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A

a - Variable in class org.tribuo.util.infotheory.impl.CachedTriple
 
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(AbstractCARTTrainer<T>) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer.AbstractCARTTrainerProvenance
Deprecated.
 
AbstractCARTTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer.AbstractCARTTrainerProvenance
Deprecated.
 
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
 
AbstractLinearSGDModel<T extends Output<T>> - Class in org.tribuo.common.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> - Class in org.tribuo.common.sgd
A trainer for a linear model which uses SGD.
AbstractLinearSGDTrainer(StochasticGradientOptimiser, int, int, int, long) - Constructor for class org.tribuo.common.sgd.AbstractLinearSGDTrainer
Constructs an SGD trainer for a linear model.
AbstractLinearSGDTrainer() - Constructor for class org.tribuo.common.sgd.AbstractLinearSGDTrainer
For olcut.
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
 
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(StochasticGradientOptimiser, int, int, int, long, boolean) - Constructor for class org.tribuo.common.sgd.AbstractSGDTrainer
Constructs an SGD trainer.
AbstractSGDTrainer(boolean) - Constructor for class org.tribuo.common.sgd.AbstractSGDTrainer
Base constructor called by subclass no-args constructors used by OLCUT.
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(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(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() - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
The overall accuracy of the evaluation.
accuracy(Label) - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
The per label accuracy of the evaluation.
accuracy() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
accuracy(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
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(double, double) - Constructor for class org.tribuo.math.optimisers.AdaDelta
It's recommended to keep rho at 0.95.
AdaDelta(double) - Constructor for class org.tribuo.math.optimisers.AdaDelta
Keeps rho at 0.95, passes through epsilon.
AdaDelta() - Constructor for class org.tribuo.math.optimisers.AdaDelta
Sets rho to 0.95 and epsilon to 1e-6.
AdaGrad - Class in org.tribuo.math.optimisers
An implementation of the AdaGrad gradient optimiser.
AdaGrad(double, double) - Constructor for class org.tribuo.math.optimisers.AdaGrad
 
AdaGrad(double) - Constructor for class org.tribuo.math.optimisers.AdaGrad
Sets epsilon to 1e-6.
AdaGradRDA - Class in org.tribuo.math.optimisers
An implementation of the AdaGrad gradient optimiser with regularized dual averaging.
AdaGradRDA(double, double, double, double, int) - Constructor for class org.tribuo.math.optimisers.AdaGradRDA
 
AdaGradRDA(double, double) - Constructor for class org.tribuo.math.optimisers.AdaGradRDA
 
Adam - Class in org.tribuo.math.optimisers
An implementation of the Adam gradient optimiser.
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(double, double) - Constructor for class org.tribuo.math.optimisers.Adam
Sets betaOne to 0.9 and betaTwo to 0.999
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.
add(Feature) - Method in class org.tribuo.Example
Adds a feature.
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>, 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(String, double) - Method in class org.tribuo.impl.ArrayExample
Adds a single feature.
add(Feature) - Method in class org.tribuo.impl.ArrayExample
 
add(String) - Method in class org.tribuo.impl.BinaryFeaturesExample
Adds a single feature with a value of 1.
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(int, int, double) - Method in class org.tribuo.math.la.DenseMatrix
 
add(int, int, double) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
add(SGDVector) - Method in class org.tribuo.math.la.DenseVector
Adds other to this vector, producing a new DenseVector.
add(int, double) - Method in class org.tribuo.math.la.DenseVector
 
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, double) - Method in interface org.tribuo.math.la.SGDVector
Adds value to the element at index.
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(int, double) - Method in class org.tribuo.math.la.SparseVector
 
add(Example<T>) - Method in class org.tribuo.MutableDataset
Adds an example to the dataset, which observes the output and each feature value.
add(String, double) - Method in class org.tribuo.MutableFeatureMap
Adds an occurrence of a feature with a given name.
add(int) - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
 
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>, 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(SequenceExample<T>) - Method in class org.tribuo.sequence.MutableSequenceDataset
Adds a SequenceExample to this dataset.
add(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that adds the operand to each value.
add(Row<T>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
add(int, Row<T>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
add() - Static method in interface org.tribuo.util.Merger
A merger which adds the elements.
addAcrossDim1(int[], double) - Method in class org.tribuo.math.la.DenseMatrix
 
addAcrossDim2(int[], double) - Method in class org.tribuo.math.la.DenseMatrix
 
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 Example<T>>) - Method in class org.tribuo.MutableDataset
Adds all the Examples in the supplied collection to this dataset.
addAll(Collection<SequenceExample<T>>) - Method in class org.tribuo.sequence.MutableSequenceDataset
Adds all the SequenceExamples in the supplied collection to this dataset.
addAll(Collection<? extends Row<T>>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
addAll(int, Collection<? extends Row<T>>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
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.
addExample(Example<T>) - Method in class org.tribuo.sequence.SequenceExample
Adds an Example to this sequence.
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 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 in org.tribuo.datasource
Specifies the iteration order of the inner sources.
AggregateDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
 
algorithm - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
 
algorithm - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
 
algorithm - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
 
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
 
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 in org.tribuo.classification.experiments
Types of algorithms supported.
alpha - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
 
alpha - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
alpha - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
alphas - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainBPResults
 
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_EVENT - Static variable in class org.tribuo.anomaly.AnomalyFactory
The anomalous 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 in org.tribuo.anomaly.evaluation
Default metrics for evaluating anomaly detection.
apply(E) - Method in interface org.tribuo.evaluation.EvaluationRenderer
Convert the evaluation to a string.
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.
applyCase(String) - Method in enum org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Apply the appropriate casing operation.
applyOptimiser(Graph, Operand<T>, Map<String, Float>) - Method in enum 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.
ARCH_STRING - Static variable in class org.tribuo.provenance.ModelProvenance
 
archString - Variable in class org.tribuo.provenance.ModelProvenance
 
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.
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.
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
 
ArrayExample<T extends Output<T>> - Class in org.tribuo.impl
An Example backed by two arrays, one of String and one of double.
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, float) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output and a weight.
ArrayExample(T, Map<String, Object>) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output and the metadata.
ArrayExample(T) - Constructor for class org.tribuo.impl.ArrayExample
Constructs an example from an output.
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(Example<T>) - Constructor for class org.tribuo.impl.ArrayExample
Copy constructor.
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
 
ASSIGN_PLACEHOLDER - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
 
ATTENTION_MASK - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
auc(double[], double[]) - Static method in class org.tribuo.util.Util
Calculates the area under the curve, bounded below by the x axis.
AUCROC(Label) - Method in interface org.tribuo.classification.evaluation.LabelEvaluation
Area under the ROC curve.
AUCROC(Label, List<Prediction<Label>>) - Static method in enum org.tribuo.classification.evaluation.LabelMetrics
Area under the ROC curve.
AUCROC(MetricTarget<Label>, List<Prediction<Label>>) - Static method in enum org.tribuo.classification.evaluation.LabelMetrics
Area under the ROC curve.
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.
averagedExplainedVariance() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
The average explained variance across all dimensions.
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(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(MetricTarget<Label>, List<Prediction<Label>>) - Static method in enum org.tribuo.classification.evaluation.LabelMetrics
 
averagedPrecision(Label, List<Prediction<Label>>) - Static method in enum 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
 

B

b - Variable in class org.tribuo.util.infotheory.impl.CachedTriple
 
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
 
BaggingTrainer(Trainer<T>, EnsembleCombiner<T>, int, long) - Constructor for class org.tribuo.ensemble.BaggingTrainer
 
balancedErrorRate() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the balanced error rate, i.e., the mean of the per label recalls.
balancedErrorRate(ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the balanced error rate, i.e., the mean of the recalls.
balancedErrorRate() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
balancedErrorRate() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
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
 
batchSize - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
batchSize - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
begin - Variable in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
 
begin - Variable in class org.tribuo.classification.sgd.crf.Chunk
 
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<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 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
 
BIAS_FEATURE - Static variable in class org.tribuo.Model
Used to denote the bias feature in a linear model.
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.
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(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, float) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output and a weight.
BinaryFeaturesExample(T, Map<String, Object>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output and the metadata.
BinaryFeaturesExample(T) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Constructs an example from an output.
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(Example<T>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample
Copy constructor.
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.
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
 
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 in org.tribuo.transform.transformations
The allowed binning types.
BinningTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
 
breakIteratorOptions - Variable in class org.tribuo.util.tokens.options.CoreTokenizerOptions
 
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
 
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
 
BUILD_TIMESTAMP - Static variable in class org.tribuo.Tribuo
The build timestamp.
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.
buildRandomTree(int[], SplittableRandom) - Method in class org.tribuo.classification.dtree.impl.ClassifierTrainingNode
Builds a CART tree with randomly chosen split points.
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).

C

c - Variable in class org.tribuo.util.infotheory.impl.CachedTriple
 
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
 
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
 
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(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.
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.
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.
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
 
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 in org.tribuo.classification.dtree
The impurity algorithm.
CARTClassificationOptions.TreeType - Enum 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(int, float, float, float, boolean, LabelImpurity, long) - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART Trainer.
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, long) - 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, LabelImpurity, long) - Constructor for class org.tribuo.classification.dtree.CARTClassificationTrainer
Creates a CART Trainer.
cartImpurity - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
CARTJointRegressionTrainer - Class in org.tribuo.regression.rtree
A Trainer that uses an approximation of the CART algorithm to build a decision tree.
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.
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.
cartMaxDepth - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
cartMinChildWeight - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
cartMinImpurityDecrease - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
cartOptions - Variable in class org.tribuo.classification.dtree.TrainTest.TrainTestOptions
 
cartOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
 
cartPrintTree - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
cartRandomSplit - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
CARTRegressionTrainer - Class in org.tribuo.regression.rtree
A Trainer that uses an approximation of the CART algorithm to build a decision tree.
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.
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.
cartSeed - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
cartSplitFraction - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
cartTreeAlgorithm - Variable in class org.tribuo.classification.dtree.CARTClassificationOptions
 
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 in org.tribuo.data.text.impl
The possible casing operations.
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.
cdf - Variable in class org.tribuo.CategoricalInfo
The CDF to sample from.
centroids - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
 
centroids - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
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
 
checkIsBinary(Feature) - Static method in class org.tribuo.impl.BinaryFeaturesExample
 
checkpointPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
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
 
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
 
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 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.
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
 
className - Variable in class org.tribuo.provenance.ModelProvenance
 
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
 
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.
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.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_OUTPUT - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
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.
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
 
ClusteringMetrics - Enum 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
 
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, 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(int) - Method in class org.tribuo.math.la.DenseMatrix
Calculates the sum of the specified column.
columnSum() - Method in class org.tribuo.math.la.DenseMatrix
Returns the dense vector containing each column sum.
combine(ImmutableOutputInfo<Label>, List<Prediction<Label>>) - Method in class org.tribuo.classification.ensemble.FullyWeightedVotingCombiner
 
combine(ImmutableOutputInfo<Label>, List<Prediction<Label>>, float[]) - 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.VotingCombiner
 
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.
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
 
combiner - Variable in class org.tribuo.ensemble.BaggingTrainer
 
combiner - Variable in class org.tribuo.ensemble.WeightedEnsembleModel
 
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
 
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.
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(C) - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
Compute the result of this metric from the input context.
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.
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(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(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(WeightedTripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
 
conditionalMI(TripleDistribution<T1, T2, T3>, Map<?, Double>, WeightedInformationTheory.VariableSelector) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
 
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
 
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() - Constructor for class org.tribuo.classification.experiments.ConfigurableTrainTest
 
ConfigurableTrainTest - Class in org.tribuo.data
Build and run a predictor for a standard dataset.
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(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.
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
 
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
 
connString - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
 
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<T3>) - Static method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
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>, List<Double>) - Static method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
constructFromMap(Map<CachedPair<T1, T2>, MutableLong>) - Static method in class org.tribuo.util.infotheory.impl.PairDistribution
 
constructFromMap(Map<CachedPair<T1, T2>, MutableLong>, int, int) - Static method in class org.tribuo.util.infotheory.impl.PairDistribution
 
constructFromMap(Map<CachedPair<T1, T2>, MutableLong>, Map<T1, MutableLong>, Map<T2, MutableLong>) - Static method in class org.tribuo.util.infotheory.impl.PairDistribution
 
constructFromMap(Map<CachedTriple<T1, T2, T3>, MutableLong>) - Static method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
constructFromMap(Map<CachedTriple<T1, T2, T3>, MutableLong>, int, int, int, int, int, int) - Static method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
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
 
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>, WeightCountTuple>) - Static method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
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<T, Integer>) - Method in interface org.tribuo.OutputFactory
Creates an ImmutableOutputInfo from the supplied mapping.
constructInfoForExternalModel(Map<Regressor, Integer>) - Method in class org.tribuo.regression.RegressionFactory
 
contains(int) - Method in class org.tribuo.impl.IndexedArrayExample
Does this example contain a feature with id i.
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?
contains(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
 
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(Model<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelMetric.Context
 
Context(SequenceModel<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelMetric.Context
 
convert(SequenceExample<T>, ImmutableFeatureMap) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
convert(SequenceExample<Label>, ImmutableFeatureMap, ImmutableOutputInfo<Label>) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
convert(byte) - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType
Converts the byte into the enum.
convert(Example<?>, ImmutableFeatureMap) - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
convert(List<? extends Example<?>>, ImmutableFeatureMap) - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
convert(SGDVector) - Method in class org.tribuo.interop.tensorflow.DenseFeatureConverter
 
convert(List<? extends SGDVector>) - 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(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(SGDVector) - Method in interface org.tribuo.interop.tensorflow.FeatureConverter
Converts a SGDVector representing the features into a TensorMap.
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(Example<?>, ImmutableFeatureMap) - Method in class org.tribuo.interop.tensorflow.ImageConverter
Transform implicitly pads unseen values with zero.
convert(List<? extends 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.ImageConverter
 
convert(List<? extends SGDVector>) - Method in class org.tribuo.interop.tensorflow.ImageConverter
 
convertBatchOutput(ImmutableOutputInfo<Label>, List<float[][]>, int[], Example<Label>[]) - Method in class org.tribuo.classification.xgboost.XGBoostClassificationConverter
 
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.
convertBatchOutput(ImmutableOutputInfo<Regressor>, List<float[][]>, int[], Example<Regressor>[]) - Method in class org.tribuo.regression.xgboost.XGBoostRegressionConverter
 
convertDataset(Dataset<T>, Function<T, Float>) - Static method in class org.tribuo.common.xgboost.XGBoostTrainer
 
convertDataset(Dataset<T>) - 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.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.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(ImmutableOutputInfo<Label>, List<float[]>, int, Example<Label>) - Method in class org.tribuo.classification.xgboost.XGBoostClassificationConverter
 
convertOutput(float[][], int, Example<T>) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
convertOutput(float[][], int[], List<Example<T>>) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
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(V, int, Example<T>) - Method in class org.tribuo.interop.ExternalModel
Converts the output of the external model into a Prediction.
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(List<OnnxValue>, int, Example<T>) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
Converts a tensor into a prediction.
convertOutput(List<OnnxValue>, int[], List<Example<T>>) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
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(Tensor, int[], List<Example<T>>) - Method in class org.tribuo.interop.tensorflow.TensorFlowFrozenExternalModel
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(TensorMap, int[], List<Example<T>>) - Method in class org.tribuo.interop.tensorflow.TensorFlowSavedModelExternalModel
Converts a tensor into a prediction.
convertOutput(ImmutableOutputInfo<Regressor>, List<float[]>, int, Example<Regressor>) - Method in class org.tribuo.regression.xgboost.XGBoostRegressionConverter
 
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<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor containing multiple outputs into a list of Outputs.
convertToBatchOutput(Tensor, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
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<T>, int[], List<Example<T>>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor containing multiple outputs into a list of Predictions.
convertToBatchPrediction(Tensor, ImmutableOutputInfo<Regressor>, int[], List<Example<Regressor>>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
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
 
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<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor into the specified output type.
convertToOutput(Tensor, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
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<T>, int, Example<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts a Tensor into a Prediction.
convertToPrediction(Tensor, ImmutableOutputInfo<Regressor>, int, Example<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToSparseVector(ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.multilabel.MultiLabel
Converts this MultiLabel into a SparseVector using the indices from the output info.
convertToTensor(Label, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToTensor(List<Example<Label>>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.tensorflow.LabelConverter
 
convertToTensor(MultiLabel, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToTensor(List<Example<MultiLabel>>, ImmutableOutputInfo<MultiLabel>) - Method in class org.tribuo.interop.tensorflow.MultiLabelConverter
 
convertToTensor(T, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.OutputConverter
Converts an Output into a Tensor representing it's output.
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(Regressor, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
convertToTensor(List<Example<Regressor>>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.tensorflow.RegressorConverter
 
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.
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.
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(String, ModelProvenance) - Method in class org.tribuo.anomaly.liblinear.LibLinearAnomalyModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyModel
 
copy() - Method in class org.tribuo.anomaly.MutableAnomalyInfo
 
copy() - Method in class org.tribuo.CategoricalIDInfo
 
copy() - Method in class org.tribuo.CategoricalInfo
 
copy(String, ModelProvenance) - Method in class org.tribuo.classification.baseline.DummyClassifierModel
 
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(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() - Method in class org.tribuo.classification.MutableLabelInfo
 
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() - Method in class org.tribuo.clustering.ClusterID
 
copy() - Method in class org.tribuo.clustering.ClusteringInfo
 
copy() - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
copy(String, ModelProvenance) - Method in class org.tribuo.clustering.kmeans.KMeansModel
 
copy() - Method in class org.tribuo.clustering.MutableClusteringInfo
 
copy(String, ModelProvenance) - Method in class org.tribuo.common.nearest.KNNModel
 
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(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) - 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.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() - 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(String, ModelProvenance) - Method in class org.tribuo.ensemble.EnsembleModel
 
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() - 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(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() - 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.DenseVector
 
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 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(String, ModelProvenance) - Method in class org.tribuo.Model
Copies a model, replacing it's provenance and name with the supplied values.
copy(String, ModelProvenance) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelModel
 
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(String, ModelProvenance) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDModel
 
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(String, ModelProvenance) - Method in class org.tribuo.regression.baseline.DummyRegressionModel
 
copy() - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.libsvm.LibSVMRegressionModel
 
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(String, ModelProvenance) - Method in class org.tribuo.regression.rtree.IndependentRegressionTreeModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.sgd.linear.LinearSGDModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.regression.slm.SparseLinearModel
 
copy() - Method in class org.tribuo.sequence.SequenceExample
Returns a deep copy of this SequenceExample.
copy() - Method in class org.tribuo.SparseModel
 
copy(String, ModelProvenance) - Method in class org.tribuo.transform.TransformedModel
 
copy() - Method in interface org.tribuo.VariableInfo
Returns a copy of this variable info.
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.
copyResourceToTmp(String) - Static method in class org.tribuo.tests.Resources
 
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 in org.tribuo.util.tokens.options
Tokenizer type.
coreTokenizerType - Variable in class org.tribuo.util.tokens.options.CoreTokenizerOptions
 
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
 
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
 
count - Variable in class org.tribuo.util.infotheory.impl.TripleDistribution
 
count - Variable in class org.tribuo.util.infotheory.impl.WeightCountTuple
 
count - Variable in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
 
count - Variable in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
countMap - Variable in class org.tribuo.regression.RegressionInfo
 
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(String) - Static method in class org.tribuo.classification.baseline.DummyClassifierTrainer
Creates a trainer which creates models which return a fixed label.
createConstantTrainer(double) - Static method in class org.tribuo.regression.baseline.DummyRegressionTrainer
Creates a trainer which create models which return a fixed value.
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(SequenceModel<Label>, List<List<Prediction<Label>>>) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluator
 
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<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(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(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(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(C, Map<MetricID<T>, Double>, EvaluationProvenance) - Method in class org.tribuo.evaluation.AbstractEvaluator
Create an evaluation for the given results
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
 
createEvaluation(C, Map<MetricID<T>, Double>, EvaluationProvenance) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
Create an evaluation for the given results
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(SequenceModel<Label>) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluator
 
createMetrics(Model<ClusterID>) - Method in class org.tribuo.clustering.evaluation.ClusteringEvaluator
 
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(Model<MultiLabel>) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluator
 
createMetrics(Model<Regressor>) - Method in class org.tribuo.regression.evaluation.RegressionEvaluator
 
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(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(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>, LinearParameters) - Method in class org.tribuo.classification.sgd.linear.LinearSGDTrainer
 
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(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(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Booster>, XGBoostOutputConverter<T>) - Method in class org.tribuo.common.xgboost.XGBoostTrainer
 
createModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<MultiLabel>, LinearParameters) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
 
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<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(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>, LinearParameters) - Method in class org.tribuo.regression.sgd.linear.LinearSGDTrainer
 
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.
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.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(Example<T>, ImmutableFeatureMap, boolean) - Static method in class org.tribuo.math.la.SparseVector
Builds a SparseVector from an Example.
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.
createSplitFunction(boolean) - Static method in class org.tribuo.util.tokens.impl.wordpiece.WordpieceBasicTokenizer
Creates a 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
 
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
 
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
 
CRFModel - Class in org.tribuo.classification.sgd.crf
An inference time model for a linear chain CRF trained using SGD.
CRFModel.ConfidenceType - Enum 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
 
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.
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(Path, 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) - 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(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(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.CSVDataSourceProvenance - Class in org.tribuo.data.csv
Provenance for CSVDataSource.
CSVDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.csv.CSVDataSource.CSVDataSourceProvenance
 
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(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.
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.
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
Provenance for CSVs loaded by CSVLoader.
CSVLoaderProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
 
csvQuoteChar - Variable in class org.tribuo.data.DataOptions
 
csvResponseName - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
csvResponseName - Variable in class org.tribuo.data.DataOptions
 
CSVSaver - Class in org.tribuo.data.csv
Saves a Dataset in CSV format suitable for loading by CSVLoader.
CSVSaver(char, char) - Constructor for class org.tribuo.data.csv.CSVSaver
Builds a CSV saver using the supplied separator and quote.
CSVSaver() - Constructor for class org.tribuo.data.csv.CSVSaver
Builds a CSV saver using the default separator and quote from CSVIterator.
cumulativeSum(double[]) - Static method in class org.tribuo.util.Util
Produces a cumulative sum array.
cumulativeSum(boolean[]) - Static method in class org.tribuo.util.Util
Produces a cumulative sum array.
currentRow - Variable in class org.tribuo.data.columnar.ColumnarIterator
 

D

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
 
data - Variable in class org.tribuo.sequence.SequenceDataset
The data in this data set.
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 in org.tribuo.data
The delimiters supported by CSV files in this options object.
DataOptions.InputFormat - Enum 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(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.Dataset
Creates a dataset.
Dataset(DataSource<T>) - Constructor for class org.tribuo.Dataset
Creates a dataset.
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
 
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
 
datasetName - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
DatasetProvenance - Class in org.tribuo.provenance
Base class for dataset provenance.
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, Dataset<T>) - Constructor for class org.tribuo.provenance.DatasetProvenance
 
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, SequenceDataset<T>) - Constructor for class org.tribuo.provenance.DatasetProvenance
 
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, String, boolean, boolean, int, int, int) - Constructor for class org.tribuo.provenance.DatasetProvenance
 
DatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.DatasetProvenance
 
datasetProvenance - Variable in class org.tribuo.provenance.ModelProvenance
 
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
 
dataSource - Variable in class org.tribuo.data.PreprocessAndSerialize.PreprocessAndSerializeOptions
 
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
 
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, DateTimeFormatter) - Constructor for class org.tribuo.data.columnar.extractors.DateExtractor
Deprecated.
dbConfig - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
 
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, 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.
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.
deepCopy() - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
 
deepCopy() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Returns a deep copy of this tree feature.
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
 
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.impl.TripleDistribution
 
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.InformationTheory
 
DEFAULT_MAP_SIZE - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
 
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
 
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_SIZE - Static variable in class org.tribuo.impl.BinaryFeaturesExample
 
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
 
DEFAULT_SPLIT_EXCEPTING_IN_DIGITS_CHARACTERS - Static variable in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer
 
DEFAULT_UNKNOWN_TOKEN - Static variable in class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
 
DEFAULT_WEIGHT - Static variable in class org.tribuo.Example
The default weight.
DEFAULT_WEIGHT - Static variable in class org.tribuo.sequence.SequenceExample
 
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
 
DefaultFeatureExtractor(int, int, boolean, boolean, boolean) - Constructor for class org.tribuo.classification.sequence.viterbi.DefaultFeatureExtractor
 
degree - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 
delimiter - Variable in class org.tribuo.data.DataOptions
 
DELTA - Static variable in class org.tribuo.math.la.VectorTuple
 
DemoOptions() - Constructor for class org.tribuo.util.infotheory.example.InformationTheoryDemo.DemoOptions
 
dense - Variable in class org.tribuo.MutableDataset
Denotes if this dataset contains implicit zeros or not.
dense - Variable in class org.tribuo.sequence.MutableSequenceDataset
 
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(List<SparseVector>) - Constructor for class org.tribuo.math.la.DenseSparseMatrix
 
DenseSparseMatrix(DenseSparseMatrix) - Constructor for class org.tribuo.math.la.DenseSparseMatrix
 
denseTrainTest() - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator
Makes a simple dataset for training and testing.
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() - Static method in class org.tribuo.classification.example.LabelledDataGenerator
 
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() - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
 
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() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
 
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(int) - Constructor for class org.tribuo.math.la.DenseVector
 
DenseVector(int, double) - Constructor for class org.tribuo.math.la.DenseVector
 
DenseVector(double[]) - Constructor for class org.tribuo.math.la.DenseVector
Does not defensively copy the input, used internally.
DenseVector(DenseVector) - Constructor for class org.tribuo.math.la.DenseVector
Copy constructor.
densify(FeatureMap) - Method in class org.tribuo.Example
Converts all implicit zeros into explicit zeros based on the supplied feature map.
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(FeatureMap) - 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() - 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(FeatureMap) - Method in class org.tribuo.sequence.SequenceExample
Converts all implicit zeros into explicit zeros based on the supplied feature map.
depth - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
depth - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
depth - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
depth - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
DESCRIPTION - Static variable in class org.tribuo.provenance.SimpleDataSourceProvenance
 
DescriptiveStats - Class in org.tribuo.evaluation
Descriptive statistics calculated across a list of doubles.
DescriptiveStats() - Constructor for class org.tribuo.evaluation.DescriptiveStats
 
DescriptiveStats(List<Double>) - Constructor for class org.tribuo.evaluation.DescriptiveStats
 
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.
dim1 - Variable in class org.tribuo.math.la.DenseMatrix
 
dim2 - Variable in class org.tribuo.math.la.DenseMatrix
 
dimensions - Variable in class org.tribuo.regression.impl.SkeletalIndependentRegressionModel
 
dimensions - Variable in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseModel
 
DimensionTuple(String, double, double) - Constructor for class org.tribuo.regression.Regressor.DimensionTuple
Creates a dimension tuple from the supplied name, value and variance.
DimensionTuple(String, double) - Constructor for class org.tribuo.regression.Regressor.DimensionTuple
Creates a dimension tuple from the supplied name and value.
directory - Variable in class org.tribuo.classification.experiments.RunAll.RunAllOptions
 
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(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(Path, OutputFactory<T>, TextFeatureExtractor<T>, DocumentPreprocessor...) - Constructor for class org.tribuo.data.text.DirectoryFileSource
 
DirectoryFileSource.DirectoryFileSourceProvenance - Class in org.tribuo.data.text
Provenance for DirectoryFileSource.
DirectoryFileSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.text.DirectoryFileSource.DirectoryFileSourceProvenance
 
distance - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
 
distance - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
distance(SGDVector, DoubleUnaryOperator, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
 
DISTANCE_DELTA - Static variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
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(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that divides each value by the operand.
DMatrixTuple(DMatrix, int[], Example<T>[]) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer.DMatrixTuple
 
DocumentPreprocessor - Interface in org.tribuo.data.text
An interface for things that can pre-process documents before they are broken into features.
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
 
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.
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.
DTYPE - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
 
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 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 in org.tribuo.regression.baseline
Types of dummy regression model.
DummyRegressionTrainerProvenance(DummyRegressionTrainer) - Constructor for class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
Constructs a provenance from the host.
DummyRegressionTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance
Deprecated.
Constructs a provenance from the marshalled form.

E

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
 
ElasticNetCDTrainer(double, double, long) - Constructor for class org.tribuo.regression.slm.ElasticNetCDTrainer
 
ElasticNetCDTrainer(double, double, double, int, boolean, long) - Constructor for class org.tribuo.regression.slm.ElasticNetCDTrainer
 
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
 
EmptyDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyDatasetProvenance
 
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
 
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
 
EmptyTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyTrainerProvenance
 
encode(SequenceExample<?>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceFeatureConverter
Encodes an example as a feed dict.
encode(List<? extends SequenceExample<?>>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceFeatureConverter
Encodes a batch of examples 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.
encode(List<SequenceExample<T>>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceOutputConverter
Encodes a batch of labels as a feed dict.
end - Variable in class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
 
end - Variable in class org.tribuo.util.tokens.Token
 
end - Variable in class org.tribuo.util.tokens.universal.Range
 
ensemble - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
 
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
 
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>, 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>, 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(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
 
ensembleOptions - Variable in class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
 
ensembleOptions - Variable in class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
 
ensembleOptions - Variable in class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
 
ensembleOptions - Variable in class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
 
ensembleSize - Variable in class org.tribuo.classification.ensemble.ClassificationEnsembleOptions
 
ensembleSize - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
ensembleSize - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
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(List<T>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon entropy, using histogram probability estimators.
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
 
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
 
epochs - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
epsilon - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
epsilon - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
 
epsilon - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
 
EPSILON - Static variable in class org.tribuo.transform.transformations.SimpleTransform
 
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 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
 
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.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 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
 
eta - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
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
 
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>, 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>, 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() - Method in class org.tribuo.evaluation.CrossValidation
Performs k fold cross validation, returning the k evaluations.
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 interface org.tribuo.evaluation.Evaluator
Evaluates the dataset using the supplied model, returning an immutable Evaluation of the appropriate type.
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>, 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() - Method in class org.tribuo.evaluation.OnlineEvaluator
Creates an Evaluation containing all the current predictions.
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>, 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>, 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>, 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 interface org.tribuo.sequence.SequenceEvaluator
Evaluates the datasource using the supplied model, returning an immutable evaluation.
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.
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 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(ModelProvenance, DataProvenance) - Constructor for class org.tribuo.provenance.EvaluationProvenance
 
EvaluationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.EvaluationProvenance
 
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.
Event - Class in org.tribuo.anomaly
An Output representing either an Event.EventType.ANOMALOUS or an Event.EventType.EXPECTED event.
Event(Event.EventType, double) - Constructor for class org.tribuo.anomaly.Event
Constructs a new event of the specified type and score.
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.EventType - Enum in org.tribuo.anomaly
The type of event.
Example<T extends Output<T>> - Class in org.tribuo
An example used for training and evaluation.
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, float) - Constructor for class org.tribuo.Example
Construct an empty example using the supplied output and weight.
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.
Example(T) - Constructor for class org.tribuo.Example
Construct an empty example using the supplied output and Example.DEFAULT_WEIGHT as the weight.
Example(Example<T>) - Constructor for class org.tribuo.Example
Copies the output, weight and metadata into this example.
ExampleArray(SparseVector[], int[], double[]) - Constructor for class org.tribuo.classification.sgd.Util.ExampleArray
 
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<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.
excuse(String) - Method in class org.tribuo.Excuse
Returns the features involved in this excuse.
exp() - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that applies Math.exp(double).
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.
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(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.
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(Map<String, String>) - Method in interface org.tribuo.classification.explanations.ColumnarExplainer
Explains the supplied data.
explain(Example<Label>) - Method in class org.tribuo.classification.explanations.lime.LIMEBase
 
explain(Map<String, String>) - Method in class org.tribuo.classification.explanations.lime.LIMEColumnar
 
explain(String) - Method in class org.tribuo.classification.explanations.lime.LIMEText
 
explain(CommandInterpreter, String[]) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
explain(Example<Label>) - Method in interface org.tribuo.classification.explanations.TabularExplainer
Explain why the supplied Example is classified a certain way.
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.
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() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculatest the explained variance for all dimensions.
explainedVariance(MetricTarget<Regressor>, RegressionSufficientStatistics) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Calculates the explained variance based on the supplied statistics.
explainedVariance(Regressor, RegressionSufficientStatistics) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Calculates the explained variance based on the supplied statistics for a single dimension.
explainWithSamples(Example<Label>) - Method in class org.tribuo.classification.explanations.lime.LIMEBase
 
explainWithSamples(Map<String, String>) - Method in class org.tribuo.classification.explanations.lime.LIMEColumnar
 
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
 
exportModel(String) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Exports this model as a SavedModelBundle, writing to the supplied directory.
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
 
ExternalDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.interop.ExternalDatasetProvenance
 
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
 
ExternalModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, int[], int[], boolean) - Constructor for class org.tribuo.interop.ExternalModel
 
externalPrediction(DMatrix) - Method in class org.tribuo.common.xgboost.XGBoostExternalModel
 
externalPrediction(U) - Method in class org.tribuo.interop.ExternalModel
Runs the external model's prediction function.
externalPrediction(OnnxTensor) - Method in class org.tribuo.interop.onnx.ONNXExternalModel
Runs the session to make a prediction.
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.
ExternalTrainerProvenance - Class in org.tribuo.interop
A dummy provenance for a model trained outside Tribuo.
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(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(Map<String, Provenance>) - Constructor for class org.tribuo.interop.ExternalTrainerProvenance
Used by the provenance serialization system.
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<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.
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
 
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.data.csv.CSVDataSource.CSVDataSourceProvenance
 
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
 
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
 
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
 
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
 
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

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(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Computes the F_1 score.
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
 
f1(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
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
 
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 - Interface in org.tribuo.interop.tensorflow
Transforms an Example or SGDVector, extracting the features from it as a TensorMap.
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
 
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
 
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
 
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.data.DatasetExplorer
 
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
 
featureIterator() - Method in class org.tribuo.sequence.SequenceExample
Creates an iterator over every feature in this sequence.
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(FeatureMap) - Constructor for class org.tribuo.FeatureMap
Constructs a deep copy of the supplied feature map.
FeatureMap(Map<String, ? extends VariableInfo>) - Constructor for class org.tribuo.FeatureMap
Constructs a feature map wrapping the supplied map.
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.
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
 
featureNames - Variable in class org.tribuo.impl.BinaryFeaturesExample
 
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
 
features - Variable in class org.tribuo.classification.sgd.Util.SequenceExampleArray
 
FEATURES_FILE_MODIFIED_TIME - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
 
FEATURES_RESOURCE_HASH - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
 
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
 
FeatureTuple(String, int, double) - Constructor for class org.tribuo.impl.IndexedArrayExample.FeatureTuple
 
featureValues - Variable in class org.tribuo.impl.ArrayExample
 
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
 
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 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 in a given field.
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.
fields - Variable in class org.tribuo.data.columnar.ColumnarIterator
 
FILE_MODIFIED_TIME - Static variable in interface org.tribuo.provenance.DataSourceProvenance
 
fileCompleter() - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
fileCompleter() - Method in class org.tribuo.data.DatasetExplorer
 
fileCompleter() - Method in class org.tribuo.ModelExplorer
Completers for files.
fileCompleter() - Method in class org.tribuo.sequence.SequenceModelExplorer
 
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.
fill(double) - Method in class org.tribuo.math.la.DenseVector
Fills this DenseVector with value.
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.
firstCount - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
 
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
 
fixSize() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Fixes the size of each InvertedFeature's inner arrays.
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.
fmix32(int) - Static method in class org.tribuo.util.MurmurHash3
 
fmix64(long) - Static method in class org.tribuo.util.MurmurHash3
 
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() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the micro averaged number of false negatives.
fn(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of false negatives for the supplied label.
fn() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of false negatives.
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(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
fn(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
fn() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
fn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
fn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
fn() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
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
 
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.
forTarget(MetricTarget<Label>) - Method in enum org.tribuo.classification.evaluation.LabelMetrics
Gets the LabelMetric wrapped around the supplied MetricTarget.
forTarget(MetricTarget<ClusterID>) - Method in enum org.tribuo.clustering.evaluation.ClusteringMetrics
 
forTarget(MetricTarget<MultiLabel>) - Method in enum org.tribuo.multilabel.evaluation.MultiLabelMetrics
Get the metric for the supplied target.
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() - 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(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of false positives for the supplied label.
fp() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of false positives.
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(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
fp(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
fp() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
fp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
fp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
fp() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
fpr - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.ROC
 
fraction - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
fractionFeaturesInSplit - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
Number of features to sample per split.
frequencyBasedSample(SplittableRandom, long) - Method in class org.tribuo.CategoricalInfo
Samples a value from this feature according to the frequency of observation.
frequencyBasedSample(Random, 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.
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(T) - Method in interface org.tribuo.Output
Compares other to this output.
fullEquals(Regressor) - Method in class org.tribuo.regression.Regressor.DimensionTuple
 
fullEquals(Regressor) - Method in class org.tribuo.regression.Regressor
 
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

gamma - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 
gamma - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
gamma - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
gatherAcrossDim1(int[]) - Method in class org.tribuo.math.la.DenseMatrix
 
gatherAcrossDim2(int[]) - Method in class org.tribuo.math.la.DenseMatrix
 
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.
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.
general - Variable in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
general - Variable in class org.tribuo.classification.experiments.RunAll.RunAllOptions
 
general - Variable in class org.tribuo.classification.experiments.TrainTest.AllClassificationOptions
 
general - Variable in class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
 
general - Variable in class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
 
general - Variable in class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
 
general - Variable in class org.tribuo.classification.sgd.kernel.TrainTest.TrainTestOptions
 
general - Variable in class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
 
general - Variable in class org.tribuo.classification.xgboost.TrainTest.TrainTestOptions
 
general - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
general - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
general - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
 
general - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 
general - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
general - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
general - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
 
general - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
generalOptions - Variable in class org.tribuo.classification.dtree.TrainTest.TrainTestOptions
 
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
 
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).
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).
generateEmptyExample() - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
This generates a sequence example with no examples.
generateExample(ColumnarIterator.Row, 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(long, Map<String, String>, 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.
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
 
generateGorillaB() - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
 
generateGorillaDataset(int) - Static method in class org.tribuo.classification.sequence.example.SequenceDataGenerator
 
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(FeatureMap) - Static method in class org.tribuo.ImmutableFeatureMap
Generates the feature ids by sorting the features with the String comparator, then sequentially numbering them.
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.
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(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
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.onnx.LabelTransformer
 
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 - Variable in class org.tribuo.Model
Does this model generate probability distributions in the output.
generatesProbabilities() - Method in class org.tribuo.Model
Does this model generate probabilistic predictions.
generatesProbabilities(CommandInterpreter) - Method in class org.tribuo.ModelExplorer
Checks if the model generates probabilities.
generatesProbabilities() - Method in class org.tribuo.regression.xgboost.XGBoostRegressionConverter
 
generateTestData() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator
 
generateTrainData() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator
 
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
 
generateUniformVector(int, double) - Static method in class org.tribuo.util.Util
 
generateUniformVector(int, float) - Static method in class org.tribuo.util.Util
 
generateWeightedIndicesSample(int, double[], Random) - 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, double[], SplittableRandom) - 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(MetricID<T>) - Method in interface org.tribuo.evaluation.Evaluation
Gets the value associated with the specific metric.
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(int) - Method in class org.tribuo.ImmutableFeatureMap
Gets the VariableIDInfo for this id number.
get(String) - Method in class org.tribuo.ImmutableFeatureMap
Gets the VariableIDInfo for this name.
get(int, int) - Method in class org.tribuo.math.la.DenseMatrix
 
get(int, int) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
get(int) - Method in class org.tribuo.math.la.DenseVector
 
get(int, int) - Method in interface org.tribuo.math.la.Matrix
Gets an element from this Matrix.
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() - Method in class org.tribuo.math.LinearParameters
 
get(int, int) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
get(int) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
 
get() - Method in interface org.tribuo.math.Parameters
Get a reference to the underlying Tensor array.
get(MetricID<MultiLabel>) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
get(MetricID<T>) - Method in interface org.tribuo.sequence.SequenceEvaluation
Gets the value associated with the specific metric.
get(int) - Method in class org.tribuo.sequence.SequenceExample
Gets the example found at the specified index.
get(String) - Method in class org.tribuo.transform.TransformerMap
Gets the transformer associated with a given feature name.
get(int) - Method in class org.tribuo.util.infotheory.impl.RowList
 
getA() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
 
getAB() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
 
getABCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
getABCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
getAC() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
 
getACCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
getACCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
getACount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
getACount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
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.
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.
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
 
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
 
getBCCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
getBCCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
getBCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
getBCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
getBias(int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Returns the bias for the specified label id.
getC() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
 
getCCount() - Method in class org.tribuo.util.infotheory.impl.TripleDistribution
 
getCCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
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
 
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.
getCM() - Method in class org.tribuo.classification.evaluation.LabelMetric.Context
 
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.
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(int) - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Cover measures the number of examples a given feature discriminates across, relative to the total.
getCover() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The number of examples a feature discriminates between.
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.
getDatasetProvenance() - Method in class org.tribuo.provenance.ModelProvenance
The training dataset provenance.
getDataType() - Method in class org.tribuo.datasource.IDXDataSource
The type of the features that were loaded in.
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
 
getDigestSupplier(String) - Static method in class org.tribuo.hash.MessageDigestHasher
Creates a supplier for the specified hash type.
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.
getDimension(int) - Method in class org.tribuo.regression.Regressor
Returns a dimension tuple for the requested dimension index.
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.linear.LinearSGDModel
 
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.linear.LinearSGDModel
 
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.
getDistribution() - Method in class org.tribuo.common.tree.LeafNode
Gets the distribution over scores in this node.
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.
getDropInvalidExamples() - Method in class org.tribuo.ImmutableDataset
Returns true if this immutable dataset dropped any invalid examples on construction.
getEmptyCopy() - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Returns a 3 element Tensor array.
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 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(int) - Method in class org.tribuo.dataset.DatasetView
 
getExample(int) - Method in class org.tribuo.Dataset
Gets the example at the supplied index.
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.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.kmeans.KMeansModel
 
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.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<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.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.
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.
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
 
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.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(int) - Method in class org.tribuo.classification.sgd.crf.CRFModel
Get a copy of the weights for feature featureID.
getFeatureWeights(String) - Method in class org.tribuo.classification.sgd.crf.CRFModel
Get a copy of the weights for feature named featureName.
getFeatureWeights(int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Gets a copy of the weights for the specified label id.
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
 
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.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
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
getFieldName() - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
getFieldName() - Method in interface org.tribuo.data.columnar.ResponseProcessor
Gets the field name 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
 
getFirstCount() - Method in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
 
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.
getFractionFeaturesInSplit() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
getFractionFeaturesInSplit() - Method in interface org.tribuo.common.tree.DecisionTreeTrainer
Returns the feature subsampling rate.
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(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.
getGain() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The information gain a feature provides when split on.
getGamma() - Method in class org.tribuo.common.libsvm.SVMParameters
 
getGlobalTransformations() - Method in class org.tribuo.transform.TransformationMap
Gets the global transformations in this TransformationMap.
getGradientParams() - Method in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
Zips the gradient parameter names and values.
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.
getID() - Method in enum org.tribuo.anomaly.Event.EventType
Returns the id of the event.
getID(Event) - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
getID() - Method in class org.tribuo.CategoricalIDInfo
 
getID(Label) - Method in class org.tribuo.classification.ImmutableLabelInfo
 
getID() - Method in class org.tribuo.clustering.ClusterID
Gets the cluster id number.
getID(ClusterID) - Method in class org.tribuo.clustering.ImmutableClusteringInfo
 
getID() - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric
The metric ID, a combination of the metric target and metric name.
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(T) - Method in interface org.tribuo.ImmutableOutputInfo
Return the id number associated with this output, or -1 if the output is unknown.
getID(MultiLabel) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
 
getID(String) - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
Gets the id for the supplied label string.
getID() - Method in class org.tribuo.RealIDInfo
 
getID(Regressor) - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
getID() - Method in interface org.tribuo.VariableIDInfo
The id number associated with this variable.
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 org.tribuo.classification.evaluation.LabelMetrics
Returns the implementing function for this metric.
getImpl() - Method in enum org.tribuo.clustering.evaluation.ClusteringMetrics
 
getImpl() - Method in enum 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
 
getInnerExcuses() - Method in class org.tribuo.ensemble.EnsembleExcuse
The individual ensemble member's excuses.
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.
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
 
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.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.IndependentMultiLabelTrainer
 
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
 
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
 
getJointCount() - Method in class org.tribuo.util.infotheory.impl.WeightedTripleDistribution
 
getJointCounts() - Method in class org.tribuo.util.infotheory.impl.WeightedPairDistribution
 
getK() - Method in class org.tribuo.evaluation.CrossValidation
Returns the number of folds.
getKernelType(int) - Static method in enum org.tribuo.common.libsvm.KernelType
Converts the LibSVM int id into the enum value.
getKernelType() - Method in class org.tribuo.common.libsvm.SVMParameters
 
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(Label) - 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.classification.LabelInfo
Gets the count of the supplied label, or 0 if the label is unknown.
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(Label) - Method in class org.tribuo.multilabel.MultiLabelInfo
Get the number of times this Label was observed, or 0 if unknown.
getLabelCount(String) - Method in class org.tribuo.multilabel.MultiLabelInfo
Get the number of times this String was observed, or 0 if unknown.
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.
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.linear.LinearSGDOptions
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.
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(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.
getMax() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the maximum observed value.
getMaxDepth() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
 
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
 
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(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.
getMean() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the sample mean.
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.
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(String) - Method in class org.tribuo.regression.RegressionInfo
Gets the minimum value this RegressionInfo has seen, or NaN if it's not seen anything.
getMin() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the minimum observed value.
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
 
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.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.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.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.
getN() - Method in class org.tribuo.evaluation.DescriptiveStats
Returns the number of values.
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.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 interface org.tribuo.VariableInfo
The name of this feature.
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 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.
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.
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.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.linear.LinearSGDTrainer
 
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.
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.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.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.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.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
 
getOS() - Method in class org.tribuo.provenance.ModelProvenance
The name of the OS used to create this model.
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() - 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(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() - Method in class org.tribuo.Prediction
Returns the predicted output.
getOutput(int) - Method in class org.tribuo.regression.ImmutableRegressionInfo
 
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.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.
getOutputName() - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
Gets the name of the output operation.
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 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
 
getPos() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
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(int, Example<T>) - Method in class org.tribuo.common.tree.LeafNode
Constructs a new prediction object based on this node's scores.
getPrediction() - Method in class org.tribuo.Excuse
Returns the prediction being excused.
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
 
getProvenance() - Method in class org.tribuo.anomaly.AnomalyFactory
 
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.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.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.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.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.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.IndependentMultiLabelTrainer
 
getProvenance() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
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
 
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.
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.
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.
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
Extract a row as an SGDVector.
getRowData() - Method in class org.tribuo.data.columnar.ColumnarIterator.Row
 
getScaledMinImpurityDecrease() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
 
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
 
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
 
getSecondFieldName() - Method in class org.tribuo.data.columnar.ColumnarFeature
If it's a conjunction feature, return the second field name.
getSequenceModel() - Method in class org.tribuo.evaluation.metrics.MetricContext
Gets the SequenceModel used by this context.
getSequenceTrainer(Trainer<Label>) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions
Creates a viterbi trainer wrapping the supplied label trainer.
getSequenceTrainer() - Method in class org.tribuo.classification.sgd.crf.CRFOptions
Returns the configured CRF trainer.
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
 
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.
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 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 org.tribuo.classification.liblinear.LinearClassificationType.LinearType
 
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 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.
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
 
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.
getSvmType() - Method in class org.tribuo.common.libsvm.SVMParameters
 
getTarget() - Method in class org.tribuo.anomaly.evaluation.AnomalyMetric
 
getTarget() - Method in class org.tribuo.classification.evaluation.LabelMetric
 
getTarget(ImmutableOutputInfo<Label>, Label) - Method in class org.tribuo.classification.sgd.linear.LinearSGDTrainer
 
getTarget() - Method in class org.tribuo.clustering.evaluation.ClusteringMetric
 
getTarget(ImmutableOutputInfo<T>, T) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
Extracts the appropriate training time representation from the supplied output.
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(ImmutableOutputInfo<MultiLabel>, MultiLabel) - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDTrainer
 
getTarget() - Method in class org.tribuo.regression.evaluation.RegressionMetric
 
getTarget(ImmutableOutputInfo<Regressor>, Regressor) - Method in class org.tribuo.regression.sgd.linear.LinearSGDTrainer
 
getTensor(String) - Method in class org.tribuo.interop.tensorflow.TensorMap
Returns the specified tensor if present.
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
 
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.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.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.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.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
 
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(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.
getTotalCover() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The total number of examples a feature discrimnates between.
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(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.
getTotalGain() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance.XGBoostFeatureImportanceInstance
The total gain across all times the feature is used to split.
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.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.kmeans.KMeansOptions
 
getTrainer() - Method in class org.tribuo.common.nearest.KNNClassifierOptions
 
getTrainer() - Method in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
getTrainer() - Method in class org.tribuo.regression.xgboost.XGBoostOptions
Gets the configured XGBoostRegressionTrainer.
getTrainerProvenance() - Method in class org.tribuo.provenance.ModelProvenance
The trainer provenance.
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.
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 org.tribuo.anomaly.Event
Gets the event 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
 
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
 
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.
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 org.tribuo.Feature
Returns the feature value.
getValue() - Method in class org.tribuo.regression.Regressor.DimensionTuple
Returns the value.
getValues() - Method in class org.tribuo.regression.Regressor
Returns the regression values.
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.
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(String) - Method in class org.tribuo.regression.RegressionInfo
Gets the variance this RegressionInfo has seen, or NaN if it's not seen that dimension.
getVariance() - Method in class org.tribuo.regression.Regressor.DimensionTuple
Returns the variance.
getVariance() - Method in class org.tribuo.util.MeanVarianceAccumulator
Gets the sample variance.
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.
getVocab() - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Returns the vocabulary that this BERTFeatureExtractor understands.
getWeight(int, int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Returns the feature/label weight for the specified feature and label id.
getWeight() - Method in class org.tribuo.common.xgboost.XGBoostFeatureImportance
Weight measures the number a times a feature occurs in the model.
getWeight(int) - 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.
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
 
GiniIndex - Class in org.tribuo.classification.dtree.impurity
The Gini index impurity measure.
GiniIndex() - Constructor for class org.tribuo.classification.dtree.impurity.GiniIndex
 
GradientOptimiser - Enum 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 in org.tribuo.math.optimisers
Type of the gradient optimisers available in CLIs.
gradientOptions - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
gradientOptions - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
gradientParamNames - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
gradientParamValues - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
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_HASH - Static variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance
 
GRAPH_HASH - Static variable in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
 
GRAPH_LAST_MOD - Static variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer.TensorFlowSequenceTrainerProvenance
 
GRAPH_LAST_MOD - Static variable in class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
 
graphDef - Variable in class org.tribuo.interop.tensorflow.example.GraphDefTuple
 
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
 
greaterThan - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
grow(int) - Method in class org.tribuo.common.tree.impl.IntArrayContainer
Grows the backing array, copying the elements.
growArray(int) - Method in class org.tribuo.impl.ArrayExample
Grows the backing arrays storing the names and values.
growArray() - Method in class org.tribuo.impl.ArrayExample
Grows the backing arrays by size+1.
growArray(int) - Method in class org.tribuo.impl.BinaryFeaturesExample
Grows the backing arrays storing the names.
growArray() - Method in class org.tribuo.impl.BinaryFeaturesExample
Grows the backing arrays by size+1.
growArray(int) - Method in class org.tribuo.impl.IndexedArrayExample
 
gStatistic - Variable in class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
 
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
 

H

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.
hadamardProductInPlace(Tensor) - Method in interface org.tribuo.math.la.Tensor
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.
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 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
 
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.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 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
 
HashCodeHasher.HashCodeHasherProvenance - Class in org.tribuo.hash
Provenance for the HashCodeHasher.
HashCodeHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
 
hashDim - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
hashDim - Variable in class org.tribuo.data.DataOptions
 
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
 
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 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
 
HashingSequenceTrainer.HashingSequenceTrainerProvenance - Class in org.tribuo.sequence
Provenance for HashingSequenceTrainer.
HashingSequenceTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.sequence.HashingSequenceTrainer.HashingSequenceTrainerProvenance
 
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
 
hashType - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
 
hasNext() - Method in class org.tribuo.data.columnar.ColumnarIterator
 
hasProbabilities() - Method in class org.tribuo.Prediction
Are the scores probabilities?
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(double) - Constructor for class org.tribuo.classification.sgd.objectives.Hinge
Construct a hinge objective with the supplied margin.
Hinge() - Constructor for class org.tribuo.classification.sgd.objectives.Hinge
Construct a hinge objective with a margin of 1.0.
Hinge - Class in org.tribuo.multilabel.sgd.objectives
Hinge loss, scores the correct value margin and any incorrect predictions -margin.
Hinge(double) - Constructor for class org.tribuo.multilabel.sgd.objectives.Hinge
Construct a hinge objective with the supplied margin.
Hinge() - Constructor for class org.tribuo.multilabel.sgd.objectives.Hinge
Construct a hinge objective with a margin of 1.0.
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.

I

i - Variable in class org.tribuo.math.la.MatrixTuple
 
id - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple
 
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
 
IDFTransformation.IDFTransformationProvenance - Class in org.tribuo.transform.transformations
Provenance for IDFTransformation.
IDFTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.IDFTransformation.IDFTransformationProvenance
 
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 in org.tribuo.datasource
The possible IDX input formats.
IDXDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
 
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
 
ImageTransformer - Class in org.tribuo.interop.onnx
Image transformer.
ImageTransformer(int, int, int) - Constructor for class org.tribuo.interop.onnx.ImageTransformer
 
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
 
ImmutableClusteringInfo(ClusteringInfo) - Constructor for class org.tribuo.clustering.ImmutableClusteringInfo
 
ImmutableDataset<T extends Output<T>> - Class in org.tribuo
This is a Dataset which has an ImmutableFeatureMap to store the feature information.
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(DataSource<T>, Model<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(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(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(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.
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() - Constructor for class org.tribuo.ImmutableFeatureMap
Constructs a new empty immutable feature map.
ImmutableLabelInfo - Class in org.tribuo.classification
An ImmutableOutputInfo object for Labels.
ImmutableMultiLabelInfo - Class in org.tribuo.multilabel
An ImmutableOutputInfo for working with multi-label 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(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>, SequenceModel<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
 
ImmutableSequenceDataset(SequenceDataSource<T>, FeatureMap, OutputInfo<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
 
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.
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(int[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Calculates the impurity assuming the input are counts.
impurity(Map<String, Double>) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity
Takes a Map for weighted 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[], 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(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(IntArrayContainer, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity
Calculates the weighted impurity of the targets specified in the indices container.
impurity - Variable in class org.tribuo.regression.rtree.impurity.RegressorImpurity.ImpurityTuple
 
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(List<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(List<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 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
 
impurityType - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
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
 
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
 
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
 
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(IndexedArrayExample<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample
Copy constructor.
IndexedArrayExample(Example<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample
This constructor removes unknown features.
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(String) - Constructor for class org.tribuo.data.columnar.extractors.IndexExtractor
Extracts the index, writing to the supplied metadata field name.
IndexExtractor() - Constructor for class org.tribuo.data.columnar.extractors.IndexExtractor
Extracts the index writing to the default metadata field name Example.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
 
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 in org.tribuo.util.infotheory.example
Type of data distribution.
initialisation - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
 
initialisation - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
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.
initialize() - Method in class org.tribuo.interop.tensorflow.TensorFlowCheckpointModel
Initializes the model.
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<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.
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.
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).
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
 
inPlaceAdd(float[], float[]) - Static method in class org.tribuo.util.Util
 
inplaceNormalizeToDistribution(double[]) - Static method in class org.tribuo.util.Util
 
inplaceNormalizeToDistribution(float[]) - Static method in class org.tribuo.util.Util
 
inPlaceSubtract(double[], double[]) - Static method in class org.tribuo.util.Util
 
inPlaceSubtract(float[], float[]) - Static method in class org.tribuo.util.Util
 
INPUT_IDS - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
inputFile - Variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.BERTFeatureExtractorOptions
 
inputFormat - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
inputFormat - Variable in class org.tribuo.data.DataOptions
 
inputModel - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
 
inputName - Variable in class org.tribuo.interop.tensorflow.example.GraphDefTuple
 
inputName - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
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
 
inputPath - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
 
inputType - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
INSTANCE_VALUES - Static variable in class org.tribuo.provenance.ModelProvenance
 
instanceProvenance - Variable in class org.tribuo.provenance.ModelProvenance
 
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.
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, 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) - Method in interface org.tribuo.math.la.Tensor
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.
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
 
InvertedFeature(double, int) - Constructor for class org.tribuo.regression.rtree.impl.InvertedFeature
 
IS_SEQUENCE - Static variable in interface org.tribuo.provenance.TrainerProvenance
 
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
 
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(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() - 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.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
 
isGenerateUnigrams() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
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.
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 - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
iterations - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
 
iterator() - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
 
iterator() - Method in class org.tribuo.classification.ImmutableLabelInfo
 
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
 
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.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
 
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 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
 
jointCounts - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
 
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.
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.
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(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(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(WeightedTripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
 
jointMI(TripleDistribution<T1, T2, T3>, Map<?, Double>, WeightedInformationTheory.VariableSelector) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
 
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(Path, RowProcessor<T>, boolean) - Constructor for class org.tribuo.json.JsonDataSource
Creates a JsonDataSource using the specified RowProcessor to process the data.
JsonDataSource(URI, 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
 
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

Kernel - Interface in org.tribuo.math.kernel
An interface for a Mercer kernel function.
kernelDegree - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
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
 
kernelGamma - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
kernelIntercept - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
kernelKernel - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
kernelLambda - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
kernelLoggingInterval - Variable in class org.tribuo.classification.sgd.kernel.KernelSVMOptions
 
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
 
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 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 - Enum in org.tribuo.common.libsvm
Kernel types from libsvm.
kernelType - Variable in class org.tribuo.common.libsvm.SVMParameters
 
kernelType - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 
kernelWidth - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
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, long) - Constructor for class org.tribuo.evaluation.KFoldSplitter
Builds a k-fold splitter.
KFoldSplitter(int) - Constructor for class org.tribuo.evaluation.KFoldSplitter
Builds a k-fold splitter using Trainer.DEFAULT_SEED as the seed.
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 in org.tribuo.clustering.kmeans
Possible distance functions.
KMeansTrainer.Initialisation - Enum in org.tribuo.clustering.kmeans
Possible initialization functions.
knnBackend - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
 
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 in org.tribuo.common.nearest
The type of combination function.
knnDistance - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
 
knnEnsembleCombiner - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
 
knnK - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
 
KNNModel<T extends Output<T>> - Class in org.tribuo.common.nearest
A k-nearest neighbours model.
KNNModel.Backend - Enum in org.tribuo.common.nearest
The parallel backend for batch predictions.
knnNumThreads - Variable in class org.tribuo.common.nearest.KNNClassifierOptions
 
knnOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
 
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 in org.tribuo.common.nearest
The available distance functions.

L

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
 
l1Ratio - Variable in class org.tribuo.regression.slm.TrainTest.SLMOptions
 
l2Distance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector
Synonym for euclideanDistance.
Label - Class in org.tribuo.classification
An immutable multi-class classification label.
Label(String, double) - Constructor for class org.tribuo.classification.Label
Builds a label with the supplied string and score.
Label(String) - Constructor for class org.tribuo.classification.Label
Builds a label with the sentinel score of Double.NaN.
label - Variable in class org.tribuo.classification.Label
The name of the label.
LabelConfusionMatrix - Class in org.tribuo.classification.evaluation
A confusion matrix for Labels.
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.
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.
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 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.
labels - Variable in class org.tribuo.classification.LabelInfo
The label domain.
labels - Variable in class org.tribuo.classification.sgd.crf.Chunk
 
labels - Variable in class org.tribuo.classification.sgd.Util.ExampleArray
 
labels - Variable in class org.tribuo.classification.sgd.Util.SequenceExampleArray
 
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
 
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
 
lambda - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
 
lambda - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
lambda - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
languageTag - Variable in class org.tribuo.util.tokens.options.BreakIteratorTokenizerOptions
 
LARSLassoTrainer - Class in org.tribuo.regression.slm
A trainer for a lasso linear regression model which uses LARS to construct the model.
LARSLassoTrainer(int) - Constructor for class org.tribuo.regression.slm.LARSLassoTrainer
Constructs a lasso LARS trainer for a linear model.
LARSLassoTrainer() - Constructor for class org.tribuo.regression.slm.LARSLassoTrainer
Constructs a lasso LARS trainer that selects all the features.
LARSTrainer - Class in org.tribuo.regression.slm
A trainer for a linear regression model which uses least angle regression.
LARSTrainer(int) - Constructor for class org.tribuo.regression.slm.LARSTrainer
Constructs a least angle regression trainer for a linear model.
LARSTrainer() - Constructor for class org.tribuo.regression.slm.LARSTrainer
Constructs a least angle regression trainer that selects all the features.
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
 
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
 
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
 
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
 
lessThanOrEqual - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
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
 
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 - Variable in class org.tribuo.classification.liblinear.TrainTest.TrainTestOptions
 
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.
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(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(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.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
 
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 - Variable in class org.tribuo.classification.libsvm.TrainTest.TrainTestOptions
 
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
 
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
 
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).
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 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
 
LinearClassificationType.LinearType - Enum 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
 
LinearRegressionType.LinearType - Enum 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
 
LinearScalingTransformation.LinearScalingTransformationProvenance - Class in org.tribuo.transform.transformations
LinearScalingTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
 
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
 
LinearSGDOptions - Class in org.tribuo.classification.sgd.linear
CLI options for training a linear classifier.
LinearSGDOptions() - Constructor for class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
LinearSGDOptions - Class in org.tribuo.multilabel.sgd.linear
CLI options for training a linear classifier.
LinearSGDOptions() - Constructor for class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
LinearSGDOptions.LossEnum - Enum in org.tribuo.classification.sgd.linear
Available loss types.
LinearSGDOptions.LossEnum - Enum 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(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 - Class in org.tribuo.multilabel.sgd.linear
A trainer for a multi-label linear model which uses SGD.
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 - Class in org.tribuo.regression.sgd.linear
A trainer for a linear regression model which uses SGD.
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
 
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
 
ListExample<T extends Output<T>> - Class in org.tribuo.impl
This class will not be performant until value types are available in Java.
ListExample(T, float) - Constructor for class org.tribuo.impl.ListExample
 
ListExample(T) - Constructor for class org.tribuo.impl.ListExample
 
ListExample(Example<T>) - Constructor for class org.tribuo.impl.ListExample
 
ListExample(T, List<? extends Feature>) - Constructor for class org.tribuo.impl.ListExample
 
ListExample(T, String[], double[]) - Constructor for class org.tribuo.impl.ListExample
 
listIterator() - Method in class org.tribuo.util.infotheory.impl.RowList
 
listIterator(int) - Method in class org.tribuo.util.infotheory.impl.RowList
 
load(Test.ConfigurableTestOptions) - Static method in class org.tribuo.classification.experiments.Test
 
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(OutputFactory<T>) - Method in class org.tribuo.data.DataOptions
 
loadDataset(CommandInterpreter, File) - Method in class org.tribuo.data.DatasetExplorer
 
loadDataSource(Path, String) - Method in class org.tribuo.data.csv.CSVLoader
Loads a DataSource from the specified csv path.
loadDataSource(URL, 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(URL, 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(URL, 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.
loadDataSource(URL, 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
 
loadModel(CommandInterpreter, File) - Method in class org.tribuo.ModelExplorer
Loads a model.
loadModel(CommandInterpreter, File) - Method in class org.tribuo.sequence.SequenceModelExplorer
 
localValues - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainCliqueValues
 
log() - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that applies Math.log(double).
LOG_2 - Static variable in class org.tribuo.util.infotheory.InformationTheory
 
LOG_2 - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
 
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_E - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
 
loggingInterval - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
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
 
loggingInterval - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
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
 
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
 
logVector(Logger, Level, float[]) - Static method in class org.tribuo.util.Util
 
logZ - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainBPResults
 
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() - 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.
loss - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
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(T, SGDVector) - Method in interface org.tribuo.common.sgd.SGDObjective
Scores a prediction, returning the loss and a vector of per output dimension gradients.
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(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
 

M

m - Variable in class org.tribuo.FeatureMap
Map from the feature names to their info.
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
 
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
 
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
 
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
 
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
 
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
 
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
 
macroTP() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
mae(Regressor) - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates the Mean Absolute Error for that dimension.
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 org.tribuo.regression.evaluation.RegressionMetrics
Calculates the Mean Absolute Error based on the supplied statistics.
mae(Regressor, RegressionSufficientStatistics) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Calculates the Mean Absolute Error based on the supplied statistics for a single dimension.
main(String[]) - Static method in class org.tribuo.classification.dtree.TrainTest
 
main(String[]) - Static method in class org.tribuo.classification.experiments.ConfigurableTrainTest
 
main(String[]) - Static method in class org.tribuo.classification.experiments.RunAll
 
main(String[]) - Static method in class org.tribuo.classification.experiments.Test
 
main(String[]) - Static method in class org.tribuo.classification.experiments.TrainTest
 
main(String[]) - Static method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
main(String[]) - Static method in class org.tribuo.classification.liblinear.TrainTest
 
main(String[]) - Static method in class org.tribuo.classification.libsvm.TrainTest
 
main(String[]) - Static method in class org.tribuo.classification.mnb.TrainTest
 
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.kernel.TrainTest
 
main(String[]) - Static method in class org.tribuo.classification.sgd.TrainTest
 
main(String[]) - Static method in class org.tribuo.classification.xgboost.TrainTest
 
main(String[]) - Static method in class org.tribuo.clustering.kmeans.TrainTest
 
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
 
main(String[]) - Static method in class org.tribuo.data.PreprocessAndSerialize
 
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
 
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
 
main(String[]) - Static method in class org.tribuo.regression.libsvm.TrainTest
 
main(String[]) - Static method in class org.tribuo.regression.rtree.TrainTest
 
main(String[]) - Static method in class org.tribuo.regression.sgd.TrainTest
 
main(String[]) - Static method in class org.tribuo.regression.slm.TrainTest
 
main(String[]) - Static method in class org.tribuo.regression.xgboost.TrainTest
 
main(String[]) - Static method in class org.tribuo.sequence.SequenceModelExplorer
 
main(String[]) - Static method in class org.tribuo.util.infotheory.example.InformationTheoryDemo
 
MAJOR_VERSION - Static variable in class org.tribuo.Tribuo
The major version number.
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.
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
 
mapScore - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainViterbiResults
 
mapValues - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainViterbiResults
 
MASK_VALUE - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
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, boolean, boolean) - Method in class org.tribuo.math.la.DenseMatrix
 
matrixMultiply(Matrix) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
matrixMultiply(Matrix, boolean, boolean) - 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 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
 
MatrixTuple(int, int, int) - Constructor for class org.tribuo.math.la.MatrixTuple
 
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.
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
 
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
 
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
 
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
 
mean(Collection<V>) - Static method in class org.tribuo.util.Util
 
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
 
MeanStdDevTransformation.MeanStdDevTransformationProvenance - Class in org.tribuo.transform.transformations
Provenance for MeanStdDevTransformation.
MeanStdDevTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
 
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.
MEMBERS - Static variable in class org.tribuo.provenance.EnsembleModelProvenance
 
merge(Tensor[][], int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
 
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(IntArrayContainer, int[], IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
Merges input and otherArray writing to output.
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.
merge(DenseSparseMatrix[]) - Method in class org.tribuo.math.util.HeapMerger
 
merge(SparseVector[]) - Method in class org.tribuo.math.util.HeapMerger
 
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(DenseSparseMatrix[]) - Method in class org.tribuo.math.util.MatrixHeapMerger
 
merge(SparseVector[]) - 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 interface org.tribuo.math.util.Merger
Merges an array of SparseVector into a single SparseVector.
merge(double, double) - Method in interface org.tribuo.util.Merger
Merges first and second.
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.
MessageDigestHasher - Class in org.tribuo.hash
Hashes Strings using the supplied MessageDigest type.
MessageDigestHasher(String, String) - Constructor for class org.tribuo.hash.MessageDigestHasher
 
MessageDigestHasher.MessageDigestHasherProvenance - Class in org.tribuo.hash
Provenance for MessageDigestHasher.
MessageDigestHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
 
metadata - Variable in class org.tribuo.Example
The example metadata.
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
 
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(T) - Constructor for class org.tribuo.evaluation.metrics.MetricTarget
Builds a metric target for an output.
MetricTarget(EvaluationMetric.Average) - Constructor for class org.tribuo.evaluation.metrics.MetricTarget
Builds a metric target for an average.
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(List<T1>, List<T2>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon mutual information, using histogram probability estimators.
mi(PairDistribution<T1, T2>) - Static method in class org.tribuo.util.infotheory.InformationTheory
Calculates the discrete Shannon mutual information, using histogram probability estimators.
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(WeightedPairDistribution<T1, T2>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
 
mi(PairDistribution<T1, T2>, Map<?, Double>, WeightedInformationTheory.VariableSelector) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
 
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
 
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
 
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
 
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_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
 
minCount(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
minCount - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
minCount - Variable in class org.tribuo.data.DataOptions
 
minCount(CommandInterpreter, int) - Method in class org.tribuo.data.DatasetExplorer
 
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
 
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.TrainTest.SGDOptions
 
minImpurityDecrease - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
Minimum impurity decrease.
minImpurityDecrease - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
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
 
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
 
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
 
minWeight - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
mkTrainingNode(Dataset<Label>, AbstractTrainingNode.LeafDeterminer) - Method in class org.tribuo.classification.dtree.CARTClassificationTrainer
 
mkTrainingNode(Dataset<T>, AbstractTrainingNode.LeafDeterminer) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
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
 
MLPExamples - Class in org.tribuo.interop.tensorflow.example
Static factory methods which produce Multi-Layer Perceptron architectures.
mnbAlpha - Variable in class org.tribuo.classification.mnb.MultinomialNaiveBayesOptions
 
mnbOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
 
mnbOptions - Variable in class org.tribuo.classification.mnb.TrainTest.TrainTestOptions
 
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<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.
modelDescription(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
modelDescription(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer
 
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
 
modelFilename - Variable in class org.tribuo.data.DatasetExplorer.DatasetExplorerOptions
 
modelFilename - Variable in class org.tribuo.ModelExplorer.ModelExplorerOptions
Model file to load.
modelFilename - Variable in class org.tribuo.sequence.SequenceModelExplorer.SequenceModelExplorerOptions
 
modelGraph - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
modelHashingAlgorithm - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
modelHashingAlgorithm - Variable in class org.tribuo.hash.HashingOptions
 
modelHashingSalt - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
modelHashingSalt - Variable in class org.tribuo.hash.HashingOptions
 
modelParameters - Variable in class org.tribuo.common.sgd.AbstractSGDModel
The weights for this model.
modelPath - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
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.
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
 
ModHashCodeHasher - Class in org.tribuo.hash
Hashes names using String.hashCode(), then reduces the dimension.
ModHashCodeHasher(String) - Constructor for class org.tribuo.hash.ModHashCodeHasher
 
ModHashCodeHasher(int, String) - Constructor for class org.tribuo.hash.ModHashCodeHasher
 
ModHashCodeHasher.ModHashCodeHasherProvenance - Class in org.tribuo.hash
Provenance for the ModHashCodeHasher.
ModHashCodeHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
 
momentum - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
 
mStep(ForkJoinPool, DenseVector[], Map<Integer, List<Integer>>, SparseVector[], double[]) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
Runs the mStep, writing to the centroidVectors array.
mul(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that multiplies each value by the operand.
multiDimDenseTrainTest() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
 
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(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(String) - Constructor for class org.tribuo.multilabel.MultiLabel
Builds a MultiLabel with a single String label.
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
 
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.
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
 
MultiLabelMetrics - Enum 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.
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
 
MultinomialNaiveBayesTrainer(double) - Constructor for class org.tribuo.classification.mnb.MultinomialNaiveBayesTrainer
 
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.LongPair - Class in org.tribuo.util
128 bits of state
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.
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(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.MutableDataset
Creates an empty dataset.
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.
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
 
MutableSequenceDataset<T extends Output<T>> - Class in org.tribuo.sequence
A MutableSequenceDataset is a SequenceDataset with a MutableFeatureMap which grows over time.
MutableSequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
Creates an empty sequence dataset.
MutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
Creates a dataset from a data source.
MutableSequenceDataset(SequenceDataSource<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
 
MutableSequenceDataset(ImmutableSequenceDataset<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset
 

N

NAME - Static variable in class org.tribuo.Example
By convention the example name is stored using this metadata key.
name - Variable in class org.tribuo.Feature
The feature name.
name - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple
 
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.
nameFeature(String, String, int) - Method in class org.tribuo.classification.explanations.lime.LIMEColumnar
Generate the feature name by combining the word and index.
nameFeature(String, int) - Method in class org.tribuo.classification.explanations.lime.LIMEText
Generate the feature name by combining the word and index.
NAMESPACE - Static variable in interface org.tribuo.data.columnar.FieldProcessor
The namespacing separator.
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
 
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.
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 - Variable in class org.tribuo.data.DataOptions
 
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.
Node<T extends Output<T>> - Interface in org.tribuo.common.tree
A node in a decision tree.
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.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
 
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(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
 
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 - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
normalize - Variable in class org.tribuo.regression.slm.SLMTrainer
 
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 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
 
normalizeToDistribution(float[]) - Static method in class org.tribuo.util.Util
 
nsplits - Variable in class org.tribuo.evaluation.KFoldSplitter
 
numActiveElements(int) - Method in class org.tribuo.math.la.DenseMatrix
 
numActiveElements(int) - Method in class org.tribuo.math.la.DenseSparseMatrix
 
numActiveElements() - Method in class org.tribuo.math.la.DenseVector
 
numActiveElements(int) - Method in interface org.tribuo.math.la.Matrix
The number of non-zero elements in that row.
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
 
numActiveFeatures - Variable in class org.tribuo.common.sgd.AbstractSGDModel.PredAndActive
 
numExamples - Variable in class org.tribuo.common.tree.AbstractTrainingNode
 
numExamples(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
 
numFeatures(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
numFeatures(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
 
numFeatures(CommandInterpreter) - Method in class org.tribuo.ModelExplorer
Displays the number of features.
numFeatures(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer
 
numFolds - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
numMembers - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
numMembers - Variable in class org.tribuo.ensemble.BaggingTrainer
 
numSamples - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
numStates - Variable in class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
 
numThreads - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
 
numThreads - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
 
numThreads - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
numThreads - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
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

observe(Event) - Method in class org.tribuo.anomaly.MutableAnomalyInfo
 
observe(double) - Method in class org.tribuo.CategoricalInfo
 
observe(Label) - Method in class org.tribuo.classification.MutableLabelInfo
 
observe(ClusterID) - Method in class org.tribuo.clustering.MutableClusteringInfo
 
observe(Prediction<T>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Records the supplied prediction.
observe(List<Prediction<T>>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Records all the supplied predictions.
observe(MultiLabel) - Method in class org.tribuo.multilabel.MutableMultiLabelInfo
Throws IllegalStateException if the MultiLabel contains a Label which has a "," in it.
observe(T) - Method in interface org.tribuo.MutableOutputInfo
Records an output value or statistics thereof.
observe(double) - Method in class org.tribuo.RealInfo
 
observe(Regressor) - Method in class org.tribuo.regression.MutableRegressionInfo
 
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.
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(int) - Method in class org.tribuo.transform.transformations.SimpleTransform
No-op on this TransformStatistics.
observeSparse() - Method in interface org.tribuo.transform.TransformStatistics
Deprecated.
in 4.1 as it's unnecessary.
observeSparse(int) - Method in interface org.tribuo.transform.TransformStatistics
Observes count sparse values.
observeValue(double, int) - Method in class org.tribuo.regression.rtree.impl.TreeFeature
Observes a value for this feature.
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.
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.
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.
ONNXExternalModel<T extends Output<T>> - Class in org.tribuo.interop.onnx
A Tribuo wrapper around a ONNX model.
optimiser - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
optimiser - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
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 a anomaly data generator used for 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.
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.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 a clustering data generator used for testing implementations.
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.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.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 an implementation of independent multi-label classification that wraps a Label Trainer and uses it to make independent predictions of each label.
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.
org.tribuo.multilabel.sgd - package org.tribuo.multilabel.sgd
Provides infrastructure for Stochastic Gradient Descent for multi-label classification problems.
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.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.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.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.
OS_STRING - Static variable in class org.tribuo.provenance.ModelProvenance
 
osString - Variable in class org.tribuo.provenance.ModelProvenance
 
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
 
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
 
OUTPUT_FILE_MODIFIED_TIME - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
 
OUTPUT_RESOURCE_HASH - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
 
OutputConverter<T extends Output<T>> - Interface in org.tribuo.interop.tensorflow
Converts the Output into a Tensor and vice versa.
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
 
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
 
outputFactory - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
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<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.
outputFactory - Variable in class org.tribuo.sequence.SequenceDataset
A factory for making OutputInfo and Output of the appropriate type.
OutputFactoryProvenance - Interface in org.tribuo.provenance
A tag provenance for an output factory.
outputFile - Variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.BERTFeatureExtractorOptions
 
outputID - Variable in class org.tribuo.impl.IndexedArrayExample
 
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(CommandInterpreter) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
outputInfo(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
 
outputInfo(CommandInterpreter) - Method in class org.tribuo.ModelExplorer
Displays the output info.
OutputInfo<T extends Output<T>> - Interface in org.tribuo
Tracks relevant properties of the appropriate Output subclass.
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.sequence.SequenceModelExplorer
 
outputMap - Variable in class org.tribuo.MutableDataset
Information about the outputs in this dataset.
outputModel - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
 
outputName - Variable in class org.tribuo.interop.tensorflow.example.GraphDefTuple
 
outputName - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
outputName - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
outputPath - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
 
outputPath - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
outputPath - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
outputPath - Variable in class org.tribuo.data.DataOptions
 
outputPath - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
 
outputPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
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
 

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, Map<CachedPair<T1, T2>, MutableLong>, Map<T1, MutableLong>, Map<T2, MutableLong>) - Constructor for class org.tribuo.util.infotheory.impl.PairDistribution
 
PairDistribution(long, LinkedHashMap<CachedPair<T1, T2>, MutableLong>, LinkedHashMap<T1, MutableLong>, LinkedHashMap<T2, MutableLong>) - Constructor for class org.tribuo.util.infotheory.impl.PairDistribution
 
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
 
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 org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
 
paramName - Variable in enum org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
 
paramName - Variable in enum org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
 
parseElement(String) - Static method in class org.tribuo.multilabel.MultiLabel
Parses a string of the form:
parseElement(int, String) - Static method in class org.tribuo.regression.Regressor
Parses a string of the form:
parseLine(String, int) - Method in class org.tribuo.data.text.impl.SimpleTextDataSource
 
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, char) - Static method in class org.tribuo.multilabel.MultiLabel
Parses a string of the form:
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.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
 
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
 
PLACEHOLDER - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
 
POINT_VERSION - Static variable in class org.tribuo.Tribuo
The patch release number.
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.
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.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.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.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.RegexFieldProcessor
Used by the OLCUT configuration system, and should not be called by external code.
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.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.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.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.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.
PRCurve(double[], double[], double[]) - Constructor for class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
Constructs a precision-recall curve.
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(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the precision for this metric target.
precision(double, double, double, double) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the precision based upon the supplied statistics.
precision - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
 
precision(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
precision(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
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 org.tribuo.classification.evaluation.LabelMetrics
 
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(CommandInterpreter, String[]) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
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(SequenceDataset<Label>) - Method in class org.tribuo.classification.sequence.viterbi.ViterbiModel
 
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(SGDVector[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
Generate a prediction using Viterbi.
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.kmeans.KMeansModel
 
predict(Example<T>) - Method in class org.tribuo.common.nearest.KNNModel
 
predict(Example<T>) - Method in class org.tribuo.common.tree.TreeModel
 
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(Iterable<Example<T>>) - Method in class org.tribuo.common.xgboost.XGBoostModel
Uses the model to predict the label for multiple examples.
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(SequenceExample<T>) - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceModel
 
predict(Example<T>) - Method in class org.tribuo.interop.tensorflow.TensorFlowModel
 
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(Example<T>) - Method in class org.tribuo.Model
Uses the model to predict the output for a single example.
predict(Iterable<Example<T>>) - Method in class org.tribuo.Model
Uses the model to predict the output for multiple examples.
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(Example<MultiLabel>) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelModel
 
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.linear.LinearSGDModel
 
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.
predict(Iterable<SequenceExample<T>>) - Method in class org.tribuo.sequence.SequenceModel
Uses the model to predict the output for multiple examples.
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(Example<T>) - Method in class org.tribuo.transform.TransformedModel
 
predict(Dataset<T>) - Method in class org.tribuo.transform.TransformedModel
 
predictAndObserve(Example<T>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Feeds the example to the model, records the prediction and returns it.
predictAndObserve(Iterable<Example<T>>) - Method in class org.tribuo.evaluation.OnlineEvaluator
Feeds the examples to the model, records the predictions and returns them.
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
 
Prediction<T extends Output<T>> - Class in org.tribuo
A prediction made by a Model.
Prediction(T, Map<String, T>, int, Example<T>, boolean) - 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(Prediction<T>, int, Example<T>) - Constructor for class org.tribuo.Prediction
Constructs a prediction from the supplied arguments.
predictionPath - Variable in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
predictionPath - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
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.
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
 
probability - Variable in class org.tribuo.util.infotheory.InformationTheory.GTestStatistics
 
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(String) - Method in interface org.tribuo.data.columnar.FieldProcessor
Processes the field value and generates a (possibly empty) list of ColumnarFeatures.
process(List<ColumnarFeature>) - Method in class org.tribuo.data.columnar.processors.feature.UniqueProcessor
 
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
 
process(String) - Method in class org.tribuo.data.columnar.processors.response.EmptyResponseProcessor
This method always returns Optional.empty().
process(String) - Method in class org.tribuo.data.columnar.processors.response.FieldResponseProcessor
 
process(String) - Method in class org.tribuo.data.columnar.processors.response.QuartileResponseProcessor
 
process(String) - Method in interface org.tribuo.data.columnar.ResponseProcessor
Returns Optional.empty() if it failed to process out a response.
process(String, String) - Method in class org.tribuo.data.text.impl.BasicPipeline
 
process(String) - Method in class org.tribuo.data.text.impl.NgramProcessor
 
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) - Method in interface org.tribuo.data.text.TextProcessor
Extracts features from the supplied text.
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>).
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.
protobufPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
provenance - Variable in class org.tribuo.data.text.impl.SimpleTextDataSource
 
provenance - Variable in class org.tribuo.Model
The model provenance.
provenanceFile - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
 
provenanceOutput - Variable in class org.tribuo.Model
The cached toString of the model provenance.
provenanceOutput - Variable in class org.tribuo.sequence.SequenceModel
 
punct(char, int) - Method in class org.tribuo.util.tokens.universal.Range
 
put(VariableInfo) - Method in class org.tribuo.MutableFeatureMap
Adds a variable info into the feature map.

Q

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.
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 repsonse processor which emits 4 distinct bins for the output factory to process.
quiet - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
quiet - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
QUOTE - Static variable in class org.tribuo.data.csv.CSVIterator
Default quote character.

R

r2(Regressor) - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates R2 for the supplied dimension.
r2() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates R2 for all dimensions.
r2(MetricTarget<Regressor>, RegressionSufficientStatistics) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Calculates R^2 based on the supplied statistics.
r2(Regressor, RegressionSufficientStatistics) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Calculates R^2 based on the supplied statistics for a single dimension.
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(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.
randpermInPlace(double[], 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.
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(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.
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(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(MetricTarget<T>, ConfusionMatrix<T>) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the recall for this metric target.
recall(double, double, double, double) - Static method in class org.tribuo.classification.evaluation.ConfusionMetrics
Calculates the recall based upon the supplied statistics.
recall - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
 
recall(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
recall(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
reconfigureOrtSession(OrtSession.SessionOptions) - Method in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
Reconstructs the OrtSession using the supplied options.
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
 
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.
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, 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(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.Mode - Enum in org.tribuo.data.columnar.processors.field
Matching mode.
regexMappingProcessors - Variable in class org.tribuo.data.columnar.RowProcessor
 
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 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
 
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[], 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 from the supplied named values.
Regressor(Regressor.DimensionTuple[]) - Constructor for class org.tribuo.regression.Regressor
Constructs a regressor from the supplied dimension tuples.
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.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
 
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
 
remove(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
remove(int) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
removeAll(Collection<?>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
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.
removeOther(IntArrayContainer, int[], IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
Copies from input to output excluding the values in otherArray.
removeProvenances - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
 
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
 
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
 
Resources - Class in org.tribuo.tests
Utils for working with classpath resources at test time.
ResponseProcessor<T extends Output<T>> - Interface in org.tribuo.data.columnar
An interface that will take the response field and produce an Output.
responseProcessor - Variable in class org.tribuo.data.columnar.RowProcessor
 
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
 
ResultSetIterator(ResultSet, int) - Constructor for class org.tribuo.data.sql.ResultSetIterator
 
retainAll(Collection<?>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
rho - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions
 
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(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() - Method in interface org.tribuo.regression.evaluation.RegressionEvaluation
Calculates the RMSE for all dimensions.
rmse(MetricTarget<Regressor>, RegressionSufficientStatistics) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Calculates the RMSE based on the supplied statistics.
rmse(Regressor, RegressionSufficientStatistics) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Calculates the RMSE based on the supplied statistics for a single dimension.
RMSProp - Class in org.tribuo.math.optimisers
An implementation of the RMSProp gradient optimiser.
RMSProp(double, double, double, double) - Constructor for class org.tribuo.math.optimisers.RMSProp
 
RMSProp(double, double) - Constructor for class org.tribuo.math.optimisers.RMSProp
 
rng - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
 
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.
Row(long, List<String>, Map<String, String>) - Constructor for class org.tribuo.data.columnar.ColumnarIterator.Row
 
Row<T> - Class in org.tribuo.util.infotheory.impl
A row of values from a RowList.
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
 
rowProcessor - Variable in class org.tribuo.data.columnar.ColumnarDataSource
 
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(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.
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(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<?>>, 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() - Constructor for class org.tribuo.data.columnar.RowProcessor
For olcut.
rowProcessor - Variable in class org.tribuo.data.DataOptions
 
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(int) - Method in class org.tribuo.math.la.DenseMatrix
Calculates the sum of the specified row.
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.
rType - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
rType - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
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

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
 
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
 
SAMPLES_RATIO - Static variable in class org.tribuo.util.infotheory.WeightedInformationTheory
 
sampleStandardDeviation(Collection<V>) - Static method in class org.tribuo.util.Util
 
sampleVariance(Collection<V>) - Static method in class org.tribuo.util.Util
 
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.
save(Path, boolean) - Method in class org.tribuo.datasource.IDXDataSource.IDXData
Writes out this IDXData to the specified path.
saveCSV(CommandInterpreter, String) - Method in class org.tribuo.data.DatasetExplorer
 
saveModel(Model<T>) - Method in class org.tribuo.data.DataOptions
 
scalarAddInPlace(double) - Method in interface org.tribuo.math.la.Tensor
Adds scalar to each element of this Tensor.
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
 
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.
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
 
scores - Variable in class org.tribuo.classification.sgd.crf.ChainHelper.ChainViterbiResults
 
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
 
secondCount - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
 
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
 
seed - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
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
 
seed - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
 
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
 
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
 
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
 
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>>, 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>>, boolean) - Constructor for class org.tribuo.sequence.SequenceExample
 
SequenceExample(List<T>, List<? extends List<? extends Feature>>, float, boolean) - Constructor for class org.tribuo.sequence.SequenceExample
 
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
 
SequenceModelExplorer - Class in org.tribuo.sequence
A CLI for interacting with a SequenceModel.
SequenceModelExplorer() - Constructor for class org.tribuo.sequence.SequenceModelExplorer
 
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.
session - Variable in class org.tribuo.interop.tensorflow.TensorFlowModel
 
set(Tensor[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
 
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(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, double) - Method in class org.tribuo.math.la.DenseVector
 
set(int, int, double) - Method in interface org.tribuo.math.la.Matrix
Sets an element at the supplied location.
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(Tensor[]) - Method in class org.tribuo.math.LinearParameters
 
set(Tensor[]) - Method in interface org.tribuo.math.Parameters
Set the underlying Tensor array to newWeights.
set(int, Row<T>) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
set(char, char, int) - Method in class org.tribuo.util.tokens.universal.Range
 
set(char, int) - Method in class org.tribuo.util.tokens.universal.Range
 
set(char[], int, int) - Method in class org.tribuo.util.tokens.universal.Range
 
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.
setCacheSize(double) - Method in class org.tribuo.common.libsvm.SVMParameters
 
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
 
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
 
setDegree(int) - Method in class org.tribuo.common.libsvm.SVMParameters
 
setElements(DenseVector) - Method in class org.tribuo.math.la.DenseVector
Sets all the elements of this vector to be the same as other.
setEpsilon(double) - Method in class org.tribuo.common.libsvm.SVMParameters
 
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.
setGamma(double) - Method in class org.tribuo.common.libsvm.SVMParameters
 
setGenerateNgrams(boolean) - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
setGenerateUnigrams(boolean) - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
setLabelOrder(List<Label>) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
Sets the label order used in LabelConfusionMatrix.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.
setMaxTokenLength(int) - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
 
setMetadataValue(String, Object) - Method in class org.tribuo.Example
Puts the specified key, value pair into the metadata.
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.
setNu(double) - Method in class org.tribuo.common.libsvm.SVMParameters
 
setNumFeatures(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
setNumSamples(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
setNumThreads(int) - Method in class org.tribuo.common.xgboost.XGBoostModel
Sets the number of threads to use at prediction time.
setProbability() - Method in class org.tribuo.common.libsvm.SVMParameters
Makes the model that is built provide probability estimates.
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
 
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.
setStoreIndices(boolean) - Method in class org.tribuo.dataset.DatasetView
Set to true to store the indices in the provenance system.
setType(Token.TokenType) - Method in class org.tribuo.util.tokens.universal.Range
 
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.
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.
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.Momentum - Enum in org.tribuo.math.optimisers
Momentum types.
sgdEpochs - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
sgdEpochs - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
sgdLoggingInterval - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
sgdLoggingInterval - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
sgdMinibatchSize - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
sgdMinibatchSize - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
sgdObjective - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
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.
sgdObjective - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
SGDOptions() - Constructor for class org.tribuo.regression.sgd.TrainTest.SGDOptions
 
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
 
sgoOptions - Variable in class org.tribuo.classification.sgd.linear.LinearSGDOptions
 
sgoOptions - Variable in class org.tribuo.multilabel.sgd.linear.LinearSGDOptions
 
shape - Variable in class org.tribuo.interop.tensorflow.TensorFlowUtil.TensorTuple
 
shapeCheck(Tensor, Tensor) - Static method in interface org.tribuo.math.la.Tensor
 
shapeSum(int[]) - Static method in interface org.tribuo.math.la.Tensor
 
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
 
shell - Variable in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
shell - Variable in class org.tribuo.data.DatasetExplorer
 
shell - Variable in class org.tribuo.ModelExplorer
The command shell instance.
shell - Variable in class org.tribuo.sequence.SequenceModelExplorer
 
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
 
showLabelStats(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
 
showProvenance(CommandInterpreter) - Method in class org.tribuo.data.DatasetExplorer
 
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
 
ShrinkingMatrix(DenseMatrix, double, double) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingMatrix
 
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
 
ShrinkingVector(DenseVector, double, double) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingVector
 
shuffle - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
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.
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 - Variable in class org.tribuo.common.sgd.AbstractSGDTrainer
 
shuffle(boolean) - Method in class org.tribuo.Dataset
Shuffles the indices, or stops shuffling them.
shuffleInPlace(SparseVector[], int[], double[], SplittableRandom) - Static method in class org.tribuo.classification.sgd.Util
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(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[], DenseVector[], double[], SplittableRandom) - Static method in class org.tribuo.regression.sgd.Util
In place shuffle of the features, labels and weights.
shuffleInPlace(SparseVector[], DenseVector[], double[], int[], SplittableRandom) - Static method in class org.tribuo.regression.sgd.Util
In place shuffle of the features, labels and weights.
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(double) - Static method in class org.tribuo.math.util.SigmoidNormalizer
A logistic sigmoid function.
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
 
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, OutputFactory<T>) - Constructor for class org.tribuo.provenance.SimpleDataSourceProvenance
This constructor initialises the provenance using the current time in the system timezone.
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(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(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.
SimpleFieldExtractor() - Constructor for class org.tribuo.data.columnar.extractors.SimpleFieldExtractor
For olcut.
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
 
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
 
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(Path, OutputFactory<T>, TextFeatureExtractor<T>) - Constructor for class org.tribuo.data.text.impl.SimpleTextDataSource
 
SimpleTextDataSource(File, OutputFactory<T>, TextFeatureExtractor<T>) - Constructor for class org.tribuo.data.text.impl.SimpleTextDataSource
 
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
 
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 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
 
SINGLE_DIM_NAME - Static variable in class org.tribuo.regression.example.RegressionDataGenerator
 
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 - Variable in class org.tribuo.common.tree.impl.IntArrayContainer
 
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 - Variable in class org.tribuo.ImmutableFeatureMap
The number of features.
size() - Method in class org.tribuo.ImmutableFeatureMap
 
size - Variable in class org.tribuo.impl.ArrayExample
 
size() - Method in class org.tribuo.impl.ArrayExample
 
size - Variable in class org.tribuo.impl.BinaryFeaturesExample
 
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(Trainer<T>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance
 
SkeletalTrainerProvenance(SequenceTrainer<T>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance
 
SkeletalTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance
 
SkeletalTrainerProvenance(SkeletalConfiguredObjectProvenance.ExtractedInfo) - 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(boolean, int) - Constructor for class org.tribuo.regression.slm.SLMTrainer
Constructs a trainer for a sparse linear model using sequential forward selection.
SLMTrainer(boolean) - Constructor for class org.tribuo.regression.slm.SLMTrainer
Constructs a trainer for a sparse linear model using sequential forward selection.
SLMTrainer() - Constructor for class org.tribuo.regression.slm.SLMTrainer
For OLCUT.
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.
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(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() - Static method in class org.tribuo.classification.example.LabelledDataGenerator
 
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() - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator
 
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() - Static method in class org.tribuo.regression.example.RegressionDataGenerator
 
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
 
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(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(IntArrayContainer, IntArrayContainer) - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
Relies upon allLeftIndices being sorted in ascending order.
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.
splitChar - Variable in class org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions
 
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
 
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
 
SplitDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
 
splitFraction - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
 
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 in org.tribuo.util.tokens.impl
SplitFunctionTokenizer.SplitType - Enum 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
 
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 org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
 
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
 
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
 
SQLDataSource.SQLDataSourceProvenance - Class in org.tribuo.data.sql
Provenance for SQLDataSource.
SQLDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.data.sql.SQLDataSource.SQLDataSourceProvenance
 
SQLDBConfig - Class in org.tribuo.data.sql
N.B.
SQLDBConfig(String, String, String, Map<String, String>) - Constructor for class org.tribuo.data.sql.SQLDBConfig
 
SQLDBConfig(String, String, String, String, String, Map<String, String>) - Constructor for class org.tribuo.data.sql.SQLDBConfig
 
SQLDBConfig(String, Map<String, String>) - Constructor for class org.tribuo.data.sql.SQLDBConfig
 
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
 
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.
standardize - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 
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
 
start - Variable in class org.tribuo.util.tokens.universal.Range
 
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
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
 
storeIndicesInProvenance() - Method in class org.tribuo.dataset.DatasetView
Are the indices stored in the provenance system.
StripProvenance - Class in org.tribuo.json
A main class for stripping out and storing provenance from a model.
StripProvenance.ProvenanceTypes - Enum 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(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform
Generate a SimpleTransform that subtracts the operand from each value.
subList(int, int) - Method in class org.tribuo.util.infotheory.impl.RowList
Unsupported.
subsample - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
subsample - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
subsampleFeatures - Variable in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
subsampleFeatures - Variable in class org.tribuo.regression.xgboost.XGBoostOptions
 
Subsequence(int, int) - Constructor for class org.tribuo.classification.sequence.ConfidencePredictingSequenceModel.Subsequence
Constructs a subsequence for the fixed range, exclusive of the end.
subSequence(int, int) - Method in class org.tribuo.util.tokens.universal.Range
 
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.
sum() - Method in class org.tribuo.math.la.DenseVector
 
sum(DoubleUnaryOperator) - 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
 
sum(float[]) - Static method in class org.tribuo.util.Util
 
sum(double[], int) - Static method in class org.tribuo.util.Util
 
sum(float[], int) - Static method in class org.tribuo.util.Util
 
sum(int[], int, float[]) - Static method in class org.tribuo.util.Util
 
sum(int[], float[]) - Static method in class org.tribuo.util.Util
 
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(DenseVector) - Static method in class org.tribuo.classification.sgd.crf.ChainHelper
Sums the log probabilities.
sumLogProbs(double[]) - Static method in class org.tribuo.classification.sgd.crf.ChainHelper
Sums the log probabilities.
summarize(EvaluationMetric<T, C>, List<? extends Model<T>>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator
Summarize performance w.r.t.
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(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.
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<? 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(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(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.
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(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of examples with this true label this confusion matrix has seen.
support() - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
support(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
support(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
support() - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
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 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
 
SVMClassificationType.SVMMode - Enum in org.tribuo.classification.libsvm
The classification model types.
svmCoefficient - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
 
svmDegree - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
 
svmGamma - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
 
svmKernel - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
 
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
 
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
 
SVMRegressionType.SVMMode - Enum in org.tribuo.regression.libsvm
Type of regression SVM.
svmType - Variable in class org.tribuo.classification.libsvm.LibSVMOptions
 
svmType - Variable in class org.tribuo.common.libsvm.LibSVMTrainer
The type of SVM algorithm.
svmType - Variable in class org.tribuo.common.libsvm.SVMParameters
 
SVMType<T extends Output<T>> - Interface in org.tribuo.common.libsvm
A carrier type for the SVM type.
svmType - Variable in class org.tribuo.regression.libsvm.TrainTest.LibSVMOptions
 

T

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.
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
 
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(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(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.TensorFlowTrainerProvenance - Class in org.tribuo.interop.tensorflow
 
TensorFlowTrainer.TFModelFormat - Enum in org.tribuo.interop.tensorflow
The model format to emit.
TensorFlowTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.interop.tensorflow.TensorFlowTrainer.TensorFlowTrainerProvenance
 
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.
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
 
termCounting - Variable in class org.tribuo.data.DataOptions
 
terminationCriterion - Variable in class org.tribuo.common.liblinear.LibLinearTrainer
 
terminationCriterion - Variable in class org.tribuo.regression.liblinear.TrainTest.LibLinearOptions
 
Test - Class in org.tribuo.classification.experiments
Test a classifier for a standard dataset.
Test() - Constructor for class org.tribuo.classification.experiments.Test
 
test - Variable in class org.tribuo.evaluation.KFoldSplitter.TrainTestFold
 
Test.ConfigurableTestOptions - Class in org.tribuo.classification.experiments
Command line options.
testBatchSize - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
testDataset - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
 
testDataset - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
testingPath - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
testingPath - Variable in class org.tribuo.data.DataOptions
 
testingPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
testSource - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
text - Variable in class org.tribuo.util.tokens.Token
 
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(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.
TextDataSource(File, OutputFactory<T>, TextFeatureExtractor<T>, DocumentPreprocessor...) - Constructor for class org.tribuo.data.text.TextDataSource
 
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 ListExample.
TextFeatureExtractorImpl(TextPipeline) - Constructor for class org.tribuo.data.text.impl.TextFeatureExtractorImpl
 
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
 
TextProcessingException(String, Throwable) - Constructor for exception org.tribuo.data.text.TextProcessingException
 
TextProcessingException(Throwable) - Constructor for exception org.tribuo.data.text.TextProcessingException
 
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.
thirdDimensionName - Static variable in class org.tribuo.regression.example.RegressionDataGenerator
Name of the third output dimension.
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 - 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
 
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.
thresholds - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.PRCurve
 
thresholds - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.ROC
 
time - Variable in class org.tribuo.provenance.ModelProvenance
 
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(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() - Method in interface org.tribuo.classification.evaluation.ClassifierEvaluation
Returns the total number of true negatives.
tn(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of true negatives for the supplied label.
tn() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of true negatives.
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(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
tn(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
tn() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
tn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
tn(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
tn() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
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
 
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(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 integation into a webpage.
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.
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.TokenType - Enum in org.tribuo.util.tokens
Tokenizers may product multiple kinds of tokens, depending on the application to which they're being put.
TOKEN_METADATA - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
TOKEN_OUTPUT - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
TOKEN_TYPE_IDS - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
TOKEN_TYPE_VALUE - Static variable in class org.tribuo.interop.onnx.extractors.BERTFeatureExtractor
 
TokenizationException - Exception in org.tribuo.util.tokens
Wraps exceptions thrown by tokenizers.
TokenizationException(String) - Constructor for exception org.tribuo.util.tokens.TokenizationException
 
TokenizationException(String, Throwable) - Constructor for exception org.tribuo.util.tokens.TokenizationException
 
TokenizationException(Throwable) - Constructor for exception org.tribuo.util.tokens.TokenizationException
 
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 org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
 
tolerance - Static variable in interface org.tribuo.math.optimisers.util.ShrinkingTensor
 
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
 
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.classification.explanations.lime.LIMETextCLI
 
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.ModelExplorer
Displays the top n features.
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.sequence.SequenceModelExplorer
 
toPrimitiveDouble(List<Double>) - Static method in class org.tribuo.util.Util
 
toPrimitiveDoubleFromInteger(List<Integer>) - Static method in class org.tribuo.util.Util
 
toPrimitiveFloat(List<Float>) - Static method in class org.tribuo.util.Util
 
toPrimitiveInt(List<Integer>) - Static method in class org.tribuo.util.Util
 
toPrimitiveLong(List<Long>) - Static method in class org.tribuo.util.Util
 
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.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.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.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.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
 
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.onnx.DenseTransformer
 
toString() - Method in class org.tribuo.interop.onnx.ImageTransformer
 
toString() - Method in class org.tribuo.interop.onnx.LabelTransformer
 
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.evaluation.MultiLabelConfusionMatrix
 
toString() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
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.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.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 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.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(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() - 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(T) - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The number of true positives for the supplied label.
tp() - Method in interface org.tribuo.classification.evaluation.ConfusionMatrix
The total number of true positives.
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(Label) - Method in class org.tribuo.classification.evaluation.LabelConfusionMatrix
 
tp(Label) - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
tp() - Method in class org.tribuo.classification.sequence.LabelSequenceEvaluation
 
tp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelConfusionMatrix
 
tp(MultiLabel) - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
tp() - Method in class org.tribuo.multilabel.evaluation.MultiLabelEvaluationImpl
 
tpr - Variable in class org.tribuo.classification.evaluation.LabelEvaluationUtil.ROC
 
train(Dataset<Event>, Map<String, Provenance>) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
 
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(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(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<ClusterID>, Map<String, Provenance>) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
train(Dataset<ClusterID>) - Method in class org.tribuo.clustering.kmeans.KMeansTrainer
 
train(Dataset<T>) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
 
train(Dataset<T>) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
 
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>) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.sgd.AbstractSGDTrainer
 
train(Dataset<T>) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
 
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 - Variable in class org.tribuo.evaluation.KFoldSplitter.TrainTestFold
 
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(SequenceDataset<T>, Map<String, Provenance>) - Method in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
train(Dataset<T>) - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.interop.tensorflow.TensorFlowTrainer
 
train(Dataset<MultiLabel>, Map<String, Provenance>) - Method in class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer
 
train(Dataset<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionSparseTrainer
 
train(Dataset<Regressor>, Map<String, Provenance>) - 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.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(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>) - 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 interface org.tribuo.sequence.SequenceTrainer
Trains a sequence prediction model using the examples in the given data set.
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>, 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>) - 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 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_INVOCATION_COUNT - Static variable in interface org.tribuo.provenance.TrainerProvenance
 
trainDataset - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
 
trainDataset - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
 
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
 
trainer - Variable in class org.tribuo.classification.sequence.SeqTrainTest.SeqTrainTestOptions
 
trainer - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
trainer - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
TRAINER - Static variable in class org.tribuo.provenance.ModelProvenance
 
Trainer<T extends Output<T>> - Interface in org.tribuo
An interface for things that can train predictive models.
trainerOptions - Variable in class org.tribuo.classification.experiments.TrainTest.AllClassificationOptions
 
trainerOptions - Variable in class org.tribuo.classification.sgd.kernel.TrainTest.TrainTestOptions
 
trainerOptions - Variable in class org.tribuo.classification.sgd.TrainTest.TrainTestOptions
 
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(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.
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(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.TrainerProvenanceImpl
Construct a TrainerProvenance by extracting the necessary fields from the supplied map.
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_TIME - Static variable in class org.tribuo.provenance.ModelProvenance
 
trainingPath - Variable in class org.tribuo.data.DataOptions
 
trainingPath - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
 
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(svm_parameter, int, svm_node[][], double[][], SplittableRandom) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer
 
trainModels(Parameter, int, FeatureNode[][], double[][]) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer
 
trainModels(svm_parameter, int, svm_node[][], double[][], SplittableRandom) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer
 
trainModels(Parameter, int, FeatureNode[][], double[][]) - Method in class org.tribuo.common.liblinear.LibLinearTrainer
Train all the liblinear instances necessary for this dataset.
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(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.regression.libsvm.LibSVMRegressionTrainer
 
trainOp - Variable in class org.tribuo.interop.tensorflow.sequence.TensorFlowSequenceTrainer
 
trainPath - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
 
trainSingleModel(Dataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, SplittableRandom, Map<String, Provenance>) - Method in class org.tribuo.ensemble.BaggingTrainer
 
trainSource - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
TrainTest - Class in org.tribuo.classification.dtree
Build and run a decision tree classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.dtree.TrainTest
 
TrainTest - Class in org.tribuo.classification.experiments
Build and run a classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.experiments.TrainTest
 
TrainTest - Class in org.tribuo.classification.liblinear
Build and run a liblinear-java classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.liblinear.TrainTest
 
TrainTest - Class in org.tribuo.classification.libsvm
Build and run a LibSVM classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.libsvm.TrainTest
 
TrainTest - Class in org.tribuo.classification.mnb
Build and run a multinomial naive bayes classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.mnb.TrainTest
 
TrainTest - Class in org.tribuo.classification.sgd.kernel
Build and run a kernel SVM classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.sgd.kernel.TrainTest
 
TrainTest - Class in org.tribuo.classification.sgd
Build and run a classifier for a standard dataset using LinearSGDTrainer.
TrainTest() - Constructor for class org.tribuo.classification.sgd.TrainTest
 
TrainTest - Class in org.tribuo.classification.xgboost
Build and run an XGBoost classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.classification.xgboost.TrainTest
 
TrainTest - Class in org.tribuo.clustering.kmeans
Build and run a k-means clustering model for a standard dataset.
TrainTest() - Constructor for class org.tribuo.clustering.kmeans.TrainTest
 
TrainTest - Class in org.tribuo.interop.tensorflow
Build and run a Tensorflow multi-class classifier for a standard dataset.
TrainTest() - Constructor for class org.tribuo.interop.tensorflow.TrainTest
 
TrainTest - Class in org.tribuo.regression.liblinear
Build and run a LibLinear regressor for a standard dataset.
TrainTest() - Constructor for class org.tribuo.regression.liblinear.TrainTest
 
TrainTest - Class in org.tribuo.regression.libsvm
Build and run a LibSVM regressor for a standard dataset.
TrainTest() - Constructor for class org.tribuo.regression.libsvm.TrainTest
 
TrainTest - Class in org.tribuo.regression.rtree
Build and run a regression tree for a standard dataset.
TrainTest() - Constructor for class org.tribuo.regression.rtree.TrainTest
 
TrainTest - Class in org.tribuo.regression.sgd
Build and run a linear regression for a standard dataset.
TrainTest() - Constructor for class org.tribuo.regression.sgd.TrainTest
 
TrainTest - Class in org.tribuo.regression.slm
Build and run a sparse linear regression model for a standard dataset.
TrainTest() - Constructor for class org.tribuo.regression.slm.TrainTest
 
TrainTest - Class in org.tribuo.regression.xgboost
Build and run an XGBoost regressor for a standard dataset.
TrainTest() - Constructor for class org.tribuo.regression.xgboost.TrainTest
 
TrainTest.AllClassificationOptions - Class in org.tribuo.classification.experiments
Command line options.
TrainTest.ImpurityType - Enum in org.tribuo.regression.rtree
Impurity function.
TrainTest.InputType - Enum 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 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 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.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 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.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>, long) - Constructor for class org.tribuo.evaluation.TrainTestSplitter
Creates a splitter that splits a dataset 70/30 train and test.
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.SplitDataSourceProvenance - Class in org.tribuo.evaluation
Provenance for a split data source.
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(OrtEnvironment, SparseVector) - Method in class org.tribuo.interop.onnx.DenseTransformer
 
transform(OrtEnvironment, List<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, 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, SparseVector) - Method in class org.tribuo.interop.onnx.ImageTransformer
 
transform(OrtEnvironment, List<SparseVector>) - Method in class org.tribuo.interop.onnx.ImageTransformer
 
transform(TransformerMap) - Method in class org.tribuo.MutableDataset
Applies all the transformations from the TransformerMap to this dataset.
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.
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
 
transformationMap - Variable in class org.tribuo.data.CompletelyConfigurableTrainTest.ConfigurableTrainTestOptions
 
transformationMap - Variable in class org.tribuo.data.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
TransformationMap - Class in org.tribuo.transform
A carrier type for a set of transformations to be applied to a Dataset.
TransformationMap(List<Transformation>, Map<String, List<Transformation>>) - Constructor for class org.tribuo.transform.TransformationMap
 
TransformationMap(List<Transformation>) - Constructor for class org.tribuo.transform.TransformationMap
 
TransformationMap(Map<String, List<Transformation>>) - Constructor for class org.tribuo.transform.TransformationMap
 
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
 
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<T>) - Method in interface org.tribuo.interop.onnx.OutputTransformer
Converts a OnnxValue containing multiple outputs into a list of Outputs.
transformToBatchOutput(List<OnnxValue>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
transformToBatchPrediction(List<OnnxValue>, ImmutableOutputInfo<Label>, int[], List<Example<Label>>) - Method in class org.tribuo.interop.onnx.LabelTransformer
 
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.
transformToBatchPrediction(List<OnnxValue>, ImmutableOutputInfo<Regressor>, int[], List<Example<Regressor>>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
transformToOutput(List<OnnxValue>, ImmutableOutputInfo<Label>) - Method in class org.tribuo.interop.onnx.LabelTransformer
 
transformToOutput(List<OnnxValue>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.onnx.OutputTransformer
Converts a OnnxValue into the specified output type.
transformToOutput(List<OnnxValue>, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
transformToPrediction(List<OnnxValue>, ImmutableOutputInfo<Label>, int, Example<Label>) - Method in class org.tribuo.interop.onnx.LabelTransformer
 
transformToPrediction(List<OnnxValue>, ImmutableOutputInfo<T>, int, Example<T>) - Method in interface org.tribuo.interop.onnx.OutputTransformer
Converts a OnnxValue into a Prediction.
transformToPrediction(List<OnnxValue>, ImmutableOutputInfo<Regressor>, int, Example<Regressor>) - Method in class org.tribuo.interop.onnx.RegressorTransformer
 
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
 
transpose() - Method in class org.tribuo.math.la.DenseMatrix
Returns a transposed copy of this matrix.
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.
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.
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
 
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
 
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_VERSION_STRING - Static variable in class org.tribuo.provenance.ModelProvenance
 
TRIBUO_VERSION_STRING - Static variable in interface org.tribuo.provenance.TrainerProvenance
 
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
 
tryAdvance(Consumer<? super ColumnarIterator.Row>) - Method in class org.tribuo.data.columnar.ColumnarIterator
 
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
 
type - Variable in class org.tribuo.util.infotheory.example.InformationTheoryDemo.DemoOptions
 
type - Variable in class org.tribuo.util.tokens.Token
 
type - Variable in class org.tribuo.util.tokens.universal.Range
 

U

UNASSIGNED - Static variable in class org.tribuo.clustering.ClusterID
 
UNASSIGNED_CLUSTER_ID - Static variable in class org.tribuo.clustering.ClusteringFactory
 
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(double) - Constructor for class org.tribuo.data.text.impl.UniqueAggregator
 
UniqueAggregator() - Constructor for class org.tribuo.data.text.impl.UniqueAggregator
 
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 in org.tribuo.data.columnar.processors.feature
The type of reduction operation to perform.
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(boolean) - Constructor for class org.tribuo.util.tokens.universal.UniversalTokenizer
 
UniversalTokenizer() - Constructor for class org.tribuo.util.tokens.universal.UniversalTokenizer
Constructs a universal tokenizer which doesn't send punctuation.
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
 
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
 
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
 
update(Tensor[]) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
 
update(Tensor[]) - Method in class org.tribuo.math.LinearParameters
 
update(Tensor[]) - Method in interface org.tribuo.math.Parameters
Apply gradients to the parameters.
usage() - Static method in class org.tribuo.sequence.SequenceModelExplorer
 
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
 
username - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
 
utf8Charset - Static variable in class org.tribuo.hash.MessageDigestHasher
 
Util - Class in org.tribuo.classification.sgd
SGD utilities.
Util() - Constructor for class org.tribuo.classification.sgd.Util
 
Util - Class in org.tribuo.regression.sgd
Utilities.
Util() - Constructor for class org.tribuo.regression.sgd.Util
 
Util - Class in org.tribuo.util
Ye olde util class.
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
 
val2 - Variable in class org.tribuo.util.MurmurHash3.LongPair
 
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.
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(Map<T, Integer>) - Static method in interface org.tribuo.OutputFactory
Validates that the mapping can be used as an output info, i.e.
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.
validateParamNames(Set<String>) - Method in enum 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
 
value - Variable in enum org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
 
value - Variable in enum org.tribuo.data.DataOptions.Delimiter
 
value - Variable in enum 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
 
value - Variable in class org.tribuo.math.la.MatrixTuple
 
value - Variable in class org.tribuo.math.la.VectorTuple
 
value - Variable in class org.tribuo.regression.rtree.impl.InvertedFeature
 
value - Variable in class org.tribuo.util.IntDoublePair
The value.
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.
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.
valueCounts - Variable in class org.tribuo.CategoricalInfo
The occurrence counts of each value.
valueOf(String) - Static method in enum org.tribuo.anomaly.evaluation.AnomalyMetrics
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.anomaly.Event.EventType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.anomaly.liblinear.LinearAnomalyType.LinearType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.anomaly.libsvm.SVMAnomalyType.SVMMode
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.dtree.CARTClassificationOptions.ImpurityType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.dtree.CARTClassificationOptions.TreeType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.evaluation.LabelMetrics
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.liblinear.LinearClassificationType.LinearType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.libsvm.SVMClassificationType.SVMMode
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.sequence.viterbi.ViterbiModel.ScoreAggregation
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions.ViterbiLabelFeatures
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.sgd.crf.CRFModel.ConfidenceType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.classification.sgd.linear.LinearSGDOptions.LossEnum
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.clustering.evaluation.ClusteringMetrics
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.clustering.kmeans.KMeansTrainer.Distance
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.common.libsvm.KernelType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.common.nearest.KNNClassifierOptions.EnsembleCombinerType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.common.nearest.KNNModel.Backend
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.common.nearest.KNNTrainer.Distance
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.data.columnar.processors.field.RegexFieldProcessor.Mode
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.data.DataOptions.Delimiter
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.data.DataOptions.InputFormat
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.datasource.AggregateDataSource.IterationOrder
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.evaluation.metrics.EvaluationMetric.Average
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.hash.HashingOptions.ModelHashingType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.OutputPooling
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.interop.tensorflow.GradientOptimiser
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.interop.tensorflow.TensorFlowTrainer.TFModelFormat
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.interop.tensorflow.TrainTest.InputType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.json.StripProvenance.ProvenanceTypes
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.math.optimisers.SGD.Momentum
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.multilabel.evaluation.MultiLabelMetrics
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.multilabel.sgd.linear.LinearSGDOptions.LossEnum
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.liblinear.LinearRegressionType.LinearType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.libsvm.SVMRegressionType.SVMMode
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.rtree.TrainTest.ImpurityType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.rtree.TrainTest.TreeType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.sgd.TrainTest.LossEnum
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.slm.TrainTest.SLMType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.transform.transformations.BinningTransformation.BinningType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.transform.transformations.SimpleTransform.Operation
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.util.infotheory.example.InformationTheoryDemo.DistributionType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.util.infotheory.WeightedInformationTheory.VariableSelector
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.util.tokens.Token.TokenType
Returns the enum constant of this type with the specified name.
values() - Static method in enum org.tribuo.anomaly.evaluation.AnomalyMetrics
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.anomaly.Event.EventType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.anomaly.liblinear.LinearAnomalyType.LinearType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.anomaly.libsvm.SVMAnomalyType.SVMMode
Returns an array containing the constants of this enum type, in the order they are declared.
values - Variable in class org.tribuo.CategoricalInfo
The values array.
values() - Static method in enum org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.dtree.CARTClassificationOptions.ImpurityType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.dtree.CARTClassificationOptions.TreeType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.ensemble.ClassificationEnsembleOptions.EnsembleType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.evaluation.LabelMetrics
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.experiments.AllTrainerOptions.AlgorithmType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.liblinear.LinearClassificationType.LinearType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.libsvm.SVMClassificationType.SVMMode
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.sequence.viterbi.ViterbiModel.ScoreAggregation
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.sequence.viterbi.ViterbiTrainerOptions.ViterbiLabelFeatures
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.sgd.crf.CRFModel.ConfidenceType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.sgd.kernel.KernelSVMOptions.KernelEnum
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.classification.sgd.linear.LinearSGDOptions.LossEnum
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.clustering.evaluation.ClusteringMetrics
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.clustering.kmeans.KMeansTrainer.Distance
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.common.libsvm.KernelType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.common.nearest.KNNClassifierOptions.EnsembleCombinerType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.common.nearest.KNNModel.Backend
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.common.nearest.KNNTrainer.Distance
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.common.xgboost.XGBoostTrainer.BoosterType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.common.xgboost.XGBoostTrainer.LoggingVerbosity
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.common.xgboost.XGBoostTrainer.TreeMethod
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.data.columnar.FieldProcessor.GeneratedFeatureType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.data.columnar.processors.feature.UniqueProcessor.UniqueType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.data.columnar.processors.field.RegexFieldProcessor.Mode
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.data.DataOptions.Delimiter
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.data.DataOptions.InputFormat
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.data.text.impl.CasingPreprocessor.CasingOperation
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.datasource.AggregateDataSource.IterationOrder
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType
Returns an array containing the constants of this enum type, 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 org.tribuo.evaluation.metrics.EvaluationMetric.Average
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.hash.HashingOptions.ModelHashingType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.interop.onnx.extractors.BERTFeatureExtractor.OutputPooling
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.interop.tensorflow.GradientOptimiser
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.interop.tensorflow.TensorFlowTrainer.TFModelFormat
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.interop.tensorflow.TrainTest.InputType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.json.StripProvenance.ProvenanceTypes
Returns an array containing the constants of this enum type, in the order they are declared.
values - Variable in class org.tribuo.math.la.DenseMatrix
 
values - Variable in class org.tribuo.math.la.SparseVector
 
values() - Static method in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.math.optimisers.SGD.Momentum
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.multilabel.evaluation.MultiLabelMetrics
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.multilabel.sgd.linear.LinearSGDOptions.LossEnum
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.baseline.DummyRegressionTrainer.DummyType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.evaluation.RegressionMetrics
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.liblinear.LinearRegressionType.LinearType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.libsvm.SVMRegressionType.SVMMode
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.rtree.TrainTest.ImpurityType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.rtree.TrainTest.TreeType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.sgd.TrainTest.LossEnum
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.slm.TrainTest.SLMType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.transform.transformations.BinningTransformation.BinningType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.transform.transformations.SimpleTransform.Operation
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.util.infotheory.example.InformationTheoryDemo.DistributionType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.util.infotheory.WeightedInformationTheory.VariableSelector
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitResult
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.util.tokens.impl.SplitFunctionTokenizer.SplitType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.util.tokens.options.CoreTokenizerOptions.CoreTokenizerType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.util.tokens.Token.TokenType
Returns an array containing the constants of this enum type, in the order they are declared.
VARIABLE_V2 - Static variable in class org.tribuo.interop.tensorflow.TensorFlowUtil
 
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.
variance(double) - Method in class org.tribuo.math.la.DenseVector
 
variance() - Method in interface org.tribuo.math.la.SGDVector
Calculates the variance of this vector.
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
 
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
 
VectorTuple(int, int) - Constructor for class org.tribuo.math.la.VectorTuple
 
VERSION - Static variable in class org.tribuo.Tribuo
The full Tribuo version string.
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 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, ViterbiModel.ScoreAggregation) - Constructor for class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
 
ViterbiTrainer(Trainer<Label>, LabelFeatureExtractor, int, ViterbiModel.ScoreAggregation) - Constructor for class org.tribuo.classification.sequence.viterbi.ViterbiTrainer
 
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 in org.tribuo.classification.sequence.viterbi
Type of label features to include.
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_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.
weight - Variable in class org.tribuo.Example
The weight associated with this example.
weight - Variable in class org.tribuo.regression.rtree.impurity.RegressorImpurity.ImpurityTuple
 
weight - Variable in class org.tribuo.util.infotheory.impl.WeightCountTuple
 
WeightCountTuple - Class in org.tribuo.util.infotheory.impl
An mutable tuple of a double and a long.
WeightCountTuple() - Constructor for class org.tribuo.util.infotheory.impl.WeightCountTuple
 
WeightCountTuple(double, long) - Constructor for class org.tribuo.util.infotheory.impl.WeightCountTuple
 
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 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
 
WeightedPairDistribution<T1,T2> - Class in org.tribuo.util.infotheory.impl
Generates the counts for a pair of vectors.
WeightedPairDistribution(long, Map<CachedPair<T1, T2>, WeightCountTuple>, Map<T1, WeightCountTuple>, Map<T2, WeightCountTuple>) - Constructor for class org.tribuo.util.infotheory.impl.WeightedPairDistribution
 
WeightedPairDistribution(long, LinkedHashMap<CachedPair<T1, T2>, WeightCountTuple>, LinkedHashMap<T1, WeightCountTuple>, LinkedHashMap<T2, WeightCountTuple>) - Constructor for class org.tribuo.util.infotheory.impl.WeightedPairDistribution
 
weightedSum(double[], float[], int) - Static method in class org.tribuo.util.Util
 
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
 
weightExtractor - Variable in class org.tribuo.data.columnar.RowProcessor
 
weights - Variable in class org.tribuo.classification.experiments.ConfigurableTrainTest.ConfigurableTrainTestOptions
 
weights - Variable in class org.tribuo.classification.sgd.Util.ExampleArray
 
weights - Variable in class org.tribuo.classification.sgd.Util.SequenceExampleArray
 
weights - Variable in class org.tribuo.ensemble.WeightedEnsembleModel
 
whitespaceSplitCharacterFunction - Static variable in class org.tribuo.util.tokens.impl.WhitespaceTokenizer
 
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
 
WIDTH_CONSTANT - Static variable in class org.tribuo.classification.explanations.lime.LIMEBase
 
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(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.
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(String) - Method in class org.tribuo.util.tokens.impl.wordpiece.Wordpiece
Executes Wordpiece tokenization on the provided token.
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.

X

xbgAlpha - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbBoosterType - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbEnsembleSize - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbEta - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbGamma - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbLambda - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbLogLevel - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbMaxDepth - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbMinWeight - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbNumThreads - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
XGBoostClassificationConverter - Class in org.tribuo.classification.xgboost
Converts XGBoost outputs into Label Predictions.
XGBoostClassificationConverter() - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationConverter
 
XGBoostClassificationTrainer - Class in org.tribuo.classification.xgboost
A Trainer which wraps the XGBoost training procedure.
XGBoostClassificationTrainer(int) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
 
XGBoostClassificationTrainer(int, int, boolean) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
 
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(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.
XGBoostClassificationTrainer(int, Map<String, Object>) - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
This gives direct access to the XGBoost parameter map.
XGBoostClassificationTrainer() - Constructor for class org.tribuo.classification.xgboost.XGBoostClassificationTrainer
For olcut.
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.experiments.AllTrainerOptions
 
xgboostOptions - Variable in class org.tribuo.classification.xgboost.TrainTest.TrainTestOptions
 
XGBoostOptions - Class in org.tribuo.classification.xgboost
CLI options for training an XGBoost classifier.
XGBoostOptions() - Constructor for class org.tribuo.classification.xgboost.XGBoostOptions
 
XGBoostOptions() - Constructor for class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
 
XGBoostOptions - Class in org.tribuo.regression.xgboost
CLI options for configuring an XGBoost regression trainer.
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(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, 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, double, double, int, double, double, double, double, double, int, boolean, long) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
Create an XGBoost trainer.
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, Map<String, Object>) - Constructor for class org.tribuo.regression.xgboost.XGBoostRegressionTrainer
This gives direct access to the XGBoost parameter map.
XGBoostRegressionTrainer.RegressionType - Enum 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(int) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
 
XGBoostTrainer(int, int, boolean) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
 
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(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(int, Map<String, Object>) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
This gives direct access to the XGBoost parameter map.
XGBoostTrainer() - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer
For olcut.
XGBoostTrainer.BoosterType - Enum 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 in org.tribuo.common.xgboost
The logging verbosity of the native library.
XGBoostTrainer.TreeMethod - Enum in org.tribuo.common.xgboost
The tree building algorithm.
XGBoostTrainer.XGBoostTrainerProvenance - Class in org.tribuo.common.xgboost
Deprecated.
XGBoostTrainerProvenance(XGBoostTrainer<T>) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer.XGBoostTrainerProvenance
Deprecated.
 
XGBoostTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.common.xgboost.XGBoostTrainer.XGBoostTrainerProvenance
Deprecated.
 
xgbQuiet - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbSubsample - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbSubsampleFeatures - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 
xgbTreeMethod - Variable in class org.tribuo.classification.xgboost.XGBoostOptions
 

Z

zeroIndexed - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
 
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.
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