Index (Tribuo 4.0.2 API)

A B C D E F G H I J K L M N O P Q R S T U V W X Z

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
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, 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
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
AbstractTrainingNode<T extends Output<T>> - Class in org.tribuo.common.tree: Base class for decision tree nodes used at training time.
AbstractTrainingNode(int, int) - Constructor for class org.tribuo.common.tree.AbstractTrainingNode: Builds an abstract training node.
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.
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.SplitCharactersTokenizer
advance() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
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
AggregateDataSource<T extends Output<T>> - Class in org.tribuo.datasource: Aggregates multiple DataSources, and round-robins the iterators.
AggregateDataSource(List<DataSource<T>>) - Constructor for class org.tribuo.datasource.AggregateDataSource
AggregateDataSource.AggregateDataSourceProvenance - Class in org.tribuo.datasource: Provenance for the AggregateDataSource.
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.LARSOptions
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
alpha - Variable in class org.tribuo.regression.slm.TrainTest.LARSOptions
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.
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.
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
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.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.
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.
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.
buildTree(int[]) - 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[]) - Method in class org.tribuo.common.tree.AbstractTrainingNode
buildTree(int[]) - 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[]) - 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

CARTClassificationOptions.TreeType - Enum in org.tribuo.classification.dtree

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, 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.

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, 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

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

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, 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

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

ChainBPResults(double, DenseVector[], DenseVector[], ChainHelper.ChainCliqueValues) - Constructor for class org.tribuo.classification.sgd.crf.ChainHelper.ChainBPResults

ChainCliqueValues(DenseVector[], DenseMatrix) - Constructor for class org.tribuo.classification.sgd.crf.ChainHelper.ChainCliqueValues

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.

ChainViterbiResults(double, int[], ChainHelper.ChainCliqueValues) - Constructor for class org.tribuo.classification.sgd.crf.ChainHelper.ChainViterbiResults

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.

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

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>) - Constructor for class org.tribuo.classification.dtree.impl.ClassifierTrainingNode

Constructor which creates the inverted file.

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.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.SplitPatternTokenizer

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.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.TensorflowCheckpointModel

close() - Method in class org.tribuo.interop.tensorflow.TensorflowExternalModel

close() - Method in class org.tribuo.interop.tensorflow.TensorflowModel

close() - Method in class org.tribuo.json.JsonFileIterator

closeTensorList(List<Tensor<?>>) - Static method in class org.tribuo.interop.tensorflow.TensorflowUtil

Closes a list of Tensors.

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.

coeff - Variable in class org.tribuo.regression.libsvm.TrainTest.LibLinearOptions

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

columnSum() - Method in class org.tribuo.math.la.DenseMatrix

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

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

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

ConfigurableTrainTest.ConfigurableTrainTestOptions - Class in org.tribuo.data

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

Converts a SequenceExample into an array of SparseVectors suitable for CRF prediction.

convert(SequenceExample<Label>, ImmutableFeatureMap, ImmutableOutputInfo<Label>) - Static method in class org.tribuo.classification.sgd.crf.CRFModel

Converts a SequenceExample into an array of SparseVectors and labels suitable for CRF prediction.

convert(byte) - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType

Converts the byte into the enum.

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.TensorflowExternalModel

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.TensorflowExternalModel

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.TensorflowExternalModel

Converts a tensor into a prediction.

convertOutput(Tensor<?>, int[], List<Example<T>>) - Method in class org.tribuo.interop.tensorflow.TensorflowExternalModel

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.

convertTensorToArray(Tensor<?>) - Static method in class org.tribuo.interop.tensorflow.TensorflowUtil

Extracts the appropriate type of primitive array from a Tensor.

convertTensorToScalar(Tensor<?>) - Static method in class org.tribuo.interop.tensorflow.TensorflowUtil

Converts a Tensor into a scalar object, boxing the primitive types.

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

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.

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.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

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.TensorflowExternalModel

copy(String, ModelProvenance) - Method in class org.tribuo.interop.tensorflow.TensorflowModel

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.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() - 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

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.

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<svm_model>) - Method in class org.tribuo.anomaly.libsvm.LibSVMAnomalyTrainer

createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>, List<Model>) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationTrainer

createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Label>, List<svm_model>) - Method in class org.tribuo.classification.libsvm.LibSVMClassificationTrainer

createModel(ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<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>, List<Booster>, XGBoostOutputConverter<T>) - Method in class org.tribuo.common.xgboost.XGBoostTrainer

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

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.

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.

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.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, ExampleTransformer<T>, OutputTransformer<T>, String) - Static method in class org.tribuo.interop.tensorflow.TensorflowExternalModel

Creates a TensorflowExternalModel by loading in a frozen graph.

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.

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.

CRFModel - Class in org.tribuo.classification.sgd.crf

An inference time model for a 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.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
DatasetExplorerOptions() - Constructor for class org.tribuo.data.DatasetExplorer.DatasetExplorerOptions
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
DecisionTreeOptions() - Constructor for class org.tribuo.regression.rtree.TrainTest.DecisionTreeOptions
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.SequenceOutputTransformer: 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.SequenceOutputTransformer: 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_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_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
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_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.LibLinearOptions
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.
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
DenseMatrix(DenseMatrix) - Constructor for class org.tribuo.math.la.DenseMatrix
DenseMatrix(Matrix) - Constructor for class org.tribuo.math.la.DenseMatrix
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
DenseTransformer<T extends Output<T>> - Class in org.tribuo.interop.tensorflow: Converts a sparse example into a dense float vector, then wraps it in a Tensor.
DenseTransformer() - Constructor for class org.tribuo.interop.tensorflow.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
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.MutableDataset: Iterates through the examples, converting implicit zeros into explicit zeros.
depth - Variable in class org.tribuo.common.tree.AbstractTrainingNode
depth - Variable in class org.tribuo.regression.rtree.TrainTest.DecisionTreeOptions
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
deserialise(Session, Map<String, Object>) - Static method in class org.tribuo.interop.tensorflow.TensorflowUtil: Writes a map containing the name of each Tensorflow VariableV2 and the associated parameter array into the supplied session.
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
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.
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<T>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceExampleTransformer: Encodes an example as a feed dict.
encode(List<SequenceExample<T>>, ImmutableFeatureMap) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceExampleTransformer: Encodes a batch of examples as a feed dict.
encode(SequenceExample<T>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceOutputTransformer: Encodes an example's label as a feed dict.
encode(List<SequenceExample<T>>, ImmutableOutputInfo<T>) - Method in interface org.tribuo.interop.tensorflow.sequence.SequenceOutputTransformer: 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
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
EnsembleModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>, ListProvenance<? extends ModelProvenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance
EnsembleModelProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance
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.
EPOCH - Static variable in class org.tribuo.interop.tensorflow.TensorflowTrainer
epochs - Variable in class org.tribuo.classification.sgd.crf.SeqTest.CRFOptions
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.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.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.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.provenance.DatasetProvenance
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.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
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.
ExampleTransformer<T extends Output<T>> - Interface in org.tribuo.interop.tensorflow: TensorFlow support is experimental, and may change without a major version bump.
exampleTransformer - Variable in class org.tribuo.interop.tensorflow.sequence.TensorflowSequenceModel
exampleTransformer - Variable in class org.tribuo.interop.tensorflow.sequence.TensorflowSequenceTrainer
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
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(Tensor<?>) - Method in class org.tribuo.interop.tensorflow.TensorflowExternalModel: 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.
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
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.SimpleFieldExtractor: Extracts the field value, or returns Optional.empty() if it failed to parse.
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.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.
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.TensorflowCheckpointTrainer.TensorflowCheckpointTrainerProvenance
extractTFProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.interop.tensorflow.TensorflowTrainer.TensorflowTrainerProvenance

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
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
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.DecisionTreeOptions
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

G

gamma - Variable in class org.tribuo.regression.libsvm.TrainTest.LibLinearOptions
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.LibLinearOptions
general - Variable in class org.tribuo.regression.rtree.TrainTest.DecisionTreeOptions
general - Variable in class org.tribuo.regression.sgd.TrainTest.SGDOptions
general - Variable in class org.tribuo.regression.slm.TrainTest.LARSOptions
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).
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 MultipleRegression 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.LabelTransformer
generatesProbabilities() - Method in interface org.tribuo.interop.tensorflow.OutputTransformer: Does this OutputTransformer generate probabilities.
generatesProbabilities() - Method in class org.tribuo.interop.tensorflow.RegressorTransformer
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(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.
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
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
getCentroidVectors() - Method in class org.tribuo.clustering.kmeans.KMeansModel: Returns a copy of the centroids.
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.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.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(SparseVector[]) - 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
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 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.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 interface org.tribuo.VariableInfo: The occurrence count of this feature.
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.
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.
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.
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.SplitCharactersTokenizer
getEnd() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
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<Label>) - Method in class org.tribuo.classification.sgd.linear.LinearSGDModel
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.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.TensorflowCheckpointModel: Deep learning models don't do 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.sgd.linear.LinearSGDModel
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.
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.
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.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
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.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.
getGamma() - Method in class org.tribuo.common.libsvm.SVMParameters
getGlobalTransformations() - Method in class org.tribuo.transform.TransformationMap: Gets the global transformations in this TransformationMap.
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
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() - 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
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.TensorflowCheckpointTrainer.TensorflowCheckpointTrainerProvenance
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.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.classification.sgd.linear.LinearSGDTrainer
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.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.TensorflowCheckpointTrainer
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.sgd.linear.LinearSGDTrainer
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 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
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(SparseVector[]) - 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.
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.
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.
getMaxFeatureID() - Method in class org.tribuo.datasource.LibSVMDataSource: Gets the maximum feature ID found.
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.
getMedian() - Method in class org.tribuo.data.columnar.processors.response.Quartile: Returns the median value.
getMemberProvenance() - Method in class org.tribuo.provenance.EnsembleModelProvenance
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.
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.
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.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.
getModelDump() - Method in class org.tribuo.common.xgboost.XGBoostModel: Returns the string model dumps from each Booster.
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.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
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.
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.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.LibLinearOptions
getOptionsDescription() - Method in class org.tribuo.regression.rtree.TrainTest.DecisionTreeOptions
getOptionsDescription() - Method in class org.tribuo.regression.sgd.TrainTest.SGDOptions
getOptionsDescription() - Method in class org.tribuo.regression.slm.TrainTest.LARSOptions
getOptionsDescription() - Method in class org.tribuo.regression.xgboost.TrainTest.XGBoostOptions
getOptionsDescription() - Method in class org.tribuo.util.infotheory.example.InformationTheoryDemo.DemoOptions
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.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.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.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.
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.
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.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.linear.LinearSGDTrainer
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.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.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.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.FeatureHasher
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.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.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.DenseTransformer
getProvenance() - Method in class org.tribuo.interop.tensorflow.ImageTransformer
getProvenance() - Method in class org.tribuo.interop.tensorflow.LabelTransformer
getProvenance() - Method in class org.tribuo.interop.tensorflow.RegressorTransformer
getProvenance() - Method in class org.tribuo.interop.tensorflow.sequence.TensorflowSequenceTrainer
getProvenance() - Method in class org.tribuo.interop.tensorflow.TensorflowCheckpointTrainer
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.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.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.linear.LinearSGDTrainer
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.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.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.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
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
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.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: Returns a copy of the split characters.
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: Returns a copy of the split characters except inside digits.
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.SplitCharactersTokenizer
getStart() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
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.
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() - Method in class org.tribuo.clustering.evaluation.ClusteringMetric
getTarget() - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric: The target for this metric instance.
getTarget() - Method in class org.tribuo.multilabel.evaluation.MultiLabelMetric
getTarget() - Method in class org.tribuo.regression.evaluation.RegressionMetric
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.SplitCharactersTokenizer
getText() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
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 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.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.classification.sgd.linear.LinearSGDModel
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.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.TensorflowCheckpointModel: Deep learning models don't do feature rankings.
getTopFeatures(int) - Method in class org.tribuo.interop.tensorflow.TensorflowExternalModel
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.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.sgd.linear.LinearSGDModel
getTopFeatures(int) - Method in class org.tribuo.regression.slm.SparseLinearModel
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
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.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.
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.SplitCharactersTokenizer
getType() - Method in class org.tribuo.util.tokens.impl.SplitPatternTokenizer
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
getUpperMedian() - Method in class org.tribuo.data.columnar.processors.response.Quartile: The upper quartile value.
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 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.
getVariances() - Method in class org.tribuo.regression.Regressor: The variances of the regressed values, if known.
getWeight(int, int) - Method in class org.tribuo.classification.sgd.crf.CRFParameters
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.regression.sgd.linear.LinearSGDModel
GiniIndex - Class in org.tribuo.classification.dtree.impurity: The Gini index impurity measure.
GiniIndex() - Constructor for class org.tribuo.classification.dtree.impurity.GiniIndex
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
gradients(Pair<Double, SGDVector>, SparseVector) - 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.TensorflowCheckpointTrainer.TensorflowCheckpointTrainerProvenance
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.TensorflowCheckpointTrainer.TensorflowCheckpointTrainerProvenance
GRAPH_LAST_MOD - Static variable in class org.tribuo.interop.tensorflow.TensorflowTrainer.TensorflowTrainerProvenance
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: Same as Tensor.hadamardProductInPlace(org.tribuo.math.la.Tensor, java.util.function.DoubleUnaryOperator), but applies the identity function.
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.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.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.MultiLabel
hashCode() - Method in class org.tribuo.multilabel.MultiLabelFactory
hashCode() - Method in class org.tribuo.multilabel.MultiLabelFactory.MultiLabelFactoryProvenance
hashCode() - Method in class org.tribuo.provenance.DatasetProvenance
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.ModelProvenance
hashCode() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
hashCode() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
hashCode() - Method in class org.tribuo.regression.baseline.DummyRegressionTrainer.DummyRegressionTrainerProvenance: Deprecated.
hashCode() - Method in class org.tribuo.regression.RegressionFactory
hashCode() - Method in class org.tribuo.regression.RegressionFactory.RegressionFactoryProvenance
hashCode() - Method in class org.tribuo.regression.Regressor.DimensionTuple: All regressors have a hashcode based on only the dimension names.
hashCode() - Method in class org.tribuo.regression.Regressor: Regressor's hashcode is based on the hash of the dimension names.
hashCode() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
hashCode() - Method in class org.tribuo.SkeletalVariableInfo
hashCode() - Method in class org.tribuo.transform.TransformationMap.TransformationList
hashCode() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
hashCode() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
hashCode() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
hashCode() - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
hashCode() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
hashCode() - Method in class org.tribuo.util.infotheory.impl.CachedPair: Overridden hashcode.
hashCode() - Method in class org.tribuo.util.infotheory.impl.CachedTriple
hashCode() - Method in class org.tribuo.util.infotheory.impl.Row
hashCode() - Method in class org.tribuo.util.infotheory.impl.WeightCountTuple
HashCodeHasher - Class in org.tribuo.hash: Hashes names using String.hashCode().
HashCodeHasher(String) - Constructor for class org.tribuo.hash.HashCodeHasher
HashCodeHasher.HashCodeHasherProvenance - Class in org.tribuo.hash: Provenance for the HashCodeHasher.
HashCodeHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
hashDim - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
hashDim - Variable in class org.tribuo.data.DataOptions
HashedFeatureMap - Class in org.tribuo.hash: A FeatureMap used by the HashingTrainer to provide feature name hashing and guarantee that the Model does not contain feature name information, but still works with unhashed features names.
Hasher - Class in org.tribuo.hash: An abstract base class for hash functions used to hash the names of features.
Hasher() - Constructor for class org.tribuo.hash.Hasher
hashFeatureMap(Dataset<T>, Hasher) - Static method in class org.tribuo.ImmutableDataset: Creates an immutable shallow copy of the supplied dataset, using the hasher to generate a HashedFeatureMap which transparently maps from the feature name to the hashed variant.
hashingOptions - Variable in class org.tribuo.classification.experiments.AllTrainerOptions
HashingOptions - Class in org.tribuo.hash: An Options implementation which provides CLI arguments for the model hashing functionality.
HashingOptions() - Constructor for class org.tribuo.hash.HashingOptions
HashingOptions.ModelHashingType - Enum in org.tribuo.hash: Supported types of hashes in CLI programs.
HashingSequenceTrainer<T extends Output<T>> - Class in org.tribuo.sequence: A SequenceTrainer that hashes all the feature names on the way in.
HashingSequenceTrainer(SequenceTrainer<T>, Hasher) - Constructor for class org.tribuo.sequence.HashingSequenceTrainer
HashingSequenceTrainer.HashingSequenceTrainerProvenance - Class in org.tribuo.sequence: Provenance for HashingSequenceTrainer.
HashingSequenceTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.sequence.HashingSequenceTrainer.HashingSequenceTrainerProvenance
HashingTrainer<T extends Output<T>> - Class in org.tribuo.hash: A Trainer which hashes the Dataset before the Model is produced.
HashingTrainer(Trainer<T>, Hasher) - Constructor for class org.tribuo.hash.HashingTrainer
hashType - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
hasNext() - Method in class org.tribuo.data.columnar.ColumnarIterator
hasProbabilities() - Method in class org.tribuo.Prediction: Are the scores probabilities?
HeapMerger - Class in org.tribuo.math.util: Merges each SparseVector separately using a PriorityQueue as a heap.
HeapMerger() - Constructor for class org.tribuo.math.util.HeapMerger
Hinge - Class in org.tribuo.classification.sgd.objectives: Hinge loss, scores the correct value margin and any incorrect predictions -margin.
Hinge(double) - Constructor for class org.tribuo.classification.sgd.objectives.Hinge: Construct a hinge objective with the supplied margin.
Hinge() - Constructor for class org.tribuo.classification.sgd.objectives.Hinge: Construct a hinge objective with a margin of 1.0.
HTMLOutput - Class in org.tribuo.util: Utilities for nice HTML output that can be put in wikis and such.
Huber - Class in org.tribuo.regression.sgd.objectives: Huber loss, i.e., a mixture of l2 and l1 losses.
Huber() - Constructor for class org.tribuo.regression.sgd.objectives.Huber
Huber(double) - Constructor for class org.tribuo.regression.sgd.objectives.Huber

I

i - Variable in class org.tribuo.math.la.MatrixTuple
id - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple
IdentityExtractor - Class in org.tribuo.data.columnar.extractors: Extracts the field value and emits it as a String.
IdentityExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.IdentityExtractor: Extracts the String value from the supplied field.
IdentityExtractor(String, String) - Constructor for class org.tribuo.data.columnar.extractors.IdentityExtractor: Extracts the String value from the supplied field.
IdentityProcessor - Class in org.tribuo.data.columnar.processors.field: A FieldProcessor which converts the field name and value into a feature with a value of IdentityProcessor.FEATURE_VALUE.
IdentityProcessor(String) - Constructor for class org.tribuo.data.columnar.processors.field.IdentityProcessor: Constructs a field processor which emits a single feature with a specific value and uses the field name and field value as the feature name.
idIterator() - Method in class org.tribuo.impl.IndexedArrayExample: Iterator over the feature ids and values.
idMap - Variable in class org.tribuo.ImmutableFeatureMap: The map from id numbers to the feature infos.
IDXDataSource<T extends Output<T>> - Class in org.tribuo.datasource: A DataSource which can read IDX formatted data (i.e., MNIST).
IDXDataSource(Path, Path, OutputFactory<T>) - Constructor for class org.tribuo.datasource.IDXDataSource: Constructs an IDXDataSource from the supplied paths.
IDXDataSource.IDXData - Class in org.tribuo.datasource: Java side representation for an IDX file.
IDXDataSource.IDXDataSourceProvenance - Class in org.tribuo.datasource: Provenance class for IDXDataSource.
IDXDataSource.IDXType - Enum in org.tribuo.datasource: The possible IDX input formats.
IDXDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
imageFormat - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
ImageTransformer - Class in org.tribuo.interop.onnx: Image transformer.
ImageTransformer(int, int, int) - Constructor for class org.tribuo.interop.onnx.ImageTransformer
ImageTransformer<T extends Output<T>> - Class in org.tribuo.interop.tensorflow: Image transformer.
ImageTransformer(int, int, int) - Constructor for class org.tribuo.interop.tensorflow.ImageTransformer
ImmutableAnomalyInfo - Class in org.tribuo.anomaly: An ImmutableOutputInfo object for Events.
ImmutableClusteringInfo - Class in org.tribuo.clustering: An ImmutableOutputInfo object for ClusterIDs.
ImmutableClusteringInfo(Map<Integer, MutableLong>) - Constructor for class org.tribuo.clustering.ImmutableClusteringInfo
ImmutableClusteringInfo(ClusteringInfo) - Constructor for class org.tribuo.clustering.ImmutableClusteringInfo
ImmutableDataset<T extends Output<T>> - Class in org.tribuo: This is a Dataset which has an ImmutableFeatureMap to store the feature information.
ImmutableDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.ImmutableDataset: If you call this it's your job to setup outputMap, featureIDMap and fill it with examples.
ImmutableDataset(DataSource<T>, Model<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(DataSource<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.ImmutableDataset: This is dangerous, and should not be used unless you've overridden everything in ImmutableDataset.
ImmutableFeatureMap - Class in org.tribuo: ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
ImmutableFeatureMap(FeatureMap) - Constructor for class org.tribuo.ImmutableFeatureMap: Constructs a new immutable version which is a deep copy of the supplied feature map, generating new ID numbers.
ImmutableFeatureMap(List<VariableInfo>) - Constructor for class org.tribuo.ImmutableFeatureMap: Constructs a new immutable feature map copying the supplied variable infos and generating appropriate ID numbers.
ImmutableFeatureMap() - Constructor for class org.tribuo.ImmutableFeatureMap: Constructs a new empty immutable feature map.
ImmutableLabelInfo - Class in org.tribuo.classification: An ImmutableOutputInfo object for Labels.
ImmutableMultiLabelInfo - Class in org.tribuo.multilabel: An ImmutableOutputInfo for working with multi-label tasks.
ImmutableOutputInfo<T extends Output<T>> - Interface in org.tribuo: An OutputInfo that is fixed, and contains an id number for each valid output.
ImmutableRegressionInfo - Class in org.tribuo.regression: A ImmutableOutputInfo for Regressors.
ImmutableSequenceDataset<T extends Output<T>> - Class in org.tribuo.sequence: This is a SequenceDataset which has an ImmutableFeatureMap to store the feature information.
ImmutableSequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: If you call this it's your job to setup outputIDInfo and featureIDMap.
ImmutableSequenceDataset(SequenceDataSource<T>, SequenceModel<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
ImmutableSequenceDataset(SequenceDataSource<T>, FeatureMap, OutputInfo<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset
ImmutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, FeatureMap, OutputInfo<T>, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: Creates a dataset from a data source.
ImmutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: Creates a dataset from a data source.
ImmutableSequenceDataset(DataProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: This is dangerous, and should not be used unless you've overridden everything in ImmutableSequenceDataset.
impurity(double[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity: Calculates the impurity assuming the inputs are counts.
impurity(float[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity: Calculates the impurity assuming the input are fractional counts.
impurity(int[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity: Calculates the impurity assuming the input are counts.
impurity(Map<String, Double>) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity: Takes a Map for weighted counts.
impurity(float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
impurity(float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
impurity(float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity: Calculates the impurity based on the supplied weights and targets.
impurity(int[], int, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity: Calculates the weighted impurity of the targets specified in the indices array.
impurity(List<int[]>, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity: Calculates the weighted impurity of the targets specified in all the indices arrays.
impurity(int[], float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity: Calculates the weighted impurity of the targets specified in the indices array.
impurity(IntArrayContainer, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity: Calculates the weighted impurity of the targets specified in the indices container.
impurity - Variable in class org.tribuo.regression.rtree.impurity.RegressorImpurity.ImpurityTuple
impurityNormed(double[]) - Method in class org.tribuo.classification.dtree.impurity.Entropy
impurityNormed(double[]) - Method in class org.tribuo.classification.dtree.impurity.GiniIndex
impurityNormed(double[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity: Calculates the impurity, assuming it's input is a normalized probability distribution.
impurityTuple(int[], int, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
impurityTuple(List<int[]>, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanAbsoluteError
impurityTuple(int[], int, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
impurityTuple(List<int[]>, float[], float[]) - Method in class org.tribuo.regression.rtree.impurity.MeanSquaredError
impurityTuple(int[], int, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity: Calculates the weighted impurity of the targets specified in the indices array.
impurityTuple(List<int[]>, float[], float[]) - Method in interface org.tribuo.regression.rtree.impurity.RegressorImpurity: Calculates the weighted impurity of the targets specified in all the indices arrays.
ImpurityTuple(float, float) - Constructor for class org.tribuo.regression.rtree.impurity.RegressorImpurity.ImpurityTuple
impurityType - Variable in class org.tribuo.regression.rtree.TrainTest.DecisionTreeOptions
impurityWeighted(double[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity: Calculates the impurity assuming the inputs are weighted counts normalizing by their sum.
impurityWeighted(float[]) - Method in interface org.tribuo.classification.dtree.impurity.LabelImpurity: Calculates the impurity assuming the input are weighted counts, normalizing by their sum.
incr - Variable in class org.tribuo.util.tokens.universal.Range
incrementalTrain(Dataset<T>, U) - Method in interface org.tribuo.IncrementalTrainer: Incrementally trains the supplied model with the new data.
IncrementalTrainer<T extends Output<T>,U extends Model<T>> - Interface in org.tribuo: An interface for incremental training of Models.
IndependentMultiLabelModel - Class in org.tribuo.multilabel.baseline: A Model which wraps n binary models, where n is the size of the MultiLabel domain.
IndependentMultiLabelTrainer - Class in org.tribuo.multilabel.baseline: Trains n independent binary Models, each of which predicts a single Label.
IndependentMultiLabelTrainer(Trainer<Label>) - Constructor for class org.tribuo.multilabel.baseline.IndependentMultiLabelTrainer
IndependentRegressionTreeModel - Class in org.tribuo.regression.rtree: A Model wrapped around a list of decision tree root Nodes used to generate independent predictions for each dimension in a regression.
index - Variable in class org.tribuo.math.la.VectorTuple
index - Variable in class org.tribuo.util.IntDoublePair
IndexedArrayExample<T extends Output<T>> - Class in org.tribuo.impl: A version of ArrayExample which also has the id numbers.
IndexedArrayExample(IndexedArrayExample<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample: Copy constructor.
IndexedArrayExample(Example<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample: This constructor removes unknown features.
IndexedArrayExample.FeatureTuple - Class in org.tribuo.impl: A tuple of the feature name, id and value.
IndexExtractor - Class in org.tribuo.data.columnar.extractors: An Extractor with special casing for loading the index from a Row.
IndexExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.IndexExtractor: Extracts the index, writing to the supplied metadata field name.
IndexExtractor() - Constructor for class org.tribuo.data.columnar.extractors.IndexExtractor: Extracts the index writing to the default metadata field name Example.NAME.
indexOf(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
indexOfMax() - Method in class org.tribuo.math.la.DenseVector
indexOfMax() - Method in interface org.tribuo.math.la.SGDVector: Returns the index of the maximum value.
indexOfMax() - Method in class org.tribuo.math.la.SparseVector
indexOfMax() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
indices - Variable in class org.tribuo.Dataset: The indices of the shuffled order.
indices - Variable in class org.tribuo.math.la.SparseVector
indices() - Method in class org.tribuo.regression.rtree.impl.InvertedFeature
InformationTheory - Class in org.tribuo.util.infotheory: A class of (discrete) information theoretic functions.
InformationTheory.GTestStatistics - Class in org.tribuo.util.infotheory: An immutable named tuple containing the statistics from a G test.
InformationTheoryDemo - Class in org.tribuo.util.infotheory.example: Demo showing how to calculate various mutual informations and entropies.
InformationTheoryDemo() - Constructor for class org.tribuo.util.infotheory.example.InformationTheoryDemo
InformationTheoryDemo.DemoOptions - Class in org.tribuo.util.infotheory.example
InformationTheoryDemo.DistributionType - Enum in org.tribuo.util.infotheory.example
INIT - Static variable in class org.tribuo.interop.tensorflow.TensorflowTrainer
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaDelta
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaGrad
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaGradRDA
initialise(Parameters) - Method in class org.tribuo.math.optimisers.Adam
initialise(Parameters) - Method in class org.tribuo.math.optimisers.ParameterAveraging
initialise(Parameters) - Method in class org.tribuo.math.optimisers.Pegasos
initialise(Parameters) - Method in class org.tribuo.math.optimisers.RMSProp
initialise(Parameters) - Method in class org.tribuo.math.optimisers.SGD
initialise(Parameters) - Method in interface org.tribuo.math.StochasticGradientOptimiser: Initialises the gradient optimiser.
initialiseCentroids(int, Dataset<ClusterID>, ImmutableFeatureMap, SplittableRandom) - Static method in class org.tribuo.clustering.kmeans.KMeansTrainer: Initialisation method called at the start of each train call.
initialLearningRate - Variable in class org.tribuo.math.optimisers.SGD
initOp - Variable in class org.tribuo.interop.tensorflow.sequence.TensorflowSequenceModel
initOp - Variable in class org.tribuo.interop.tensorflow.sequence.TensorflowSequenceTrainer
innerGetExcuse(Example<Label>, double[][]) - Method in class org.tribuo.classification.liblinear.LibLinearClassificationModel: The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
innerGetExcuse(Example<T>, double[][]) - Method in class org.tribuo.common.liblinear.LibLinearModel: The call to getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
innerGetExcuse(Example<Regressor>, double[][]) - Method in class org.tribuo.regression.liblinear.LibLinearRegressionModel: The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
innerModel - Variable in class org.tribuo.classification.explanations.lime.LIMEBase
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.common.nearest.KNNModel: Uses the model to predict the output for multiple examples.
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.interop.ExternalModel
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.interop.tensorflow.TensorflowModel
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.Model: Called by the base implementations of Model.predict(Iterable) and Model.predict(Dataset).
innerTrainer - Variable in class org.tribuo.classification.ensemble.AdaBoostTrainer
innerTrainer - Variable in class org.tribuo.ensemble.BaggingTrainer
inPlaceAdd(double[], double[]) - Static method in class org.tribuo.util.Util
inPlaceAdd(float[], float[]) - Static method in class org.tribuo.util.Util
inplaceNormalizeToDistribution(double[]) - Static method in class org.tribuo.util.Util
inplaceNormalizeToDistribution(float[]) - Static method in class org.tribuo.util.Util
inPlaceSubtract(double[], double[]) - Static method in class org.tribuo.util.Util
inPlaceSubtract(float[], float[]) - Static method in class org.tribuo.util.Util
INPUT_NAME - Static variable in class org.tribuo.interop.tensorflow.TensorflowModel
inputFormat - Variable in class org.tribuo.classification.experiments.Test.ConfigurableTestOptions
inputFormat - Variable in class org.tribuo.data.DataOptions
inputModel - Variable in class org.tribuo.json.StripProvenance.StripProvenanceOptions
inputPath - Variable in class org.tribuo.data.sql.SQLToCSV.SQLToCSVOptions
inputPath - Variable in class org.tribuo.data.text.SplitTextData.TrainTestSplitOptions
inputType - Variable in class org.tribuo.interop.tensorflow.TrainTest.TensorflowOptions
INSTANCE_VALUES - Static variable in class org.tribuo.provenance.ModelProvenance
instanceProvenance - Variable in class org.tribuo.provenance.ModelProvenance
IntArrayContainer - Class in org.tribuo.common.tree.impl: An array container which maintains the array and the size.
IntArrayContainer(int) - Constructor for class org.tribuo.common.tree.impl.IntArrayContainer: Constructs a new int array container with the specified initial backing array size.
IntDoublePair - Class in org.tribuo.util: A Pair of a primitive int and a primitive double.
IntDoublePair(int, double) - Constructor for class org.tribuo.util.IntDoublePair
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseMatrix
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseSparseMatrix: Only implemented for DenseMatrix.
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor: Updates this Tensor by adding all the values from the intersection with other.
intersectAndAddInPlace(Tensor) - Method in interface org.tribuo.math.la.Tensor: Same as Tensor.intersectAndAddInPlace(org.tribuo.math.la.Tensor, java.util.function.DoubleUnaryOperator), but applies the identity function.
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
intersection(SparseVector) - Method in class org.tribuo.math.la.SparseVector: Generates an array of the indices that are active in both this vector and other
IntExtractor - Class in org.tribuo.data.columnar.extractors: Extracts the field value and converts it to a int.
IntExtractor(String) - Constructor for class org.tribuo.data.columnar.extractors.IntExtractor: Extracts a int value from the supplied field name.
IntExtractor(String, String) - Constructor for class org.tribuo.data.columnar.extractors.IntExtractor: Extracts a int value from the supplied field name.
invalidMultiDimSparseExample() - Static method in class org.tribuo.regression.example.RegressionDataGenerator: Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.anomaly.example.AnomalyDataGenerator: Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.classification.example.LabelledDataGenerator: Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.clustering.example.ClusteringDataGenerator: Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.multilabel.example.MultiLabelDataGenerator: Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invalidSparseExample() - Static method in class org.tribuo.regression.example.RegressionDataGenerator: Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
invertData(Dataset<Regressor>) - Static method in class org.tribuo.regression.rtree.impl.RegressorTrainingNode: Inverts a training dataset from row major to column major.
InvertedFeature - Class in org.tribuo.regression.rtree.impl: Internal datastructure for implementing a decision tree.
InvertedFeature(double, int[]) - Constructor for class org.tribuo.regression.rtree.impl.InvertedFeature
InvertedFeature(double, int) - Constructor for class org.tribuo.regression.rtree.impl.InvertedFeature
IS_SEQUENCE - Static variable in interface org.tribuo.provenance.TrainerProvenance
IS_SNAPSHOT - Static variable in class org.tribuo.Tribuo: Is this a snapshot build.
IS_TRAINING - Static variable in class org.tribuo.interop.tensorflow.TensorflowTrainer
isAnomaly() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
isAnomaly() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
isAnomaly() - Method in interface org.tribuo.common.libsvm.SVMType: Is this an anomaly detection algorithm.
isAnomaly() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
isBinary(Feature) - Static method in class org.tribuo.impl.BinaryFeaturesExample
isClassification() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
isClassification() - Method in class org.tribuo.classification.liblinear.LinearClassificationType
isClassification() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
isClassification() - Method in interface org.tribuo.common.liblinear.LibLinearType: Is this class a Classification algorithm?
isClassification() - Method in interface org.tribuo.common.libsvm.SVMType: Is this a classification algorithm.
isClassification() - Method in class org.tribuo.regression.liblinear.LinearRegressionType
isClassification() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
isConfigured() - Method in class org.tribuo.data.columnar.RowProcessor: Returns true if the regexes have been expanded into field processors.
isDense() - Method in class org.tribuo.MutableDataset: Is the dataset dense (i.e., do all features in the domain have a value in each example).
isDense() - Method in class org.tribuo.provenance.DatasetProvenance: Is the Dataset dense?
isDigit(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer: A quick check for whether a character is a digit.
isEmpty() - Method in class org.tribuo.util.infotheory.impl.RowList
isGenerateNgrams() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
isGenerateUnigrams() - Method in class org.tribuo.util.tokens.universal.UniversalTokenizer
isLeaf() - Method in class org.tribuo.common.tree.AbstractTrainingNode
isLeaf() - Method in class org.tribuo.common.tree.LeafNode
isLeaf() - Method in interface org.tribuo.common.tree.Node: Is it a leaf node?
isLeaf() - Method in class org.tribuo.common.tree.SplitNode
isLetterOrDigit(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer: A quick check for whether a character should be kept in a word or should be removed from the word if it occurs at one of the ends.
isNgram(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer: A quick check for a character in a language that may not separate words with whitespace (includes Arabic, CJK, and Thai).
isNu() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
isNu() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
isNu() - Method in interface org.tribuo.common.libsvm.SVMType: Is this a nu-SVM.
isNu() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
isProbabilistic() - Method in interface org.tribuo.classification.sgd.LabelObjective: Does the objective function score probabilities or not?
isProbabilistic() - Method in class org.tribuo.classification.sgd.objectives.Hinge: Returns false.
isProbabilistic() - Method in class org.tribuo.classification.sgd.objectives.LogMulticlass: Returns true.
isRegression() - Method in class org.tribuo.anomaly.libsvm.SVMAnomalyType
isRegression() - Method in class org.tribuo.classification.liblinear.LinearClassificationType
isRegression() - Method in class org.tribuo.classification.libsvm.SVMClassificationType
isRegression() - Method in interface org.tribuo.common.liblinear.LibLinearType: Is this class a Regression algorithm?
isRegression() - Method in interface org.tribuo.common.libsvm.SVMType: Is this a regression algorithm.
isRegression() - Method in class org.tribuo.regression.liblinear.LinearRegressionType
isRegression() - Method in class org.tribuo.regression.libsvm.SVMRegressionType
isSampled() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance: Is this view from a bootstrap sample.
isSequence() - Method in class org.tribuo.provenance.DatasetProvenance: Is it a sequence dataset?
isSequence() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance: Is this a sequence trainer.
isSplitCharacter(char) - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer: Is this character a split character for this tokenizer instance.
isSplitXDigitCharacter(char) - Method in class org.tribuo.util.tokens.impl.SplitCharactersTokenizer: Is this character a split character except inside a digit for this tokenizer instance.
isWeighted() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance: Is this view a weighted bootstrap sample.
isWhitespace(char) - Static method in class org.tribuo.util.tokens.universal.UniversalTokenizer: A quick check for whether a character is whitespace.
isZeroIndexed() - Method in class org.tribuo.datasource.LibSVMDataSource: Returns true if this dataset is zero indexed, false otherwise (i.e., it starts from 1).
iteration - Variable in class org.tribuo.math.optimisers.SGD
iterations - Variable in class org.tribuo.clustering.kmeans.KMeansOptions
iterations - Variable in class org.tribuo.clustering.kmeans.TrainTest.KMeansOptions
iterations - Variable in class org.tribuo.regression.slm.TrainTest.LARSOptions
iterator() - Method in class org.tribuo.anomaly.ImmutableAnomalyInfo
iterator() - Method in class org.tribuo.classification.ImmutableLabelInfo
iterator() - Method in class org.tribuo.clustering.ImmutableClusteringInfo
iterator() - Method in class org.tribuo.data.columnar.ColumnarDataSource
iterator() - Method in class org.tribuo.data.csv.CSVLoader.CSVLoaderProvenance
iterator() - Method in class org.tribuo.data.text.DirectoryFileSource
iterator() - Method in class org.tribuo.data.text.TextDataSource
iterator() - Method in class org.tribuo.dataset.DatasetView
iterator() - Method in class org.tribuo.Dataset
iterator() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
iterator() - Method in class org.tribuo.datasource.AggregateDataSource
iterator() - Method in class org.tribuo.datasource.IDXDataSource
iterator() - Method in class org.tribuo.datasource.LibSVMDataSource
iterator() - Method in class org.tribuo.datasource.ListDataSource
iterator() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
iterator() - Method in class org.tribuo.FeatureMap
iterator() - Method in class org.tribuo.impl.ArrayExample
iterator() - Method in class org.tribuo.impl.BinaryFeaturesExample
iterator() - Method in class org.tribuo.impl.ListExample
iterator() - Method in class org.tribuo.math.la.DenseMatrix
iterator() - Method in class org.tribuo.math.la.DenseSparseMatrix
iterator() - Method in class org.tribuo.math.la.DenseVector
iterator() - Method in class org.tribuo.math.la.SparseVector
iterator() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
iterator() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
iterator() - Method in class org.tribuo.multilabel.ImmutableMultiLabelInfo
iterator() - Method in class org.tribuo.provenance.DatasetProvenance
iterator() - Method in class org.tribuo.provenance.EnsembleModelProvenance
iterator() - Method in class org.tribuo.provenance.EvaluationProvenance
iterator() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
iterator() - Method in class org.tribuo.provenance.ModelProvenance
iterator() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
iterator() - Method in class org.tribuo.regression.example.GaussianDataSource
iterator() - Method in class org.tribuo.regression.ImmutableRegressionInfo
iterator() - Method in class org.tribuo.regression.Regressor.DimensionTuple
iterator() - Method in class org.tribuo.regression.Regressor
iterator() - Method in class org.tribuo.regression.rtree.impl.TreeFeature
iterator() - Method in class org.tribuo.sequence.SequenceDataset
iterator() - Method in class org.tribuo.sequence.SequenceExample
iterator() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
iterator() - Method in class org.tribuo.util.infotheory.impl.RowList

J

j - Variable in class org.tribuo.math.la.MatrixTuple
JOINER - Static variable in class org.tribuo.data.columnar.ColumnarFeature
jointCounts - Variable in class org.tribuo.util.infotheory.impl.PairDistribution
jointEntropy(List<T1>, List<T2>) - Static method in class org.tribuo.util.infotheory.InformationTheory: Calculates the Shannon joint entropy of two arrays, using histogram probability estimators.
jointEntropy(ArrayList<T1>, ArrayList<T2>, ArrayList<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory: Calculates the Shannon/Guiasu weighted joint entropy of two arrays, using histogram probability estimators.
jointMI(List<T1>, List<T2>, List<T3>) - Static method in class org.tribuo.util.infotheory.InformationTheory: Calculates the discrete Shannon joint mutual information, using histogram probability estimators.
jointMI(TripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.InformationTheory: Calculates the discrete Shannon joint mutual information, using histogram probability estimators.
jointMI(List<T1>, List<T2>, List<T3>, List<Double>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory: Calculates the discrete weighted joint mutual information, using histogram probability estimators.
jointMI(WeightedTripleDistribution<T1, T2, T3>) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
jointMI(TripleDistribution<T1, T2, T3>, Map<?, Double>, WeightedInformationTheory.VariableSelector) - Static method in class org.tribuo.util.infotheory.WeightedInformationTheory
JointRegressorTrainingNode - Class in org.tribuo.regression.rtree.impl: A decision tree node used at training time.
JointRegressorTrainingNode(RegressorImpurity, Dataset<Regressor>, boolean) - Constructor for class org.tribuo.regression.rtree.impl.JointRegressorTrainingNode: Constructor which creates the inverted file.
JsonDataSource<T extends Output<T>> - Class in org.tribuo.json: A DataSource for loading data from a JSON text file and applying FieldProcessors to it.
JsonDataSource(Path, RowProcessor<T>, boolean) - Constructor for class org.tribuo.json.JsonDataSource: Creates a JsonDataSource using the specified RowProcessor to process the data.
JsonDataSource(URI, RowProcessor<T>, boolean) - Constructor for class org.tribuo.json.JsonDataSource: Creates a JsonDataSource using the specified RowProcessor to process the data.
JsonDataSource.JsonDataSourceProvenance - Class in org.tribuo.json: Provenance for JsonDataSource.
JsonDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.json.JsonDataSource.JsonDataSourceProvenance
JsonFileIterator - Class in org.tribuo.json: An iterator for JSON format files converting them into a format suitable for RowProcessor.
JsonFileIterator(Reader) - Constructor for class org.tribuo.json.JsonFileIterator: Builds a JsonFileIterator for the supplied Reader.
JsonFileIterator(URI) - Constructor for class org.tribuo.json.JsonFileIterator: Builds a CSVIterator for the supplied URI.
JsonUtil - Class in org.tribuo.json: Utilities for interacting with JS