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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
Creates an XGBoostExternalModel from the supplied model.
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(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 LibLinear'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
 
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
 
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<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.
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
 
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.
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.
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
 
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
 
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.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, 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