.tribuo.classification.evaluation.LabelMetrics
The number of true positives.
TP - Enum constant in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
The number of true positives.
tpr - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.ROC
The true positive rate at the corresponding threshold.
train - Variable in class org.tribuo.evaluation.KFoldSplitter.TrainTestFold
The training fold.
train(Dataset<Event>, Map<String, Provenance>) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
 
train(Dataset<Label>) - Method in class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
 
train(Dataset<Label>, Map<String, Provenance>) - Method in class org.tribuo.classification.baseline.DummyClassifierTrainer
 
train(Dataset<Label>, Map<String, Provenance>) - Method in class org.tribuo.classification.ensemble.AdaBoostTrainer
If the trainer implements WeightedExamples then do boosting by weighting, otherwise do boosting by sampling.
train(Dataset<Label>, Map<String, Provenance>) - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
 
train(Dataset<Label>, Map<String, Provenance>) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
 
train(Dataset<Label>, Map<String, Provenance>) - Method in class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
 
train(Dataset<Label>, Map<String, Provenance>, int) - Method in class org.tribuo.classification.baseline.DummyClassifierTrainer
 
train(Dataset<Label>, Map<String, Provenance>, int) - Method in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
train(Dataset<Label>, Map<String, Provenance>, int) - Method in class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
 
train(Dataset<Label>, Map<String, Provenance>, int) - Method in class org.tribuo.classification.sgd.kernel.KernelSVMTrainer
 
train(Dataset<Label>, Map<String, Provenance>, int) - Method in class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
 
train(Dataset<ClusterID>) - Method in class org.tribuo.clustering.hdbscan.HdbscanTrainer
 
train(Dataset<ClusterID>) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
train(Dataset<ClusterID>, Map<String, Provenance>) - Method in class org.tribuo.clustering.hdbscan.HdbscanTrainer
 
train(Dataset<ClusterID>, Map<String, Provenance>) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
train(Dataset<ClusterID>, Map<String, Provenance>, int) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
train(Dataset<MultiLabel>) - Method in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
 
train(Dataset<MultiLabel>) - Method in class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
 
train(Dataset<MultiLabel>, Map<String, Provenance>) - Method in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
 
train(Dataset<MultiLabel>, Map<String, Provenance>) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
 
train(Dataset<MultiLabel>, Map<String, Provenance>) - Method in class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
 
train(Dataset<MultiLabel>, Map<String, Provenance>, int) - Method in class org.tribuo.multilabel.baseline.ClassifierChainTrainer
 
train(Dataset<MultiLabel>, Map<String, Provenance>, int) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
 
train(Dataset<MultiLabel>, Map<String, Provenance>, int) - Method in class org.tribuo.multilabel.ensemble.CCEnsembleTrainer
 
train(Dataset<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
 
train(Dataset<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.rtree.CARTRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.slm.ElasticNetCDTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.slm.SLMTrainer
Trains a sparse linear model.
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>, int) - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>, int) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>, int) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>, int) - Method in class org.tribuo.regression.rtree.CARTRegressionTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>, int) - Method in class org.tribuo.regression.slm.ElasticNetCDTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>, int) - Method in class org.tribuo.regression.slm.SLMTrainer
Trains a sparse linear model.
train(Dataset<Regressor>, Map<String, Provenance>, int) - Method in class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
 
train(Dataset<T>) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
train(Dataset<T>) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
train(Dataset<T>) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
train(Dataset<T>) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
train(Dataset<T>) - Method in class org.tribuo.ensemble.BaggingTrainer
 
train(Dataset<T>) - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
train(Dataset<T>) - Method in interface org.tribuo.SparseTrainer
Trains a sparse predictive model using the examples in the given data set.
train(Dataset<T>) - Method in interface org.tribuo.Trainer
Trains a predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.nearest.KNNTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.ensemble.BaggingTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.hash.HashingTrainer
This clones the Dataset, hashes each of the examples and rewrites their feature ids before passing it to the inner trainer.
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in interface org.tribuo.SparseTrainer
Trains a sparse predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>) - Method in interface org.tribuo.Trainer
Trains a predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.transform.TransformTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.common.nearest.KNNTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.ensemble.BaggingTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.hash.HashingTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
train(Dataset<T>, Map<String, Provenance>, int) - Method in interface org.tribuo.SparseTrainer
Trains a predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>, int) - Method in interface org.tribuo.Trainer
Trains a predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.transform.TransformTrainer
 
train(SequenceDataset<Label>, Map<String, Provenance>) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
The viterbi train method is unique because it delegates to a regular Model train method, but before it does, it adds features derived from preceding labels.
train(SequenceDataset<Label>, Map<String, Provenance>) - Method in class org.tribuo.classification.sgd.crf.CRFTrainer
 
train(SequenceDataset<T>) - Method in interface org.tribuo.sequence.SequenceTrainer
Trains a sequence prediction model using the examples in the given data set.
train(SequenceDataset<T>, Map<String, Provenance>) - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
train(SequenceDataset<T>, Map<String, Provenance>) - Method in class org.tribuo.sequence.HashingSequenceTrainer
This clones the SequenceDataset, hashes each of the examples and rewrites their feature ids before passing it to the inner trainer.
train(SequenceDataset<T>, Map<String, Provenance>) - Method in class org.tribuo.sequence.IndependentSequenceTrainer
 
train(SequenceDataset<T>, Map<String, Provenance>) - Method in interface org.tribuo.sequence.SequenceTrainer
Trains a sequence prediction model using the examples in the given data set.
TRAIN_INVOCATION_COUNT - Static variable in interface org.tribuo.provenance.TrainerProvenance
The name of the provenance field recording the train invocation count.
trainDataset - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
Path to a serialised SequenceDataset used for training.
trainDataset - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
Path to a serialised SequenceDataset used for training.
trainDimension(double[], SparseVector[], float[], SplittableRandom) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
Trains a single dimension of the possibly multiple dimensions.
trainDimension(double[], SparseVector[], float[], SplittableRandom) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
Trains a single dimension of the possibly multiple dimensions.
trainer - Variable in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
Load a trainer from the config file.
trainer - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
Name of the trainer in the configuration file.
trainer - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
Load a trainer from the config file.
trainer - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
Load a trainer from the config file.
Trainer<T extends Output<T>> - Interface in org.tribuo
An interface for things that can train predictive models.
TRAINER - Enum constant in enum class org.tribuo.json.StripProvenance.ProvenanceTypes
Select the trainer provenance.
TRAINER - Static variable in class org.tribuo.provenance.ModelProvenance
 
trainerOptions - Variable in class org.tribuo.classification.experiments.TrainTest.AllClassificationOptions
All the classification trainer options.
trainerOptions - Variable in class org.tribuo.classification.sgd.fm.TrainTest.TrainTestOptions
 
trainerOptions - Variable in class org.tribuo.classification.sgd.kernel.TrainTest.TrainTestOptions
The Kernel SVM SGD options.
trainerOptions - Variable in class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
The linear SGD trainer options.
trainerProvenance - Variable in class org.tribuo.provenance.ModelProvenance
 
TrainerProvenance - Interface in org.tribuo.provenance
A tag interface for trainer provenances.
TrainerProvenanceImpl - Class in org.tribuo.provenance.impl
An implementation of TrainerProvenance that delegates everything to SkeletalTrainerProvenance.
TrainerProvenanceImpl(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.TrainerProvenanceImpl
Construct a TrainerProvenance by extracting the necessary fields from the supplied map.
TrainerProvenanceImpl(SequenceTrainer<T>) - Constructor for class org.tribuo.provenance.impl.TrainerProvenanceImpl
Construct a TrainerProvenance by reading all the configurable parameters along with the train call count.
TrainerProvenanceImpl(Trainer<T>) - Constructor for class org.tribuo.provenance.impl.TrainerProvenanceImpl
Construct a TrainerProvenance by reading all the configurable parameters along with the train call count.
trainerType - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
trainExplainer(Example<Regressor>, List<Example<Regressor>>) - Method in class org.tribuo.classification.explanations.lime.LIMEBase
Trains the explanation model using the supplied sampled data and the input example.
TRAINING_INFO_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ModelProto
 
TRAINING_TIME - Static variable in class org.tribuo.provenance.ModelProvenance
 
trainingPath - Variable in class org.tribuo.data.DataOptions
Path to the training file.
trainingPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Path to the libsvm format training file.
trainInvocationCounter - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
trainInvocationCounter - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
 
trainInvocationCounter - Variable in class org.tribuo.common.xgboost.XGBoostTrainer
 
trainInvocationCounter - Variable in class org.tribuo.ensemble.BaggingTrainer
 
trainInvocationCounter - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
trainInvocationCounter - Variable in class org.tribuo.regression.slm.SLMTrainer
 
trainModels(Parameter, int, FeatureNode[][], double[][]) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyTrainer
 
trainModels(Parameter, int, FeatureNode[][], double[][]) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
 
trainModels(Parameter, int, FeatureNode[][], double[][]) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
Train all the liblinear instances necessary for this dataset.
trainModels(Parameter, int, FeatureNode[][], double[][]) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionTrainer
 
trainModels(svm_parameter, int, svm_node[][], double[][], SplittableRandom) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
 
trainModels(svm_parameter, int, svm_node[][], double[][], SplittableRandom) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
 
trainModels(svm_parameter, int, svm_node[][], double[][], SplittableRandom) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
Train all the LibSVM instances necessary for this dataset.
trainModels(svm_parameter, int, svm_node[][], double[][], SplittableRandom) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionTrainer
 
trainOp - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
trainPath - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
Output training data file.
trainSingleModel(Dataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, int, Map<String, Provenance>, int) - Method in class org.tribuo.ensemble.BaggingTrainer
Trains a single model.
trainSource - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
Load the training DataSource from the config file.
TrainTest - Class in org.tribuo.classification.dtree
Build and run a decision tree classifier for a standard dataset.
TrainTest - Class in org.tribuo.classification.experiments
Build and run a classifier for a standard dataset.
TrainTest - Class in org.tribuo.classification.liblinear
Build and run a liblinear-java classifier for a standard dataset.
TrainTest - Class in org.tribuo.classification.libsvm
Build and run a LibSVM classifier for a standard dataset.
TrainTest - Class in org.tribuo.classification.mnb
Build and run a multinomial naive bayes classifier for a standard dataset.
TrainTest - Class in org.tribuo.classification.sgd.fm
Build and run a classifier for a standard dataset using FMClassificationTrainer.
TrainTest - Class in org.tribuo.classification.sgd.kernel
Build and run a kernel SVM classifier for a standard dataset.
TrainTest - Class in org.tribuo.classification.sgd
Build and run a classifier for a standard dataset using LinearSGDTrainer.
TrainTest - Class in org.tribuo.classification.xgboost
Build and run an XGBoost classifier for a standard dataset.
TrainTest - Class in org.tribuo.clustering.hdbscan
Build and run a HDBSCAN* clustering model for a standard dataset.
TrainTest - Class in org.tribuo.clustering.kmeans
Build and run a k-means clustering model for a standard dataset.
TrainTest - Class in org.tribuo.interop.tensorflow
Build and run a Tensorflow multi-class classifier for a standard dataset.
TrainTest - Class in org.tribuo.regression.liblinear
Build and run a LibLinear regressor for a standard dataset.
TrainTest - Class in org.tribuo.regression.libsvm
Build and run a LibSVM regressor for a standard dataset.
TrainTest - Class in org.tribuo.regression.rtree
Build and run a regression tree for a standard dataset.
TrainTest - Class in org.tribuo.regression.sgd.fm
Build and run a regression factorization machine for a standard dataset.
TrainTest - Class in org.tribuo.regression.sgd
Build and run a linear regression for a standard dataset.
TrainTest - Class in org.tribuo.regression.slm
Build and run a sparse linear regression model for a standard dataset.
TrainTest - Class in org.tribuo.regression.xgboost
Build and run an XGBoost regressor for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.dtree.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.experiments.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.liblinear.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.libsvm.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.mnb.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.sgd.fm.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.sgd.kernel.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.sgd.TrainTest
 
TrainTest() - Constructor for class org.tribuo.classification.xgboost.TrainTest
 
TrainTest() - Constructor for class org.tribuo.clustering.hdbscan.TrainTest
 
TrainTest() - Constructor for class org.tribuo.clustering.kmeans.TrainTest
 
TrainTest() - Constructor for class org.tribuo.interop.tensorflow.TrainTest
 
TrainTest() - Constructor for class org.tribuo.regression.liblinear.TrainTest
 
TrainTest() - Constructor for class org.tribuo.regression.libsvm.TrainTest
 
TrainTest() - Constructor for class org.tribuo.regression.rtree.TrainTest
 
TrainTest() - Constructor for class org.tribuo.regression.sgd.fm.TrainTest
 
TrainTest() - Constructor for class org.tribuo.regression.sgd.TrainTest
 
TrainTest() - Constructor for class org.tribuo.regression.slm.TrainTest
 
TrainTest() - Constructor for class org.tribuo.regression.xgboost.TrainTest
 
TrainTest.AllClassificationOptions - Class in org.tribuo.classification.experiments
Command line options.
TrainTest.FMRegressionOptions - Class in org.tribuo.regression.sgd.fm
Command line options.
TrainTest.HdbscanCLIOptions - Class in org.tribuo.clustering.hdbscan
Options for the HDBSCAN* CLI.
TrainTest.ImpurityType - Enum Class in org.tribuo.regression.rtree
Impurity function.
TrainTest.InputType - Enum Class in org.tribuo.interop.tensorflow
Type of feature extractor.
TrainTest.KMeansOptions - Class in org.tribuo.clustering.kmeans
Options for the K-Means CLI.
TrainTest.LibLinearOptions - Class in org.tribuo.regression.liblinear
Command line options.
TrainTest.LibSVMOptions - Class in org.tribuo.regression.libsvm
Command line options.
TrainTest.LossEnum - Enum Class in org.tribuo.regression.sgd.fm
Loss function.
TrainTest.LossEnum - Enum Class in org.tribuo.regression.sgd
Loss function.
TrainTest.RegressionTreeOptions - Class in org.tribuo.regression.rtree
Command line options.
TrainTest.SGDOptions - Class in org.tribuo.regression.sgd
Command line options.
TrainTest.SLMOptions - Class in org.tribuo.regression.slm
Command line options.
TrainTest.SLMType - Enum Class in org.tribuo.regression.slm
Type of sparse linear model.
TrainTest.TensorflowOptions - Class in org.tribuo.interop.tensorflow
Options for training a model in TensorFlow.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.dtree
Command line options.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.liblinear
Command line options.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.libsvm
Command line options.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.mnb
Command line options.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.sgd.fm
Command line options.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.sgd.kernel
Command line options.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.sgd
Command line options.
TrainTest.TrainTestOptions - Class in org.tribuo.classification.xgboost
Command line options.
TrainTest.TreeType - Enum Class in org.tribuo.regression.rtree
Type of tree trainer.
TrainTest.XGBoostOptions - Class in org.tribuo.regression.xgboost
Command line options.
TrainTestHelper - Class in org.tribuo.classification
This class provides static methods used by the demo classes in each classification backend.
TrainTestOptions() - Constructor for class org.tribuo.classification.dtree.TrainTest.TrainTestOptions
 
TrainTestOptions() - Constructor for class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
 
TrainTestOptions() - Constructor for class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
 
TrainTestOptions() - Constructor for class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
 
TrainTestOptions() - Constructor for class org.tribuo.classification.sgd.fm.TrainTest.TrainTestOptions
 
TrainTestOptions() - Constructor for class org.tribuo.classification.sgd.kernel.TrainTest.TrainTestOptions
 
TrainTestOptions() - Constructor for class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
 
TrainTestOptions() - Constructor for class org.tribuo.classification.xgboost.TrainTest.TrainTestOptions
 
TrainTestSplitOptions() - Constructor for class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
 
TrainTestSplitter<T extends Output<T>> - Class in org.tribuo.evaluation
Splits data into training and testing sets.
TrainTestSplitter(DataSource<T>) - Constructor for class org.tribuo.evaluation.TrainTestSplitter
Creates a splitter that splits a dataset 70/30 train and test using a default seed.
TrainTestSplitter(DataSource<T>, double, long) - Constructor for class org.tribuo.evaluation.TrainTestSplitter
Creates a splitter that will split the given data set into a training and testing set.
TrainTestSplitter(DataSource<T>, long) - Constructor for class org.tribuo.evaluation.TrainTestSplitter
Creates a splitter that splits a dataset 70/30 train and test.
TrainTestSplitter.SplitDataSourceProvenance - Class in org.tribuo.evaluation
Provenance for a split data source.
transform(double) - Method in class org.tribuo.transform.transformations.SimpleTransform
Apply the operation to the input.
transform(double) - Method in interface org.tribuo.transform.Transformer
Applies the transformation to the supplied input value.
transform(OrtEnvironment, List<SparseVector>) - Method in class org.tribuo.interop.onnx.DenseTransformer
 
transform(OrtEnvironment, List<SparseVector>) - Method in interface org.tribuo.interop.onnx.ExampleTransformer
Converts a list of SparseVectors representing a batch of features into a OnnxTensor.
transform(OrtEnvironment, List<SparseVector>) - Method in class org.tribuo.interop.onnx.ImageTransformer
 
transform(OrtEnvironment, SparseVector) - Method in class org.tribuo.interop.onnx.DenseTransformer
 
transform(OrtEnvironment, SparseVector) - Method in interface org.tribuo.interop.onnx.ExampleTransformer
Converts a SparseVector representing the features into a OnnxTensor.
transform(OrtEnvironment, SparseVector) - Method in class org.tribuo.interop.onnx.ImageTransformer
 
transform(TransformerMap) - Method in class org.tribuo.Example
Transforms this example by applying the transformations from the supplied TransformerMap.
transform(TransformerMap) - Method in class org.tribuo.impl.ArrayExample
 
transform(TransformerMap) - Method in class org.tribuo.impl.BinaryFeaturesExample
 
transform(TransformerMap) - Method in class org.tribuo.impl.ListExample
 
transform(TransformerMap) - Method in class org.tribuo.MutableDataset
Applies all the transformations from the TransformerMap to this dataset.
Transformation - Interface in org.tribuo.transform
An interface representing a class of transformations which can be applied to a feature.
TransformationList(List<Transformation>) - Constructor for class org.tribuo.transform.TransformationMap.TransformationList
Constructs a transformation list.
transformationMap - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
Load a transformation map from the config file.
transformationMap - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
Load a transformation map from the config file.
TransformationMap - Class in org.tribuo.transform
A carrier type for a set of transformations to be applied to a Dataset.
TransformationMap(List<Transformation>) - Constructor for class org.tribuo.transform.TransformationMap
Creates a TransformationMap with only global transformations.
TransformationMap(List<Transformation>, Map<String, List<Transformation>>) - Constructor for class org.tribuo.transform.TransformationMap
Creates a transformation map from the supplied global transformation list, and per feature transformations.
TransformationMap(Map<String, List<Transformation>>) - Constructor for class org.tribuo.transform.TransformationMap
Creates a TransformationMap with only per feature transformations.
TransformationMap.TransformationList - Class in org.tribuo.transform
A carrier type as OLCUT does not support nested generics.
TransformationProvenance - Interface in org.tribuo.transform
A tag interface for provenances in the transformation system.
transformDataset(Dataset<T>) - Method in class org.tribuo.transform.TransformerMap
Copies the supplied dataset and applies the transformers to each example in it.
transformDataset(Dataset<T>, boolean) - Method in class org.tribuo.transform.TransformerMap
Copies the supplied dataset and applies the transformers to each example in it.
TransformedModel<T extends Output<T>> - Class in org.tribuo.transform
Wraps a Model with it's TransformerMap so all Examples are transformed appropriately before the model makes predictions.
Transformer - Interface in org.tribuo.transform
A fitted Transformation which can apply a transform to the input value.
TransformerMap - Class in org.tribuo.transform
A collection of Transformers which can be applied to a Dataset or Example.
TransformerMap(Map<String, List<Transformer>>, DatasetProvenance, ConfiguredObjectProvenance) - Constructor for class org.tribuo.transform.TransformerMap
Constructs a transformer map which encapsulates a set of transformers that can be applied to features.
TransformerMap.TransformerMapProvenance - Class in org.tribuo.transform
Provenance for TransformerMap.
TransformerMapProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.TransformerMap.TransformerMapProvenance
Deserialization constructor.
transformExample(Example<T>) - Method in class org.tribuo.transform.TransformerMap
Copies the supplied example and applies the transformers to it.
transformExample(Example<T>, List<String>) - Method in class org.tribuo.transform.TransformerMap
Copies the supplied example and applies the transformers to it.
transformOutput(Prediction<Label>) - Static method in class org.tribuo.classification.explanations.lime.LIMEBase
Transforms a Prediction for a multiclass problem into a Regressor output which represents the probability for each class.
transformProvenances - Variable in class org.tribuo.MutableDataset
The provenances of the transformations applied to this dataset.
TransformStatistics - Interface in org.tribuo.transform
An interface for the statistics that need to be collected for a specific Transformation on a single feature.
transformToBatchOutput(List<OnnxValue>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.onnx.LabelTransformer
 
transformToBatchOutput(List<OnnxValue>, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
 
transformToBatchOutput(List<OnnxValue>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
transformToBatchOutput(List<OnnxValue>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.onnx.OutputTransformer
Converts a OnnxValue containing multiple outputs into a list of Outputs.
transformToBatchPrediction(List<OnnxValue>, ImmutableOutputInfo<Label>, int[], List<Example<Label>>) - Method in class org.tribuo.interop.onnx.LabelTransformer
 
transformToBatchPrediction(List<OnnxValue>, ImmutableOutputInfo<MultiLabel>, int[], List<Example<MultiLabel>>) - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
 
transformToBatchPrediction(List<OnnxValue>, ImmutableOutputInfo<Regressor>, int[], List<Example<Regressor>>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
transformToBatchPrediction(List<OnnxValue>, ImmutableOutputInfo<T>, int[], List<Example<T>>) - Method in interface org.tribuo.interop.onnx.OutputTransformer
Converts a OnnxValue containing multiple outputs into a list of Predictions.
transformToOutput(List<OnnxValue>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.onnx.LabelTransformer
 
transformToOutput(List<OnnxValue>, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
 
transformToOutput(List<OnnxValue>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
transformToOutput(List<OnnxValue>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.onnx.OutputTransformer
Converts a OnnxValue into the specified output type.
transformToPrediction(List<OnnxValue>, ImmutableOutputInfo<Label>, int, Example<Label>) - Method in class org.tribuo.interop.onnx.LabelTransformer
 
transformToPrediction(List<OnnxValue>, ImmutableOutputInfo<MultiLabel>, int, Example<MultiLabel>) - Method in class org.tribuo.interop.onnx.MultiLabelTransformer
 
transformToPrediction(List<OnnxValue>, ImmutableOutputInfo<Regressor>, int, Example<Regressor>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
transformToPrediction(List<OnnxValue>, ImmutableOutputInfo<T>, int, Example<T>) - Method in interface org.tribuo.interop.onnx.OutputTransformer
Converts a OnnxValue into a Prediction.
TransformTrainer<T extends Output<T>> - Class in org.tribuo.transform
A Trainer which encapsulates another trainer plus a TransformationMap object to apply to each Dataset before training each Model.
TransformTrainer(Trainer<T>, TransformationMap) - Constructor for class org.tribuo.transform.TransformTrainer
Creates a trainer which transforms the data before training, and stores the transformers along with the trained model in a TransformedModel.
TransformTrainer(Trainer<T>, TransformationMap, boolean) - Constructor for class org.tribuo.transform.TransformTrainer
Creates a trainer which transforms the data before training, and stores the transformers along with the trained model in a TransformedModel.
TransformTrainer(Trainer<T>, TransformationMap, boolean, boolean) - Constructor for class org.tribuo.transform.TransformTrainer
Creates a trainer which transforms the data before training, and stores the transformers along with the trained model in a TransformedModel.
transitionValues - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainCliqueValues
The label-label transition matrix.
transpose() - Method in class org.tribuo.math.la.DenseMatrix
Returns a transposed copy of this matrix.
transpose(Dataset<T>) - Static method in class org.tribuo.math.la.SparseVector
Converts a dataset of row-major examples into an array of column-major sparse vectors.
transpose(Dataset<T>, ImmutableFeatureMap) - Static method in class org.tribuo.math.la.SparseVector
Converts a dataset of row-major examples into an array of column-major sparse vectors.
transpose(SparseVector[]) - Static method in class org.tribuo.math.la.SparseVector
Transposes an array of sparse vectors from row-major to column-major or vice versa.
TreeFeature - Class in org.tribuo.regression.rtree.impl
An inverted feature, which stores a reference to all the values of this feature.
TreeFeature(int) - Constructor for class org.tribuo.regression.rtree.impl.TreeFeature
Constructs an inverted feature with the specified feature id.
TreeModel<T extends Output<T>> - Class in org.tribuo.common.tree
A Model wrapped around a decision tree root Node.
TreeModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, Map<String, List<String>>) - Constructor for class org.tribuo.common.tree.TreeModel
Constructs a trained decision tree model.
treeType - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Tree type.
Tribuo - Class in org.tribuo
This class stores the current Tribuo version, along with other compile time information.
Tribuo() - Constructor for class org.tribuo.Tribuo
 
TRIBUO_NATIVE - Enum constant in enum class org.tribuo.interop.tensorflow.TensorFlowTrainer.TFModelFormat
Saves the model inside the Tribuo object, emits a TensorFlowNativeModel.
TRIBUO_VERSION_STRING - Static variable in class org.tribuo.provenance.ModelProvenance
 
TRIBUO_VERSION_STRING - Static variable in interface org.tribuo.provenance.TrainerProvenance
The name of the provenance field recording the Tribuo version used in training.
TripleDistribution<T1,T2,T3> - Class in org.tribuo.util.infotheory.impl
Generates the counts for a triplet of vectors.
TripleDistribution(long, Map<CachedTriple<T1, T2, T3>, MutableLong>, Map<CachedPair<T1, T2>, MutableLong>, Map<CachedPair<T1, T3>, MutableLong>, Map<CachedPair<T2, T3>, MutableLong>, Map<T1, MutableLong>, Map<T2, MutableLong>, Map<T3, MutableLong>) - Constructor for class org.tribuo.util.infotheory.impl.TripleDistribution
Constructs a triple distribution from the supplied distributions.
tryAdvance(Consumer<? super ColumnarIterator.Row>) - Method in class org.tribuo.data.columnar.ColumnarIterator
 
TWEEDIE - Enum constant in enum class org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Tweedie loss function.
twoNorm() - Method in class org.tribuo.math.la.DenseMatrix
 
twoNorm() - Method in class org.tribuo.math.la.DenseSparseMatrix
 
twoNorm() - Method in class org.tribuo.math.la.DenseVector
 
twoNorm() - Method in interface org.tribuo.math.la.SGDVector
Calculates the euclidean norm for this vector.
twoNorm() - Method in class org.tribuo.math.la.SparseVector
 
twoNorm() - Method in interface org.tribuo.math.la.Tensor
Calculates the euclidean norm for this vector.
twoNorm() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
twoNorm() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
type - Variable in class org.tribuo.classification.ensemble.ClassificationEnsembleOptions
Ensemble method, options are {ADABOOST, BAGGING, RF}.
type - Variable in class org.tribuo.util.infotheory.example.InformationTheoryDemo.DemoOptions
The type of the input distribution.
type - Variable in class org.tribuo.util.tokens.Token
The token type.
type - Variable in class org.tribuo.util.tokens.universal.Range
The current token type.
TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.AttributeProto
 
TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.ValueInfoProto
 

U

UBYTE - Enum constant in enum class org.tribuo.datasource.IDXDataSource.IDXType
An unsigned byte.
UINT16 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
uint16_t
UINT16_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
uint16_t
UINT32 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
UINT32 = 12;
UINT32_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
UINT32 = 12;
UINT64 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
UINT64 = 13;
UINT64_DATA_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TensorProto
 
UINT64_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
UINT64 = 13;
UINT8 - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
uint8_t
UINT8_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
uint8_t
UNASSIGNED - Static variable in class org.tribuo.clustering.ClusterID
The sentinel unassigned cluster ID.
UNASSIGNED_CLUSTER_ID - Static variable in class org.tribuo.clustering.ClusteringFactory
The sentinel unassigned cluster id, used when there is no ground truth clustering.
UNDEFINED - Enum constant in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
UNDEFINED = 0;
UNDEFINED - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
UNDEFINED = 0;
UNDEFINED_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
UNDEFINED = 0;
UNDEFINED_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
UNDEFINED = 0;
UNIFORM - Enum constant in enum class org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Samples uniformly from the label domain.
uniformSample(SplittableRandom) - Method in class org.tribuo.CategoricalInfo
 
uniformSample(SplittableRandom) - Method in class org.tribuo.RealInfo
 
uniformSample(SplittableRandom) - Method in interface org.tribuo.VariableInfo
Sample a value uniformly from the range of this variable.
unionSize(MultiLabel, MultiLabel) - Static method in class org.tribuo.multilabel.MultiLabel
The number of unique labels across both MultiLabels.
UniqueAggregator - Class in org.tribuo.data.text.impl
Aggregates feature tokens, generating unique features.
UniqueAggregator() - Constructor for class org.tribuo.data.text.impl.UniqueAggregator
Constructs an aggregator that replaces all features with the same name with a single feature with the last observed value of that feature.
UniqueAggregator(double) - Constructor for class org.tribuo.data.text.impl.UniqueAggregator
Constructs an aggregator that replaces all features with the same name with a single feature with the specified value.
UniqueProcessor - Class in org.tribuo.data.columnar.processors.feature
Processes a feature list, aggregating all the feature values with the same name.
UniqueProcessor(UniqueProcessor.UniqueType) - Constructor for class org.tribuo.data.columnar.processors.feature.UniqueProcessor
Creates a UniqueProcessor using the specified reduction operation.
UniqueProcessor.UniqueType - Enum Class in org.tribuo.data.columnar.processors.feature
The type of reduction operation to perform.
UNIVERSAL - Enum constant in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
UniversalTokenizer - Class in org.tribuo.util.tokens.universal
This class was originally written for the purpose of document indexing in an information retrieval context (principally used in Sun Labs' Minion search engine).
UniversalTokenizer() - Constructor for class org.tribuo.util.tokens.universal.UniversalTokenizer
Constructs a universal tokenizer which doesn't send punctuation.
UniversalTokenizer(boolean) - Constructor for class org.tribuo.util.tokens.universal.UniversalTokenizer
Constructs a universal tokenizer.
UNKNOWN - Enum constant in enum class org.tribuo.anomaly.Event.EventType
An unknown (i.e., unlabelled) event, with id -1.
UNKNOWN - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
Some tokenizers may work in concert with vocabulary data.
UNKNOWN - Static variable in class org.tribuo.classification.Label
The name of the unknown label (i.e., an unlabelled output).
UNKNOWN_EVENT - Static variable in class org.tribuo.anomaly.AnomalyFactory
The unknown event.
UNKNOWN_LABEL - Static variable in class org.tribuo.classification.LabelFactory
The singleton unknown label, used for unlablled examples.
UNKNOWN_MULTILABEL - Static variable in class org.tribuo.multilabel.MultiLabelFactory
The sentinel unknown multi-label output used to signal there is no ground truth value.
UNKNOWN_MULTIPLE_REGRESSOR - Static variable in class org.tribuo.regression.RegressionFactory
Deprecated.
Deprecated when regression was made multidimensional by default. Use RegressionFactory.UNKNOWN_REGRESSOR instead.
UNKNOWN_REGRESSOR - Static variable in class org.tribuo.regression.RegressionFactory
The sentinel unknown regressor, used when there is no ground truth regressor value.
UNKNOWN_TOKEN - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Default unknown token name.
UNKNOWN_VERSION - Static variable in class org.tribuo.provenance.ModelProvenance
 
unknownCount - Variable in class org.tribuo.anomaly.AnomalyInfo
The number of unknown events observed (i.e., those without labels).
unknownCount - Variable in class org.tribuo.classification.LabelInfo
The number of unknown labels this LabelInfo has seen.
unknownCount - Variable in class org.tribuo.clustering.ClusteringInfo
 
unknownCount - Variable in class org.tribuo.multilabel.MultiLabelInfo
 
unknownCount - Variable in class org.tribuo.regression.RegressionInfo
 
unpack(int[]) - Method in class org.tribuo.classification.sgd.crf.Chunk
Copies the labels into the constraints array starting at Chunk.begin.
UNSQUEEZE - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Adds extra dimensions to a tensor in the specified places, the axes are the second input.
update(Tensor[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
 
update(Tensor[]) - Method in class org.tribuo.common.sgd.FMParameters
 
update(Tensor[]) - Method in class org.tribuo.math.LinearParameters
 
update(Tensor[]) - Method in interface org.tribuo.math.Parameters
Apply gradients to the parameters.
UPDATE_BINDING_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
UPPERCASE - Enum constant in enum class org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Uppercase the input text.
useBias() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
Returns true if the SparseVector should be constructed with a bias feature.
useBias() - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
Returns true if the SparseVector should be constructed with a bias feature.
useMomentum - Variable in class org.tribuo.math.optimisers.SGD
 
useRandomSplitPoints - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
Whether to choose split points for features at random.
useRandomSplitPoints - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
Whether to choose split points for features at random.
username - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
Username for the SQL database
utf8Charset - Static variable in class org.tribuo.hash.MessageDigestHasher
Util - Class in org.tribuo.classification.sgd
SGD utilities.
Util - Class in org.tribuo.regression.sgd
Utilities.
Util - Class in org.tribuo.util
Ye olde util class.
Util() - Constructor for class org.tribuo.classification.sgd.Util
 
Util() - Constructor for class org.tribuo.regression.sgd.Util
 
Util.ExampleArray - Class in org.tribuo.classification.sgd
A nominal tuple.
Util.SequenceExampleArray - Class in org.tribuo.classification.sgd
A nominal tuple.

V

val1 - Variable in class org.tribuo.util.MurmurHash3.LongPair
First value.
val2 - Variable in class org.tribuo.util.MurmurHash3.LongPair
Second value.
validate(Class<? extends Output<?>>) - Method in class org.tribuo.Dataset
Validates that this Dataset does in fact contain the supplied output type.
validate(Class<? extends Output<?>>) - Method in class org.tribuo.Model
Validates that this Model does in fact support the supplied output type.
validate(Class<? extends Output<?>>) - Method in class org.tribuo.sequence.SequenceModel
Validates that this Model does in fact support the supplied output type.
validateCondaName(String) - Static method in class org.tribuo.interop.oci.OCIUtil
Validates that the name is a valid conda environment.
validateCondaPath(String) - Static method in class org.tribuo.interop.oci.OCIUtil
Validates that the path is a valid OCI object storage path.
validateExample() - Method in class org.tribuo.Example
Checks the example to see if all the feature names are unique, the feature values are not NaN, and there is at least one feature.
validateExample() - Method in class org.tribuo.impl.ArrayExample
 
validateExample() - Method in class org.tribuo.impl.BinaryFeaturesExample
 
validateExample() - Method in class org.tribuo.impl.ListExample
 
validateExample() - Method in class org.tribuo.sequence.SequenceExample
Checks that each Example in this sequence is valid.
validateMapping() - Method in class org.tribuo.regression.ImmutableRegressionInfo
Returns true if the id numbers correspond to a lexicographic ordering of the dimension names starting from zero, false otherwise.
validateMapping(Map<T, Integer>) - Static method in interface org.tribuo.OutputFactory
Validates that the mapping can be used as an output info, i.e.
validateParamNames(Set<String>) - Method in enum class org.tribuo.interop.tensorflow.GradientOptimiser
Checks that the parameter names in the supplied set are an exact match for the parameter names that this gradient optimiser expects.
validateSalt(String) - Static method in class org.tribuo.hash.Hasher
Salt validation is currently a test to see if the string is longer than Hasher.MIN_LENGTH.
validateTransformations(FeatureMap) - Method in class org.tribuo.transform.TransformationMap
Checks that a given transformation set doesn't have conflicts when applied to the supplied featureMap.
validationPath - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
Output validation data file.
value - Variable in enum class org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
The log value used by the XGBoost native library.
value - Variable in enum class org.tribuo.data.DataOptions.Delimiter
The delimiter character.
value - Variable in enum class org.tribuo.datasource.IDXDataSource.IDXType
The encoded byte value.
value - Variable in class org.tribuo.Feature
The feature value.
value - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple
The feature value.
value - Variable in class org.tribuo.math.la.MatrixTuple
The value.
value - Variable in class org.tribuo.math.la.VectorTuple
The current value.
value - Variable in class org.tribuo.regression.rtree.impl.InvertedFeature
The feature value of this object.
value - Variable in class org.tribuo.util.IntDoublePair
The value.
VALUE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
VALUE_INFO_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.GraphProto
 
VALUE_NOT_SET - Enum constant in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
 
VALUE_NOT_SET - Enum constant in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
 
VALUE_TYPE_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
valueAndGradient(int, SGDVector) - Method in interface org.tribuo.classification.sgd.LabelObjective
valueAndGradient(int, SGDVector) - Method in class org.tribuo.classification.sgd.objectives.Hinge
Deprecated.
valueAndGradient(int, SGDVector) - Method in class org.tribuo.classification.sgd.objectives.LogMulticlass
Deprecated.
valueAndGradient(SGDVector[], int[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Generates predictions based on the input features and labels, then scores those predictions to produce a loss for the example and a gradient update.
valueCounts - Variable in class org.tribuo.CategoricalInfo
The occurrence counts of each value.
valueOf(int) - Static method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
Deprecated.
valueOf(int) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
Deprecated.
valueOf(int) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Deprecated.
valueOf(int) - Static method in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
Deprecated.
valueOf(int) - Static method in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
Deprecated.
valueOf(int) - Static method in enum class ai.onnx.proto.OnnxMl.Version
Deprecated.
valueOf(Descriptors.EnumValueDescriptor) - Static method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
Returns the enum constant of this class with the specified name.
valueOf(Descriptors.EnumValueDescriptor) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
Returns the enum constant of this class with the specified name.
valueOf(Descriptors.EnumValueDescriptor) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Returns the enum constant of this class with the specified name.
valueOf(Descriptors.EnumValueDescriptor) - Static method in enum class ai.onnx.proto.OnnxMl.Version
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class ai.onnx.proto.OnnxMl.Version
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.anomaly.Event.EventType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.anomaly.liblinear.LinearAnomalyType.LinearType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.anomaly.libsvm.SVMAnomalyType.SVMMode
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.dtree.CARTClassificationOptions.ImpurityType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.dtree.CARTClassificationOptions.TreeType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.evaluation.LabelMetrics
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.libsvm.SVMClassificationType.SVMMode
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.sequence.viterbi.ViterbiModel.ScoreAggregation
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions.ViterbiLabelFeatures
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.sgd.crf.CRFModel.ConfidenceType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.sgd.fm.FMClassificationOptions.LossEnum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.classification.sgd.linear.LinearSGDOptions.LossEnum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.clustering.hdbscan.HdbscanTrainer.Distance
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Distance
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.common.libsvm.KernelType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.common.nearest.KNNClassifierOptions.EnsembleCombinerType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.common.nearest.KNNModel.Backend
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.common.nearest.KNNTrainer.Distance
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.data.columnar.processors.field.RegexFieldProcessor.Mode
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.data.DataOptions.Delimiter
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.data.DataOptions.InputFormat
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.datasource.AggregateDataSource.IterationOrder
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.datasource.IDXDataSource.IDXType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.evaluation.metrics.EvaluationMetric.Average
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.hash.HashingOptions.ModelHashingType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions.Mode
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.OutputPooling
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.interop.tensorflow.GradientOptimiser
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.interop.tensorflow.TensorFlowTrainer.TFModelFormat
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.interop.tensorflow.TrainTest.InputType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.json.StripProvenance.ProvenanceTypes
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.math.optimisers.SGD.Momentum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions.LossEnum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.multilabel.sgd.linear.LinearSGDOptions.LossEnum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.liblinear.LinearRegressionType.LinearType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.libsvm.SVMRegressionType.SVMMode
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.rtree.TrainTest.ImpurityType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.rtree.TrainTest.TreeType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.sgd.fm.TrainTest.LossEnum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.sgd.TrainTest.LossEnum
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.slm.TrainTest.SLMType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.transform.transformations.BinningTransformation.BinningType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.util.infotheory.example.InformationTheoryDemo.DistributionType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.util.infotheory.WeightedInformationTheory.VariableSelector
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.util.onnx.ONNXOperators
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.tribuo.util.tokens.Token.TokenType
Returns the enum constant of this class with the specified name.
values - Variable in class org.tribuo.CategoricalInfo
The values array.
values - Variable in class org.tribuo.math.la.DenseMatrix
 
values - Variable in class org.tribuo.math.la.SparseVector
 
values() - Static method in enum class ai.onnx.proto.OnnxMl.AttributeProto.AttributeType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataLocation
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class ai.onnx.proto.OnnxMl.TensorProto.DataType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension.ValueCase
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class ai.onnx.proto.OnnxMl.TypeProto.ValueCase
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class ai.onnx.proto.OnnxMl.Version
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.anomaly.evaluation.AnomalyMetrics
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.anomaly.Event.EventType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.anomaly.liblinear.LinearAnomalyType.LinearType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.anomaly.libsvm.SVMAnomalyType.SVMMode
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.dtree.CARTClassificationOptions.ImpurityType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.dtree.CARTClassificationOptions.TreeType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.evaluation.LabelMetrics
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.liblinear.LinearClassificationType.LinearType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.libsvm.SVMClassificationType.SVMMode
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.sequence.viterbi.ViterbiModel.ScoreAggregation
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions.ViterbiLabelFeatures
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.sgd.crf.CRFModel.ConfidenceType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.sgd.fm.FMClassificationOptions.LossEnum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.classification.sgd.linear.LinearSGDOptions.LossEnum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.clustering.evaluation.ClusteringMetrics
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.clustering.hdbscan.HdbscanTrainer.Distance
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Distance
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.common.libsvm.KernelType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.common.nearest.KNNClassifierOptions.EnsembleCombinerType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.common.nearest.KNNModel.Backend
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.common.nearest.KNNTrainer.Distance
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.data.columnar.processors.field.RegexFieldProcessor.Mode
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.data.DataOptions.Delimiter
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.data.DataOptions.InputFormat
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.datasource.AggregateDataSource.IterationOrder
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.datasource.IDXDataSource.IDXType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Method in class org.tribuo.evaluation.DescriptiveStats
Returns a copy of the values.
values() - Static method in enum class org.tribuo.evaluation.metrics.EvaluationMetric.Average
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.hash.HashingOptions.ModelHashingType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.interop.oci.OCIModelCLI.OCIModelOptions.Mode
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.interop.oci.OCIUtil.OCIModelType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.OutputPooling
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.interop.tensorflow.GradientOptimiser
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.interop.tensorflow.TensorFlowTrainer.TFModelFormat
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.interop.tensorflow.TrainTest.InputType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.json.StripProvenance.ProvenanceTypes
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.math.optimisers.SGD.Momentum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.multilabel.evaluation.MultiLabelMetrics
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.multilabel.sgd.fm.FMMultiLabelOptions.LossEnum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.multilabel.sgd.linear.LinearSGDOptions.LossEnum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.evaluation.RegressionMetrics
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.liblinear.LinearRegressionType.LinearType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.libsvm.SVMRegressionType.SVMMode
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.rtree.TrainTest.ImpurityType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.rtree.TrainTest.TreeType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.sgd.fm.TrainTest.LossEnum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.sgd.TrainTest.LossEnum
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.slm.TrainTest.SLMType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.transform.transformations.BinningTransformation.BinningType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.transform.transformations.SimpleTransform.Operation
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.util.infotheory.example.InformationTheoryDemo.DistributionType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.util.infotheory.WeightedInformationTheory.VariableSelector
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.util.onnx.ONNXOperators
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.tribuo.util.tokens.Token.TokenType
Returns an array containing the constants of this enum class, in the order they are declared.
VALUES_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
VARIABLE_V2 - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
The name of the variable op.
VariableIDInfo - Interface in org.tribuo
Adds an id number to a VariableInfo.
VariableInfo - Interface in org.tribuo
A VariableInfo subclass contains information about a feature and its observed values.
VARIADIC_INPUT - Static variable in class org.tribuo.util.onnx.ONNXAttribute
Value used to denote a varaidic input in an ONNX operator
variance - Variable in class org.tribuo.common.sgd.AbstractFMTrainer
 
variance - Variable in class org.tribuo.regression.sgd.fm.TrainTest.FMRegressionOptions
Variance of the initialization gaussian.
variance() - Method in interface org.tribuo.math.la.SGDVector
Calculates the variance of this vector.
variance(double) - Method in class org.tribuo.math.la.DenseVector
 
variance(double) - Method in interface org.tribuo.math.la.SGDVector
Calculates the variance of this vector based on the supplied mean.
variance(double) - Method in class org.tribuo.math.la.SparseVector
 
VectorIterator - Interface in org.tribuo.math.la
vectorNorm(double[]) - Static method in class org.tribuo.util.Util
Computes the vector two-norm.
VectorNormalizer - Interface in org.tribuo.math.util
A functional interface that generates a normalized version of a double array.
VectorTuple - Class in org.tribuo.math.la
A mutable tuple used to avoid allocation when iterating a vector.
VectorTuple() - Constructor for class org.tribuo.math.la.VectorTuple
Creates an empty vector tuple.
VectorTuple(int, int) - Constructor for class org.tribuo.math.la.VectorTuple
Creates a vector tuple with the specified values.
VERSION - Static variable in class org.tribuo.Tribuo
The full Tribuo version string.
VERSION_FIELD_NUMBER - Static variable in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
versionString - Variable in class org.tribuo.provenance.ModelProvenance
 
viterbi(ChainHelper.ChainCliqueValues) - Static method in class org.tribuo.classification.sgd.crf.ChainHelper
Runs Viterbi on a linear chain CRF.
ViterbiModel - Class in org.tribuo.classification.sequence.viterbi
An implementation of a viterbi model.
ViterbiModel.ScoreAggregation - Enum Class in org.tribuo.classification.sequence.viterbi
Types of label score aggregation.
ViterbiTrainer - Class in org.tribuo.classification.sequence.viterbi
Builds a Viterbi model using the supplied Trainer.
ViterbiTrainer(Trainer<Label>, LabelFeatureExtractor, int, ViterbiModel.ScoreAggregation) - Constructor for class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
Constructs a ViterbiTrainer wrapping the specified trainer.
ViterbiTrainer(Trainer<Label>, LabelFeatureExtractor, ViterbiModel.ScoreAggregation) - Constructor for class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
Constructs a ViterbiTrainer wrapping the specified trainer, with an unbounded stack size.
ViterbiTrainerOptions - Class in org.tribuo.classification.sequence.viterbi
Options for building a viterbi trainer.
ViterbiTrainerOptions() - Constructor for class org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions
 
ViterbiTrainerOptions.ViterbiLabelFeatures - Enum Class in org.tribuo.classification.sequence.viterbi
Type of label features to include.
VOTING - Enum constant in enum class org.tribuo.common.nearest.KNNClassifierOptions.EnsembleCombinerType
VotingCombiner - Class in org.tribuo.classification.ensemble
A combiner which performs a weighted or unweighted vote across the predicted labels.
VotingCombiner() - Constructor for class org.tribuo.classification.ensemble.VotingCombiner
Constructs a voting combiner.

W

WARNING - Enum constant in enum class org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
Only warnings are logged.
WARNING_THRESHOLD - Static variable in class org.tribuo.interop.onnx.DenseTransformer
Number of times the feature size warning should be printed.
WARNING_THRESHOLD - Static variable in class org.tribuo.interop.tensorflow.DenseFeatureConverter
Number of times the feature size warning should be printed.
WEEK_OF_MONTH - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The week of the month, as defined by ISO 8601 semantics for week of the year.
WEEK_OF_YEAR - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The week of the year in ISO 8601.
weight - Variable in class org.tribuo.Example
The weight associated with this example.
weight - Variable in class org.tribuo.regression.rtree.impurity.RegressorImpurity.ImpurityTuple
The sum of the weights.
weight - Variable in class org.tribuo.util.infotheory.impl.WeightCountTuple
The current weight.
WeightCountTuple - Class in org.tribuo.util.infotheory.impl
A mutable tuple of a double and a long.
WeightCountTuple() - Constructor for class org.tribuo.util.infotheory.impl.WeightCountTuple
Creates a zeroed WeightCountTuple.
WeightCountTuple(double, long) - Constructor for class org.tribuo.util.infotheory.impl.WeightCountTuple
Creates a WeightCountTuple with the specifed values.
weightedConditionalEntropy(ArrayList<T1>, ArrayList<T2>, ArrayList<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete Shannon/Guiasu Weighted Conditional Entropy of two arrays, using histogram probability estimators.
WeightedEnsembleModel<T extends Output<T>> - Class in org.tribuo.ensemble
An ensemble model that uses weights to combine the ensemble member predictions.
WeightedEnsembleModel(String, EnsembleModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Model<T>>, EnsembleCombiner<T>) - Constructor for class org.tribuo.ensemble.WeightedEnsembleModel
Unless you are implementing a Trainer you should not use this constructor directly.
WeightedEnsembleModel(String, EnsembleModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Model<T>>, EnsembleCombiner<T>, float[]) - Constructor for class org.tribuo.ensemble.WeightedEnsembleModel
Unless you are implementing a Trainer you should not use this constructor directly.
weightedEntropy(ArrayList<T>, ArrayList<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
Calculates the discrete Shannon/Guiasu Weighted Entropy, using histogram probability estimators.
WeightedExamples - Interface in org.tribuo
Tag interface denoting that a Trainer can use example weights.
WeightedInformationTheory - Class in org.tribuo.util.infotheory
A class of (discrete) weighted information theoretic functions.
WeightedInformationTheory.VariableSelector - Enum Class in org.tribuo.util.infotheory
Chooses which variable is the one with associated weights.
WeightedLabels - Interface in org.tribuo.classification
Tag interface denoting the Trainer can use label weights.
weightedMean(double[], double[]) - Static method in class org.tribuo.util.Util
Returns the weighted mean of the input.
weightedMean(double[], float[], int) - Static method in class org.tribuo.util.Util
Computes the weighted mean of the first length elements of the array.
WeightedPairDistribution<T1,T2> - Class in org.tribuo.util.infotheory.impl
Generates the counts for a pair of vectors.
WeightedPairDistribution(long, LinkedHashMap<CachedPair<T1, T2>, WeightCountTuple>, LinkedHashMap<T1, WeightCountTuple>, LinkedHashMap<T2, WeightCountTuple>) - Constructor for class org.tribuo.util.infotheory.impl.WeightedPairDistribution
Constructs a weighted pair distribution from the supplied values.
WeightedPairDistribution(long, Map<CachedPair<T1, T2>, WeightCountTuple>, Map<T1, WeightCountTuple>, Map<T2, WeightCountTuple>) - Constructor for class org.tribuo.util.infotheory.impl.WeightedPairDistribution
Constructs a weighted pair distribution from the supplied values.
weightedSum(double[], float[], int) - Static method in class org.tribuo.util.Util
Computes the weighted sum of the first length elements of the array.
WeightedTripleDistribution<T1,T2,T3> - Class in org.tribuo.util.infotheory.impl
Generates the counts for a triplet of vectors.
WeightedTripleDistribution(long, Map<CachedTriple<T1, T2, T3>, WeightCountTuple>, Map<CachedPair<T1, T2>, WeightCountTuple>, Map<CachedPair<T1, T3>, WeightCountTuple>, Map<CachedPair<T2, T3>, WeightCountTuple>, Map<T1, WeightCountTuple>, Map<T2, WeightCountTuple>, Map<T3, WeightCountTuple>) - Constructor for class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
Constructs a weighted triple distribution from the supplied values.
weightExtractor - Variable in class org.tribuo.data.columnar.RowProcessor
 
weights - Variable in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
A list of weights to use in classification.
weights - Variable in class org.tribuo.classification.sgd.Util.ExampleArray
The example weights.
weights - Variable in class org.tribuo.classification.sgd.Util.SequenceExampleArray
The sequence example weights.
weights - Variable in class org.tribuo.ensemble.WeightedEnsembleModel
 
WHERE - Enum constant in enum class org.tribuo.util.onnx.ONNXOperators
Choice operator, based on the true value of the condition input, returns the element at that index from either the second or third input.
WHITESPACE - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
Some tokenizers may produce tokens corresponding to whitespace (e.g.
whitespaceSplitCharacterFunction - Static variable in class org.tribuo.util.tokens.impl.WhitespaceTokenizer
The splitting function for whitespace, using Character.isWhitespace(char).
WhitespaceTokenizer - Class in org.tribuo.util.tokens.impl
A simple tokenizer that splits on whitespace.
WhitespaceTokenizer() - Constructor for class org.tribuo.util.tokens.impl.WhitespaceTokenizer
Constructs a tokenizer that splits on whitespace.
WIDTH_CONSTANT - Static variable in class org.tribuo.classification.explanations.lime.LIMEBase
Width of the noise gaussian.
WORD - Enum constant in enum class org.tribuo.util.tokens.Token.TokenType
A WORD corresponds to a token that does not consist of or contain whitespace and may correspond to a regular "word" that could be looked up in a dictionary.
wordpiece(String) - Method in class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Executes Wordpiece tokenization on the provided token.
Wordpiece - Class in org.tribuo.util.tokens.impl.wordpiece
This is vanilla implementation of the Wordpiece algorithm as found here: https://github.com/huggingface/transformers/blob/master/src/transformers/models/bert/tokenization_bert.py
Wordpiece(String) - Constructor for class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Constructs a wordpiece by reading the vocabulary from the supplied path.
Wordpiece(String, String, int) - Constructor for class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Initializes an instance of Wordpiece with the given vocabulary, unknown token, and max word length.
Wordpiece(Set<String>) - Constructor for class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Constructs a Wordpiece using the supplied vocab.
Wordpiece(Set<String>, String) - Constructor for class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Constructs a Wordpiece using the supplied vocabulary and unknown token.
Wordpiece(Set<String>, String, int) - Constructor for class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Initializes an instance of Wordpiece with the given vocabulary, unknown token, and max word length.
WordpieceBasicTokenizer - Class in org.tribuo.util.tokens.impl.wordpiece
This is a tokenizer that is used "upstream" of WordpieceTokenizer and implements much of the functionality of the 'BasicTokenizer' implementation in huggingface.
WordpieceBasicTokenizer() - Constructor for class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Constructs a default tokenizer which tokenizes Chinese characters.
WordpieceBasicTokenizer(boolean) - Constructor for class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Constructs a tokenizer.
WordpieceTokenizer - Class in org.tribuo.util.tokens.impl.wordpiece
This Tokenizer is meant to be a reasonable approximation of the BertTokenizer defined here.
WordpieceTokenizer(Wordpiece, Tokenizer, boolean, boolean, Set<String>) - Constructor for class org.tribuo.util.tokens.impl.wordpiece.WordpieceTokenizer
Constructs a wordpiece tokenizer.
wrapFeatures(String, List<Feature>) - Static method in class org.tribuo.data.columnar.processors.field.TextFieldProcessor
Convert the Features from a text pipeline into ColumnarFeatures with the right field name.
wrapTrainer(Trainer<Label>) - Method in class org.tribuo.classification.ensemble.ClassificationEnsembleOptions
Wraps the supplied trainer using the ensemble trainer described by these options.
writeLibSVMFormat(Dataset<T>, PrintStream, boolean, Function<T, Number>) - Static method in class org.tribuo.datasource.LibSVMDataSource
Writes out a dataset in LibSVM format.
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel
 
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationModel
 
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.common.sgd.AbstractFMModel
Writes this Model into OnnxMl.GraphProto.Builder inside the input's ONNXContext.
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.common.sgd.AbstractLinearSGDModel
Writes this Model into OnnxMl.GraphProto.Builder inside the input's ONNXContext.
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
 
writeONNXGraph(ONNXRef<?>) - Method in interface org.tribuo.ONNXExportable
Writes this Model into OnnxMl.GraphProto.Builder inside the input's ONNXContext.
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
 
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
 
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.regression.slm.SparseLinearModel
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.AttributeProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.GraphProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.ModelProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.NodeProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.OperatorSetIdProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.SparseTensorProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.StringStringEntryProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TensorAnnotation
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TensorProto.Segment
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TensorProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto.Dimension
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TensorShapeProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TrainingInfoProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Map
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Opaque
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Sequence
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TypeProto.SparseTensor
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TypeProto.Tensor
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.TypeProto
 
writeTo(CodedOutputStream) - Method in class ai.onnx.proto.OnnxMl.ValueInfoProto
 

X

X1 - Static variable in class org.tribuo.classification.example.DemoLabelDataSource
The first feature name.
X2 - Static variable in class org.tribuo.classification.example.DemoLabelDataSource
The second feature name.
xbgAlpha - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
L1 regularization term for weights.
xgbBoosterType - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Weak learning algorithm.
xgbEnsembleSize - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Number of trees in the ensemble.
xgbEta - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Step size shrinkage parameter (range [0,1]).
xgbGamma - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Minimum loss reduction to make a split (range [0,Infinity]).
xgbLambda - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
L2 regularization term for weights.
xgbLogLevel - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Make the XGBoost training procedure quiet.
xgbMaxDepth - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Max tree depth (range (0,Integer.MAX_VALUE]).
xgbMinWeight - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Minimum sum of instance weights needed in a leaf (range [0,Infinity]).
xgbNumThreads - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Number of threads to use (range (1, num hw threads)).
XGBOOST - Enum constant in enum class org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
XGBoostClassificationConverter - Class in org.tribuo.classification.xgboost
Converts XGBoost outputs into Label Predictions.
XGBoostClassificationConverter() - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationConverter
Constructs an XGBoostClassificationConverter.
XGBoostClassificationTrainer - Class in org.tribuo.classification.xgboost
A Trainer which wraps the XGBoost training procedure.
XGBoostClassificationTrainer() - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
For olcut.
XGBoostClassificationTrainer(int) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
Create an XGBoost trainer.
XGBoostClassificationTrainer(int, double, double, int, double, double, double, double, double, int, boolean, long) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
Create an XGBoost trainer.
XGBoostClassificationTrainer(int, int, boolean) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
Create an XGBoost trainer.
XGBoostClassificationTrainer(int, Map<String, Object>) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
This gives direct access to the XGBoost parameter map.
XGBoostClassificationTrainer(XGBoostTrainer.BoosterType, XGBoostTrainer.TreeMethod, int, double, double, int, double, double, double, double, double, int, XGBoostTrainer.LoggingVerbosity, long) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
Create an XGBoost trainer.
XGBoostExternalModel<T extends Output<T>> - Class in org.tribuo.common.xgboost
A Model which wraps around a XGBoost.Booster which was trained by a system other than Tribuo.
XGBoostFeatureImportance - Class in org.tribuo.common.xgboost
Generate and collate feature importance information from the XGBoost model.
XGBoostFeatureImportance.XGBoostFeatureImportanceInstance - Class in org.tribuo.common.xgboost
An instance of feature importance values for a single feature.
XGBoostModel<T extends Output<T>> - Class in org.tribuo.common.xgboost
A Model which wraps around a XGBoost.Booster.
xgboostOptions - Variable in class org.tribuo.classification.xgboost.TrainTest.TrainTestOptions
The XGBoost trainer options.
xgBoostOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
Options for XGBoost trainers.
XGBoostOptions - Class in org.tribuo.classification.xgboost
CLI options for training an XGBoost classifier.
XGBoostOptions - Class in org.tribuo.regression.xgboost
CLI options for configuring an XGBoost regression trainer.
XGBoostOptions() - Constructor for class org.tribuo.classification.xgboost.XGBoostOptions
 
XGBoostOptions() - Constructor for class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
XGBoostOptions() - Constructor for class org.tribuo.regression.xgboost.XGBoostOptions
 
XGBoostOutputConverter<T extends Output<T>> - Interface in org.tribuo.common.xgboost
Converts the output of XGBoost into the appropriate prediction type.
XGBoostRegressionConverter - Class in org.tribuo.regression.xgboost
Converts XGBoost outputs into Regressor Predictions.
XGBoostRegressionConverter() - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionConverter
Construct an XGBoostRegressionConverter.
XGBoostRegressionTrainer - Class in org.tribuo.regression.xgboost
A Trainer which wraps the XGBoost training procedure.
XGBoostRegressionTrainer(int) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
Creates an XGBoostRegressionTrainer using the default parameters, the squared error loss and the supplied number of trees.
XGBoostRegressionTrainer(XGBoostTrainer.BoosterType, XGBoostTrainer.TreeMethod, XGBoostRegressionTrainer.RegressionType, int, double, double, int, double, double, double, double, double, int, XGBoostTrainer.LoggingVerbosity, long) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
Create an XGBoost trainer.
XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType, int) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
Creates an XGBoostRegressionTrainer using the default parameters, the supplied loss and the supplied number of trees.
XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType, int, double, double, int, double, double, double, double, double, int, boolean, long) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
Create an XGBoost trainer.
XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType, int, int, boolean) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
Creates an XGBoostRegressionTrainer using the default parameters with the supplied loss, number of trees, number of threads, and logging level.
XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType, int, Map<String, Object>) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
This gives direct access to the XGBoost parameter map.
XGBoostRegressionTrainer.RegressionType - Enum Class in org.tribuo.regression.xgboost
Types of regression loss.
XGBoostTrainer<T extends Output<T>> - Class in org.tribuo.common.xgboost
A Trainer which wraps the XGBoost training procedure.
XGBoostTrainer() - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
For olcut.
XGBoostTrainer(int) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
Constructs an XGBoost trainer using the specified number of trees.
XGBoostTrainer(int, double, double, int, double, double, double, double, double, int, boolean, long) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
Create an XGBoost trainer.
XGBoostTrainer(int, int, boolean) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
Constructs an XGBoost trainer using the specified number of trees.
XGBoostTrainer(int, Map<String, Object>) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
This gives direct access to the XGBoost parameter map.
XGBoostTrainer(XGBoostTrainer.BoosterType, XGBoostTrainer.TreeMethod, int, double, double, int, double, double, double, double, double, int, XGBoostTrainer.LoggingVerbosity, long) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
Create an XGBoost trainer.
XGBoostTrainer.BoosterType - Enum Class in org.tribuo.common.xgboost
The type of XGBoost model.
XGBoostTrainer.DMatrixTuple<T extends Output<T>> - Class in org.tribuo.common.xgboost
Tuple of a DMatrix, the number of valid features in each example, and the examples themselves.
XGBoostTrainer.LoggingVerbosity - Enum Class in org.tribuo.common.xgboost
The logging verbosity of the native library.
XGBoostTrainer.TreeMethod - Enum Class in org.tribuo.common.xgboost
The tree building algorithm.
XGBoostTrainer.XGBoostTrainerProvenance - Class in org.tribuo.common.xgboost
Deprecated.
XGBoostTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer.XGBoostTrainerProvenance
Deprecated.
 
XGBoostTrainerProvenance(XGBoostTrainer<T>) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer.XGBoostTrainerProvenance
Deprecated.
 
xgbQuiet - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Deprecated, use xgb-loglevel.
xgbSubsample - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Subsample size for each tree (range (0,1]).
xgbSubsampleFeatures - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Subsample features for each tree (range (0,1]).
xgbTreeMethod - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
Tree building algorithm.
XOR - Enum constant in enum class org.tribuo.util.infotheory.example.InformationTheoryDemo.DistributionType
Data generated from an XOR function.

Y

YEAR - Enum constant in enum class org.tribuo.data.columnar.processors.field.DateFieldProcessor.DateFeatureType
The year.

Z

zeroIndexed - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
Is the libsvm file zero indexed.
zipArraysCached(ArrayList<T1>, ArrayList<T2>) - Static method in class org.tribuo.util.infotheory.impl.CachedPair
Takes two arrays and zips them together into an array of CachedPairs.

_

_START_VERSION - Enum constant in enum class ai.onnx.proto.OnnxMl.Version
proto3 requires the first enum value to be zero.
_START_VERSION_VALUE - Static variable in enum class ai.onnx.proto.OnnxMl.Version
proto3 requires the first enum value to be zero.
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _ 
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form