- 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
-
- 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
-
- 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
DataSource
s, and round-robins the iterators.
- AggregateDataSource(List<DataSource<T>>) - Constructor for class org.tribuo.datasource.AggregateDataSource
-
- AggregateDataSource.AggregateDataSourceProvenance - Class in org.tribuo.datasource
-
- 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
-
- AnomalyEvaluator - Class in org.tribuo.anomaly.evaluation
-
- 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
-
- 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
Transformer
s 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
-
- 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
-
- 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 Tensor
s.
- 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
-
- ClusteringEvaluator - Class in org.tribuo.clustering.evaluation
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- constructInfoForExternalModel(Map<Regressor, Integer>) - Method in class org.tribuo.regression.RegressionFactory
-
- contains(int) - Method in class org.tribuo.impl.IndexedArrayExample
-
Does this example contain a feature with id i.
- contains(String) - Method in class org.tribuo.multilabel.MultiLabel
-
Does this MultiLabel contain this string?
- contains(Label) - Method in class org.tribuo.multilabel.MultiLabel
-
Does this MultiLabel contain this Label?
- contains(Object) - Method in class org.tribuo.util.infotheory.impl.RowList
-
- containsAll(Collection<?>) - Method in class org.tribuo.util.infotheory.impl.RowList
-
- containsMetadata(String) - Method in class org.tribuo.Example
-
Test if the metadata contains the supplied key.
- Context(Model<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelMetric.Context
-
- Context(SequenceModel<Label>, List<Prediction<Label>>) - Constructor for class org.tribuo.classification.evaluation.LabelMetric.Context
-
- convert(SequenceExample<T>, ImmutableFeatureMap) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
-
- convert(SequenceExample<Label>, ImmutableFeatureMap, ImmutableOutputInfo<Label>) - Static method in class org.tribuo.classification.sgd.crf.CRFModel
-
- convert(byte) - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType
-
Converts the byte into the enum.
- 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
Prediction
s.
- 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
ArrayList
s.
- 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
-
- 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
Prediction
s 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
-
- createModel(Map<String, T>, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<Regressor>) - Method in class org.tribuo.regression.impl.SkeletalIndependentRegressionTrainer
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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.
- 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
Model
s.
- 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
-
- 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
-
- evaluate(SequenceModel<T>, SequenceDataSource<T>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator
-
- 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
-
- 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
-
- 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
-
- Event - Class in org.tribuo.anomaly
-
- 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
-
- 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
-
- Example(T) - Constructor for class org.tribuo.Example
-
- 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
-
- expandRegexMapping(Model<T>) - Method in class org.tribuo.data.columnar.RowProcessor
-
- expandRegexMapping(ImmutableFeatureMap) - Method in class org.tribuo.data.columnar.RowProcessor
-
- expandRegexMapping(Collection<String>) - Method in class org.tribuo.data.columnar.RowProcessor
-
- 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
Output
s in LibLinear's format.
- extractData(Dataset<T>, ImmutableOutputInfo<T>, ImmutableFeatureMap) - Method in class org.tribuo.common.libsvm.LibSVMTrainer
-
Extracts the features and
Output
s 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- get(String) - Method in class org.tribuo.ImmutableFeatureMap
-
- 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
Event
s.
- 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
Label
s that this LabelInfo has seen.
- getDomain() - Method in class org.tribuo.classification.LabelInfo
-
Returns the set of possible
Label
s 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- getNormalizer() - Method in class org.tribuo.classification.sgd.objectives.Hinge
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- ImmutableClusteringInfo - Class in org.tribuo.clustering
-
- 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
-
- ImmutableDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.ImmutableDataset
-
If you call this it's your job to setup outputMap, featureIDMap and fill it with examples.
- ImmutableDataset(DataSource<T>, Model<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
-
Creates a dataset from a data source.
- ImmutableDataset(DataSource<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
-
Creates a dataset from a data source.
- ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
-
Creates a dataset from a data source.
- ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset
-
Creates a dataset from a data source.
- ImmutableDataset(DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.ImmutableDataset
-
This is dangerous, and should not be used unless you've overridden everything in ImmutableDataset.
- ImmutableFeatureMap - Class in org.tribuo
-
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
- ImmutableFeatureMap(FeatureMap) - Constructor for class org.tribuo.ImmutableFeatureMap
-
Constructs a new immutable version which is a deep copy of the supplied feature map, generating new ID numbers.
- ImmutableFeatureMap(List<VariableInfo>) - Constructor for class org.tribuo.ImmutableFeatureMap
-
Constructs a new immutable feature map copying the supplied variable infos and generating appropriate ID numbers.
- ImmutableFeatureMap() - Constructor for class org.tribuo.ImmutableFeatureMap
-
Constructs a new empty immutable feature map.
- ImmutableLabelInfo - Class in org.tribuo.classification
-
An ImmutableOutputInfo object for Labels.
- ImmutableMultiLabelInfo - Class in org.tribuo.multilabel
-
An ImmutableOutputInfo for working with multi-label tasks.
- ImmutableOutputInfo<T extends Output<T>> - Interface in org.tribuo
-
An
OutputInfo
that is fixed, and contains an id number for each valid output.
- ImmutableRegressionInfo - Class in org.tribuo.regression
-
- ImmutableSequenceDataset<T extends Output<T>> - Class in org.tribuo.sequence
-
- 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
Model
s.
- 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
Model
s, 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
Node
s 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
-
- 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
-
- intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
-
- intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
-
- intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor
-
Updates this
Tensor
by adding all the values from the intersection with
other
.
- intersectAndAddInPlace(Tensor) - Method in interface org.tribuo.math.la.Tensor
-
- intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
-
- intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
-
- intersection(SparseVector) - Method in class org.tribuo.math.la.SparseVector
-
Generates an array of the indices that are active in both this
vector and other
- 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
-