Index (Core 4.3.2 API)

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

A

AbstractEvaluator<T,C,E,M> - Class in org.tribuo.evaluation: Base class for evaluators.
AbstractEvaluator() - Constructor for class org.tribuo.evaluation.AbstractEvaluator
AbstractSequenceEvaluator<T,C,E,M> - Class in org.tribuo.sequence: Base class for sequence evaluators.
AbstractSequenceEvaluator() - Constructor for class org.tribuo.sequence.AbstractSequenceEvaluator
add - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Adds the specified constant.
add() - Static method in interface org.tribuo.util.Merger: A merger which adds the elements.
add(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that adds the operand to each value.
add(String) - Method in class org.tribuo.impl.BinaryFeaturesExample: Adds a single feature with a value of 1.
add(String, double) - Method in class org.tribuo.impl.ArrayExample: Adds a single feature.
add(String, double) - Method in class org.tribuo.MutableFeatureMap: Adds an occurrence of a feature with a given name.
add(Example<T>) - Method in class org.tribuo.ImmutableDataset: Adds an Example to the dataset, which will remove features with unknown names.
add(Example<T>) - Method in class org.tribuo.MutableDataset: Adds an example to the dataset, which observes the output and each feature value.
add(Example<T>, Merger) - Method in class org.tribuo.ImmutableDataset: Adds a Example to the dataset, which will insert feature ids, remove unknown features and sort the examples by the feature ids (merging duplicate ids).
add(Feature) - Method in class org.tribuo.Example: Adds a feature.
add(Feature) - Method in class org.tribuo.impl.ArrayExample
add(Feature) - Method in class org.tribuo.impl.BinaryFeaturesExample: Adds a feature to this example.
add(Feature) - Method in class org.tribuo.impl.IndexedArrayExample
add(Feature) - Method in class org.tribuo.impl.ListExample
add(SequenceExample<T>) - Method in class org.tribuo.sequence.ImmutableSequenceDataset: Adds a SequenceExample to the dataset, which will insert feature ids, remove unknown features and sort the examples by the feature ids.
add(SequenceExample<T>) - Method in class org.tribuo.sequence.MutableSequenceDataset: Adds a SequenceExample to this dataset.
add(SequenceExample<T>, Merger) - Method in class org.tribuo.sequence.ImmutableSequenceDataset: Adds a SequenceExample to the dataset, which will insert feature ids, remove unknown features and sort the examples by the feature ids.
addAll(Collection<? extends Example<T>>) - Method in class org.tribuo.MutableDataset: Adds all the Examples in the supplied collection to this dataset.
addAll(Collection<? extends Feature>) - Method in class org.tribuo.Example: Adds a collection of features.
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.ArrayExample
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.BinaryFeaturesExample: Adds a collection of features to this example.
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.IndexedArrayExample
addAll(Collection<? extends Feature>) - Method in class org.tribuo.impl.ListExample
addAll(Collection<SequenceExample<T>>) - Method in class org.tribuo.sequence.MutableSequenceDataset: Adds all the SequenceExamples in the supplied collection to this dataset.
addExample(Example<T>) - Method in class org.tribuo.sequence.SequenceExample: Adds an Example to this sequence.
AggregateConfigurableDataSource<T> - Class in org.tribuo.datasource: Aggregates multiple ConfigurableDataSources, uses AggregateDataSource.IterationOrder to control the iteration order.
AggregateConfigurableDataSource(List<ConfigurableDataSource<T>>) - Constructor for class org.tribuo.datasource.AggregateConfigurableDataSource: Creates an aggregate data source which will iterate the provided sources in the order of the list (i.e., using AggregateDataSource.IterationOrder.SEQUENTIAL.
AggregateConfigurableDataSource(List<ConfigurableDataSource<T>>, AggregateDataSource.IterationOrder) - Constructor for class org.tribuo.datasource.AggregateConfigurableDataSource: Creates an aggregate data source using the supplied sources and iteration order.
AggregateConfigurableDataSource.AggregateConfigurableDataSourceProvenance - Class in org.tribuo.datasource: Provenance for the AggregateConfigurableDataSource.
AggregateConfigurableDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.AggregateConfigurableDataSource.AggregateConfigurableDataSourceProvenance: Deserialization constructor.
AggregateDataSource<T> - Class in org.tribuo.datasource: Aggregates multiple DataSources, uses AggregateDataSource.IterationOrder to control the iteration order.
AggregateDataSource(List<DataSource<T>>) - Constructor for class org.tribuo.datasource.AggregateDataSource: Creates an aggregate data source which will iterate the provided sources in the order of the list (i.e., using AggregateDataSource.IterationOrder.SEQUENTIAL.
AggregateDataSource(List<DataSource<T>>, AggregateDataSource.IterationOrder) - Constructor for class org.tribuo.datasource.AggregateDataSource: Creates an aggregate data source using the supplied sources and iteration order.
AggregateDataSource.AggregateDataSourceProvenance - Class in org.tribuo.datasource: Provenance for the AggregateDataSource.
AggregateDataSource.IterationOrder - Enum in org.tribuo.datasource: Specifies the iteration order of the inner sources.
AggregateDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance: Deserialization constructor.
ALL_OUTPUTS - Static variable in class org.tribuo.Model: Used in getTopFeatures when the Model doesn't support per output feature lists.
allProvenances() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
allProvenances() - Method in class org.tribuo.dataset.MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance
allProvenances() - Method in class org.tribuo.dataset.SelectedFeatureDataset.SelectedFeatureDatasetProvenance
allProvenances() - Method in class org.tribuo.provenance.DatasetProvenance: Returns a list of all the provenances.
allProvenances() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
apply(E) - Method in interface org.tribuo.evaluation.EvaluationRenderer: Convert the evaluation to a string.
applyTransformerList(double, List<Transformer>) - Static method in class org.tribuo.transform.TransformerMap: Applies a List of Transformers to the supplied double value, returning the transformed value.
ARCH_STRING - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the architecture name field.
archString - Variable in class org.tribuo.provenance.ModelProvenance: The system CPU architecture string.
argmax(List<R>, Function<R, Double>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Calculates the argmax of a metric across the supplied evaluations.
argmax(List<T>) - Static method in class org.tribuo.util.Util: Find the index of the maximum value in a list.
argmax(EvaluationMetric<T, C>, List<? extends Model<T>>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Calculates the argmax of a metric across the supplied models (i.e., the index of the model which performed the best).
argmax(EvaluationMetric<T, C>, Model<T>, List<? extends Dataset<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Calculates the argmax of a metric across the supplied datasets.
argmin(List<T>) - Static method in class org.tribuo.util.Util: Find the index of the minimum value in a list.
ArrayExample<T> - Class in org.tribuo.impl: An Example backed by two arrays, one of String and one of double.
ArrayExample(Example<T>) - Constructor for class org.tribuo.impl.ArrayExample: Copy constructor.
ArrayExample(T) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output.
ArrayExample(T, float) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output and a weight.
ArrayExample(T, float, int) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output and a weight, with an initial size for the feature arrays.
ArrayExample(T, float, Map<String, Object>) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output, a weight and the metadata.
ArrayExample(T, String[], double[]) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output, an array of names and an array of values.
ArrayExample(T, String[], double[], Map<String, Object>) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output, an array of names and an array of values.
ArrayExample(T, List<? extends Feature>) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output and a list of features.
ArrayExample(T, Map<String, Object>) - Constructor for class org.tribuo.impl.ArrayExample: Constructs an example from an output and the metadata.
ArrayExample(T, Example<U>, float) - Constructor for class org.tribuo.impl.ArrayExample: Clones an example's features, but uses the supplied output and weight.
asMap() - Method in interface org.tribuo.evaluation.Evaluation: Get a map of all the metrics stored in this evaluation.
asMap() - Method in interface org.tribuo.sequence.SequenceEvaluation: Get a map of all the metrics stored in this evaluation.
auc(double[], double[]) - Static method in class org.tribuo.util.Util: Calculates the area under the curve, bounded below by the x axis.

B

BaggingTrainer<T> - Class in org.tribuo.ensemble: A Trainer that wraps another trainer and produces a bagged ensemble.
BaggingTrainer() - Constructor for class org.tribuo.ensemble.BaggingTrainer: For the configuration system.
BaggingTrainer(Trainer<T>, EnsembleCombiner<T>, int) - Constructor for class org.tribuo.ensemble.BaggingTrainer: Constructs a bagging trainer with the supplied parameters using Trainer.DEFAULT_SEED as the RNG seed.
BaggingTrainer(Trainer<T>, EnsembleCombiner<T>, int, long) - Constructor for class org.tribuo.ensemble.BaggingTrainer: Constructs a bagging trainer with the supplied parameters.
BIAS_FEATURE - Static variable in class org.tribuo.Model: Used to denote the bias feature in a linear model.
binarise - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Binarises the output around 1.0.
binarise() - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that sets negative and zero values to zero and positive values to one.
BinaryFeaturesExample<T> - Class in org.tribuo.impl: An Example backed by a single array of feature names.
BinaryFeaturesExample(Example<T>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Copy constructor.
BinaryFeaturesExample(T) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Constructs an example from an output.
BinaryFeaturesExample(T, float) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Constructs an example from an output and a weight.
BinaryFeaturesExample(T, float, int) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Constructs an example from an output and a weight, with an initial size for the feature arrays.
BinaryFeaturesExample(T, float, Map<String, Object>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Constructs an example from an output, a weight and the metadata.
BinaryFeaturesExample(T, String[]) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Constructs an example from an output and an array of names.
BinaryFeaturesExample(T, List<? extends Feature>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Constructs an example from an output and a list of features.
BinaryFeaturesExample(T, Map<String, Object>) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Constructs an example from an output and the metadata.
BinaryFeaturesExample(T, Example<U>, float) - Constructor for class org.tribuo.impl.BinaryFeaturesExample: Clones an example's features, but uses the supplied output and weight.
binarySearch(List<? extends Comparable<? super T>>, T) - Static method in class org.tribuo.util.Util: A binary search function.
binarySearch(List<? extends Comparable<? super T>>, T, int, int) - Static method in class org.tribuo.util.Util: A binary search function.
binarySearch(List<? extends T>, int, ToIntFunction<T>) - Static method in class org.tribuo.util.Util: A binary search function.
BinningTransformation - Class in org.tribuo.transform.transformations: A Transformation which bins values.
BinningTransformation.BinningTransformationProvenance - Class in org.tribuo.transform.transformations: Provenance for BinningTransformation.
BinningTransformation.BinningTransformer - Class in org.tribuo.transform.transformations: The implementation of a Transformer which splits the input into n bins.
BinningTransformation.BinningType - Enum in org.tribuo.transform.transformations: The allowed binning types.
BinningTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance: Deserialization constructor.
BinningTransformer(BinningTransformation.BinningType, double[], double[]) - Constructor for class org.tribuo.transform.transformations.BinningTransformation.BinningTransformer: Constructs a binning transformer with the supplied bin widths and bin values.
BUILD_TIMESTAMP - Static variable in class org.tribuo.Tribuo: The build timestamp.
buildModel(ONNXContext, String, long, M) - Static method in interface org.tribuo.ONNXExportable: Creates an ONNX model protobuf for the supplied context.
BYTE - Enum constant in enum org.tribuo.datasource.IDXDataSource.IDXType: A signed byte.

C

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
castDataset(Dataset<?>, Class<T>) - Static method in class org.tribuo.Dataset: Casts the dataset to the specified output type, assuming it is valid.
castDataset(SequenceDataset<?>, Class<T>) - Static method in class org.tribuo.sequence.SequenceDataset: Casts the dataset to the specified output type, assuming it is valid.
castModel(Class<U>) - Method in class org.tribuo.Model: Casts the model to the specified output type, assuming it is valid.
castModel(Class<U>) - Method in class org.tribuo.sequence.SequenceModel: Casts the model to the specified output type, assuming it is valid.
CategoricalIDInfo - Class in org.tribuo: Same as a CategoricalInfo, but with an additional int id field.
CategoricalIDInfo(CategoricalInfo, int) - Constructor for class org.tribuo.CategoricalIDInfo: Constructs a categorical id info copying the information from the supplied info, with the specified id.
CategoricalInfo - Class in org.tribuo: Stores information about Categorical features.
CategoricalInfo(String) - Constructor for class org.tribuo.CategoricalInfo: Constructs a new empty categorical info for the supplied feature name.
CategoricalInfo(CategoricalInfo) - Constructor for class org.tribuo.CategoricalInfo: Constructs a deep copy of the supplied categorical info.
CategoricalInfo(CategoricalInfo, String) - Constructor for class org.tribuo.CategoricalInfo: Constructs a deep copy of the supplied categorical info, with the new feature name.
cdf - Variable in class org.tribuo.CategoricalInfo: The CDF to sample from.
checkIsBinary(Feature) - Static method in class org.tribuo.impl.BinaryFeaturesExample: Checks if the supplied feature is binary, if not throw an IllegalArgumentException.
className - Variable in class org.tribuo.provenance.ModelProvenance: The name of the host class.
clear() - Method in class org.tribuo.impl.ListExample: Clears the features from this example.
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.sequence.MutableSequenceDataset: Clears all the examples out of this dataset, and flushes the FeatureMap, OutputInfo, and transform provenances.
clone() - Method in class org.tribuo.Feature
combine(ImmutableOutputInfo<T>, List<Prediction<T>>) - Method in interface org.tribuo.ensemble.EnsembleCombiner: Combine the predictions.
combine(ImmutableOutputInfo<T>, List<Prediction<T>>, float[]) - Method in interface org.tribuo.ensemble.EnsembleCombiner: Combine the supplied predictions.
combiner - Variable in class org.tribuo.ensemble.BaggingTrainer
combiner - Variable in class org.tribuo.ensemble.WeightedEnsembleModel: The ensemble combination function.
compareTo(Feature) - Method in class org.tribuo.Feature
compute(C) - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric: Compute the result of this metric from the input context.
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.
ConfigurableDataSource<T> - Interface in org.tribuo: It's a DataSource that's also Configurable.
ConfiguredDataSourceProvenance - Interface in org.tribuo.provenance: A tag interface for configurable data source provenance.
constructInfoForExternalModel(Map<T, Integer>) - Method in interface org.tribuo.OutputFactory: Creates an ImmutableOutputInfo from the supplied mapping.
contains(int) - Method in class org.tribuo.impl.IndexedArrayExample: Does this example contain a feature with id i.
containsMetadata(String) - Method in class org.tribuo.Example: Test if the metadata contains the supplied key.
convert(byte) - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType: Converts the byte into the enum.
copy() - Method in class org.tribuo.CategoricalIDInfo
copy() - Method in class org.tribuo.CategoricalInfo
copy() - Method in class org.tribuo.Example: Returns a deep copy of this Example.
copy() - Method in class org.tribuo.impl.ArrayExample
copy() - Method in class org.tribuo.impl.BinaryFeaturesExample
copy() - Method in class org.tribuo.impl.IndexedArrayExample
copy() - Method in class org.tribuo.impl.ListExample
copy() - Method in class org.tribuo.Model: Copies a model, returning a deep copy of any mutable state, and a shallow copy otherwise.
copy() - Method in interface org.tribuo.Output: Deep copy of the output up to its immutable state.
copy() - Method in interface org.tribuo.OutputInfo: Generates a copy of this OutputInfo, including it's mutability.
copy() - Method in class org.tribuo.RealIDInfo
copy() - Method in class org.tribuo.RealInfo
copy() - Method in class org.tribuo.sequence.SequenceExample: Returns a deep copy of this SequenceExample.
copy() - Method in class org.tribuo.SparseModel
copy() - Method in interface org.tribuo.VariableInfo: Returns a copy of this variable info.
copy(String, EnsembleModelProvenance, List<Model<T>>) - Method in class org.tribuo.ensemble.EnsembleModel: Copies this ensemble model.
copy(String, EnsembleModelProvenance, List<Model<T>>) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
copy(String, ModelProvenance) - Method in class org.tribuo.ensemble.EnsembleModel
copy(String, ModelProvenance) - Method in class org.tribuo.Model: Copies a model, replacing its provenance and name with the supplied values.
copy(String, ModelProvenance) - Method in class org.tribuo.transform.TransformedModel
copyDataset(Dataset<T>) - Static method in class org.tribuo.ImmutableDataset: Creates an immutable deep copy of the supplied dataset.
copyDataset(Dataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Static method in class org.tribuo.ImmutableDataset: Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
copyDataset(Dataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, Merger) - Static method in class org.tribuo.ImmutableDataset: Creates an immutable deep copy of the supplied dataset.
copyDataset(SequenceDataset<T>) - Static method in class org.tribuo.sequence.ImmutableSequenceDataset: Creates an immutable deep copy of the supplied dataset.
copyDataset(SequenceDataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Static method in class org.tribuo.sequence.ImmutableSequenceDataset: Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
copyDataset(SequenceDataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, Merger) - Static method in class org.tribuo.sequence.ImmutableSequenceDataset: Creates an immutable deep copy of the supplied dataset.
copyValues(int) - Method in class org.tribuo.impl.ArrayExample: Returns a copy of the feature values array at the specific size.
count - Variable in class org.tribuo.SkeletalVariableInfo: How often the feature occurs in the dataset.
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.
createContext(Model<T>, List<Prediction<T>>) - Method in class org.tribuo.evaluation.AbstractEvaluator: Create the context needed for evaluation.
createContext(Model<T>, List<Prediction<T>>) - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric: Creates the context this metric uses to compute it's value.
createContext(Model<T>, Dataset<T>) - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric: Creates the metric context used to compute this metric's value, generating Predictions for each Example in the supplied dataset.
createContext(SequenceModel<T>, List<List<Prediction<T>>>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator: Create the context needed for evaluation.
createDataCarrier() - Method in class org.tribuo.Model: Constructs the data carrier for serialization.
createDataCarrier() - Method in class org.tribuo.sequence.SequenceModel: Constructs the data carrier for serialization.
createDataCarrier(FeatureMap, OutputInfo<T>) - Method in class org.tribuo.Dataset: Constructs the data carrier for serialization.
createDataCarrier(FeatureMap, OutputInfo<T>) - Method in class org.tribuo.sequence.SequenceDataset: Constructs the data carrier for serialization.
createDataCarrier(FeatureMap, OutputInfo<T>, List<ObjectProvenance>) - Method in class org.tribuo.Dataset: Constructs the data carrier for serialization.
createDeepCopy(Dataset<T>) - Static method in class org.tribuo.MutableDataset: Creates a deep copy of the supplied Dataset which is mutable.
createEnsembleFromExistingModels(String, List<Model<T>>, EnsembleCombiner<T>) - Static method in class org.tribuo.ensemble.WeightedEnsembleModel: Creates an ensemble from existing models.
createEnsembleFromExistingModels(String, List<Model<T>>, EnsembleCombiner<T>, float[]) - Static method in class org.tribuo.ensemble.WeightedEnsembleModel: Creates an ensemble from existing models.
createEvaluation(C, Map<MetricID<T>, Double>, EvaluationProvenance) - Method in class org.tribuo.evaluation.AbstractEvaluator: Create an evaluation for the given results
createEvaluation(C, Map<MetricID<T>, Double>, EvaluationProvenance) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator: Create an evaluation for the given results
createIDXData(IDXDataSource.IDXType, int[], double[]) - Static method in class org.tribuo.datasource.IDXDataSource.IDXData: Constructs an IDXData, validating the input and defensively copying it.
createMetrics(Model<T>) - Method in class org.tribuo.evaluation.AbstractEvaluator: Creates the appropriate set of metrics for this model, by querying for it's OutputInfo.
createMetrics(SequenceModel<T>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator: Creates the appropriate set of metrics for this model, by querying for it's OutputInfo.
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.
createStats() - Method in interface org.tribuo.transform.Transformation: Creates the statistics object for this Transformation.
createStats() - Method in class org.tribuo.transform.transformations.BinningTransformation
createStats() - Method in class org.tribuo.transform.transformations.IDFTransformation
createStats() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation
createStats() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation
createStats() - Method in class org.tribuo.transform.transformations.SimpleTransform: Returns itself.
createTransformers(TransformationMap) - Method in class org.tribuo.Dataset: Takes a TransformationMap and converts it into a TransformerMap by observing all the values in this dataset.
createTransformers(TransformationMap, boolean) - Method in class org.tribuo.Dataset: Takes a TransformationMap and converts it into a TransformerMap by observing all the values in this dataset.
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.
createWithEmptyOutputs(List<? extends List<? extends Feature>>, OutputFactory<T>) - Static method in class org.tribuo.sequence.SequenceExample: Creates a SequenceExample using OutputFactory.getUnknownOutput() as the output for each sequence element.
CREATION_TIME - Static variable in class org.tribuo.provenance.impl.TimestampedTrainerProvenance: The name of the provenance field storing the model creation time.
CrossValidation<T,E> - 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.
cumulativeSum(boolean[]) - Static method in class org.tribuo.util.Util: Produces a cumulative sum array.
cumulativeSum(double[]) - Static method in class org.tribuo.util.Util: Produces a cumulative sum array.
CURRENT_VERSION - Static variable in class org.tribuo.CategoricalIDInfo: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.CategoricalInfo: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.dataset.DatasetView: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.dataset.MinimumCardinalityDataset: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.dataset.SelectedFeatureDataset: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.ensemble.WeightedEnsembleModel: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.hash.HashCodeHasher: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.hash.HashedFeatureMap: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.hash.MessageDigestHasher: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.hash.ModHashCodeHasher: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.ImmutableDataset: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.ImmutableFeatureMap: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.impl.ArrayExample: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.impl.BinaryFeaturesExample: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.impl.IndexedArrayExample: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.impl.ListExample: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.MutableDataset: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.MutableFeatureMap: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.Prediction: The current protobuf serialization version of this class.
CURRENT_VERSION - Static variable in class org.tribuo.RealIDInfo: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.RealInfo: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.SelectedFeatureSet: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.sequence.ImmutableSequenceDataset: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.sequence.IndependentSequenceModel: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.sequence.MinimumCardinalitySequenceDataset: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.sequence.MutableSequenceDataset: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.sequence.SequenceExample: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformer: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.transform.transformations.SimpleTransform: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.transform.TransformedModel: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.transform.TransformerMap: Protobuf serialization version.

D

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.
DataProvenance - Interface in org.tribuo.provenance: Tag interface for data sources provenances.
Dataset<T> - Class in org.tribuo: A class for sets of data, which are used to train and evaluate classifiers.
Dataset(DataSource<T>) - Constructor for class org.tribuo.Dataset: Creates a dataset.
Dataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.Dataset: Creates a dataset.
Dataset(DataProvenance, OutputFactory<T>, String) - Constructor for class org.tribuo.Dataset: Creates a dataset.
DATASET - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the dataset provenance field.
DatasetDataCarrier<T> - Class in org.tribuo.impl: Serialization carrier for common fields in Dataset.
DatasetDataCarrier(DataProvenance, FeatureMap, OutputInfo<T>, OutputFactory<T>, List<ObjectProvenance>, String) - Constructor for class org.tribuo.impl.DatasetDataCarrier: Constructs a new DatasetDataCarrier.
datasetProvenance - Variable in class org.tribuo.provenance.ModelProvenance: The dataset provenance.
DatasetProvenance - Class in org.tribuo.provenance: Base class for dataset provenance.
DatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.DatasetProvenance: Deserialization constructor.
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, String, boolean, boolean, int, int, int) - Constructor for class org.tribuo.provenance.DatasetProvenance: Constructs a dataset provenance using the supplied information.
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, Dataset<T>) - Constructor for class org.tribuo.provenance.DatasetProvenance: Creates a dataset provenance from the supplied dataset.
DatasetProvenance(DataProvenance, ListProvenance<ObjectProvenance>, SequenceDataset<T>) - Constructor for class org.tribuo.provenance.DatasetProvenance: Creates a dataset provenance from the supplied sequence dataset.
DatasetView<T> - Class in org.tribuo.dataset: DatasetView provides an immutable view on another Dataset that only exposes selected examples.
DatasetView(Dataset<T>, int[], String) - Constructor for class org.tribuo.dataset.DatasetView: Creates a DatasetView which includes the supplied indices from the dataset.
DatasetView(Dataset<T>, int[], ImmutableFeatureMap, ImmutableOutputInfo<T>, String) - Constructor for class org.tribuo.dataset.DatasetView: Creates a DatasetView which includes the supplied indices from the dataset.
DatasetView.DatasetViewProvenance - Class in org.tribuo.dataset: Provenance for the DatasetView.
DatasetViewProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.dataset.DatasetView.DatasetViewProvenance: Deserialization constructor.
DataSource<T> - Interface in org.tribuo: A interface for things that can be given to a Dataset's constructor.
DATASOURCE_CREATION_TIME - Static variable in interface org.tribuo.provenance.DataSourceProvenance: The name of the provenance field for the datasource timestamp.
DataSourceProvenance - Interface in org.tribuo.provenance: Data source provenance.
DEFAULT_FIELD_NAME - Static variable in annotation type org.tribuo.protos.ProtoSerializableField: The default field name, used to signify it should use the field name rather than a supplied value.
DEFAULT_METADATA_SIZE - Static variable in class org.tribuo.Example: The default initial size of the metadata map.
DEFAULT_SEED - Static variable in interface org.tribuo.Trainer: Default seed used to initialise RNGs.
DEFAULT_SIZE - Static variable in class org.tribuo.impl.ArrayExample: Default initial size of the backing arrays.
DEFAULT_SIZE - Static variable in class org.tribuo.impl.BinaryFeaturesExample: Default initial size of the backing arrays.
DEFAULT_WEIGHT - Static variable in class org.tribuo.Example: The default weight.
DEFAULT_WEIGHT - Static variable in class org.tribuo.sequence.SequenceExample: The default sequence example weight.
dense - Variable in class org.tribuo.MutableDataset: Denotes if this dataset contains implicit zeros or not.
dense - Variable in class org.tribuo.sequence.MutableSequenceDataset: Does this dataset have a dense feature space.
densify() - Method in class org.tribuo.MutableDataset: Iterates through the examples, converting implicit zeros into explicit zeros.
densify() - Method in class org.tribuo.sequence.MutableSequenceDataset: Iterates through the examples, converting implicit zeros into explicit zeros.
densify(List<String>) - Method in class org.tribuo.Example: Adds zero valued features for each feature name in featureNames.
densify(List<String>) - Method in class org.tribuo.impl.ArrayExample: Adds zero valued features for each feature name in featureList.
densify(List<String>) - Method in class org.tribuo.impl.BinaryFeaturesExample
densify(List<String>) - Method in class org.tribuo.impl.IndexedArrayExample: Unlike ArrayExample.densify(List) this method will throw IllegalArgumentException if one of the feature names is not present in this example's ImmutableFeatureMap.
densify(List<String>) - Method in class org.tribuo.impl.ListExample: Adds zero valued features for each feature name in featureNames.
densify(FeatureMap) - Method in class org.tribuo.Example: Converts all implicit zeros into explicit zeros based on the supplied feature map.
densify(FeatureMap) - Method in class org.tribuo.impl.BinaryFeaturesExample
densify(FeatureMap) - Method in class org.tribuo.sequence.SequenceExample: Converts all implicit zeros into explicit zeros based on the supplied feature map.
DESCRIPTION - Static variable in class org.tribuo.provenance.SimpleDataSourceProvenance: The description field in the provenance.
DescriptiveStats - Class in org.tribuo.evaluation: Descriptive statistics calculated across a list of doubles.
DescriptiveStats() - Constructor for class org.tribuo.evaluation.DescriptiveStats: Create an empty DescriptiveStats.
DescriptiveStats(List<Double>) - Constructor for class org.tribuo.evaluation.DescriptiveStats: Create a DescriptiveStats initialized with the supplied values.
DESERIALIZATION_METHOD_NAME - Static variable in interface org.tribuo.protos.ProtoSerializable: The name of the static deserialization method for ProtoSerializable classes.
deserialize(DatasetDataProto) - Static method in class org.tribuo.impl.DatasetDataCarrier: Deserializes a DatasetDataProto into a DatasetDataCarrier.
deserialize(DatasetProto) - Static method in class org.tribuo.Dataset: Deserializes a dataset proto into a dataset.
deserialize(EnsembleCombinerProto) - Static method in interface org.tribuo.ensemble.EnsembleCombiner: Deserialization helper for EnsembleCombiner.
deserialize(ExampleProto) - Static method in class org.tribuo.Example: Deserializes an example proto into an example.
deserialize(FeatureDomainProto) - Static method in class org.tribuo.FeatureMap: Deserializes a FeatureDomainProto into a FeatureMap subclass.
deserialize(HasherProto, String) - Static method in class org.tribuo.hash.Hasher: Deserializes a HasherProto into a Hasher subclass.
deserialize(ModelDataProto) - Static method in class org.tribuo.impl.ModelDataCarrier: Deserializes a ModelDataProto into a ModelDataCarrier.
deserialize(ModelProto) - Static method in class org.tribuo.Model: Deserializes the model from the supplied protobuf.
deserialize(OutputDomainProto) - Static method in interface org.tribuo.OutputInfo: Deserializes a OutputDomainProto into a OutputInfo subclass.
deserialize(OutputFactoryProto) - Static method in interface org.tribuo.OutputFactory: Deserializes a OutputFactoryProto into a OutputFactory subclass.
deserialize(OutputProto) - Static method in interface org.tribuo.Output: Deserializes a OutputProto into a Output subclass.
deserialize(SequenceDatasetProto) - Static method in class org.tribuo.sequence.SequenceDataset: Deserializes a sequence dataset proto into a sequence dataset.
deserialize(SequenceExampleProto) - Static method in class org.tribuo.sequence.SequenceExample: Deserialization shortcut, used to firm up the types.
deserialize(SequenceModelProto) - Static method in class org.tribuo.sequence.SequenceModel: Deserializes the model from the supplied protobuf.
deserialize(TransformerMapProto) - Static method in class org.tribuo.transform.TransformerMap: Deserializes a TransformerMapProto into a TransformerMap.
deserialize(TransformerProto) - Static method in interface org.tribuo.transform.Transformer: Deserializes a TransformerProto into a Transformer subclass.
deserialize(VariableInfoProto) - Static method in interface org.tribuo.VariableInfo: Deserializes the variable info from the supplied protobuf.
deserialize(SERIALIZED) - Static method in class org.tribuo.protos.ProtoUtil: Instantiates the class from the supplied protobuf fields.
deserializeExamples(List<ExampleProto>, Class<?>, FeatureMap) - Static method in class org.tribuo.Dataset: Deserializes a list of example protos into a list of examples.
deserializeExamples(List<SequenceExampleProto>, Class<?>, FeatureMap) - Static method in class org.tribuo.sequence.SequenceDataset: Deserializes a list of sequence example protos into a list of sequence examples.
deserializeFromFile(Path) - Static method in class org.tribuo.Dataset: Reads an instance of DatasetProto from the supplied path and deserializes it.
deserializeFromFile(Path) - Static method in class org.tribuo.Model: Reads an instance of ModelProto from the supplied path and deserializes it.
deserializeFromFile(Path) - Static method in class org.tribuo.sequence.SequenceDataset: Reads an instance of SequenceDatasetProto from the supplied path and deserializes it.
deserializeFromFile(Path) - Static method in class org.tribuo.sequence.SequenceModel: Reads an instance of SequenceModelProto from the supplied path and deserializes it.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.CategoricalIDInfo: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.CategoricalInfo: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.dataset.DatasetView: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.dataset.MinimumCardinalityDataset: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.dataset.SelectedFeatureDataset: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.ensemble.WeightedEnsembleModel: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.hash.HashCodeHasher: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.hash.HashedFeatureMap: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.hash.MessageDigestHasher: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.hash.ModHashCodeHasher: Deserialization constructor.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.ImmutableDataset: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.ImmutableFeatureMap: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.impl.ArrayExample: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.impl.BinaryFeaturesExample: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.impl.IndexedArrayExample: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.impl.ListExample: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.MutableDataset: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.MutableFeatureMap: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.Prediction: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.RealIDInfo: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.RealInfo: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.SelectedFeatureSet: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.sequence.ImmutableSequenceDataset: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.sequence.IndependentSequenceModel: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.sequence.MutableSequenceDataset: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.sequence.SequenceExample: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.transform.TransformedModel: Deserialization factory.
deserializeFromStream(InputStream) - Static method in class org.tribuo.Dataset: Reads an instance of DatasetProto from the supplied input stream and deserializes it.
deserializeFromStream(InputStream) - Static method in class org.tribuo.Model: Reads an instance of ModelProto from the supplied input stream and deserializes it.
deserializeFromStream(InputStream) - Static method in class org.tribuo.sequence.SequenceDataset: Reads an instance of SequenceDatasetProto from the supplied input stream and deserializes it.
deserializeFromStream(InputStream) - Static method in class org.tribuo.sequence.SequenceModel: Reads an instance of SequenceModelProto from the supplied input stream and deserializes it.
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.
distributionEquals(Prediction<T>) - Method in class org.tribuo.Prediction: Checks that the other prediction has the same distribution as this prediction, using the Output.fullEquals(T) method.
distributionEquals(Prediction<T>, double) - Method in class org.tribuo.Prediction: Checks that the other prediction has the same distribution as this prediction, using the Output.fullEquals(T) method.
div - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Divides by the specified constant.
div(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that divides each value by the operand.
domainAndIDEquals(ImmutableOutputInfo<T>) - Method in interface org.tribuo.ImmutableOutputInfo: Checks if the domain is the same as the other output info's domain, and that each element is mapped to the same id number.
domainEquals(FeatureMap) - Method in class org.tribuo.FeatureMap: Check if this feature map contains the same features as the supplied one.
DOUBLE - Enum constant in enum org.tribuo.datasource.IDXDataSource.IDXType: A 64-bit float.
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.

E

EmptyDatasetProvenance - Class in org.tribuo.provenance.impl: An empty DatasetProvenance, should not be used except by the provenance removal system.
EmptyDatasetProvenance() - Constructor for class org.tribuo.provenance.impl.EmptyDatasetProvenance: An empty dataset provenance.
EmptyDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyDatasetProvenance: Deserialization constructor.
EmptyDataSourceProvenance - Class in org.tribuo.provenance.impl: An empty DataSourceProvenance, should not be used except by the provenance removal system.
EmptyDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyDataSourceProvenance: Deserialization constructor.
EmptyTrainerProvenance - Class in org.tribuo.provenance.impl: An empty TrainerProvenance, should not be used except by the provenance removal system.
EmptyTrainerProvenance() - Constructor for class org.tribuo.provenance.impl.EmptyTrainerProvenance: Constructs an empty trainer provenance.
EmptyTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.EmptyTrainerProvenance: Deserialization constructor.
EnsembleCombiner<T> - Interface in org.tribuo.ensemble: An interface for combining predictions.
EnsembleExcuse<T> - Class in org.tribuo.ensemble: An Excuse which has a List of excuses for each of the ensemble members.
EnsembleExcuse(Example<T>, Prediction<T>, Map<String, List<Pair<String, Double>>>, List<Excuse<T>>) - Constructor for class org.tribuo.ensemble.EnsembleExcuse: Constructs an ensemble excuse, comprising the excuses from each ensemble member, along with the feature weights.
EnsembleModel<T> - Class in org.tribuo.ensemble: A model which contains a list of other Models.
EnsembleModel(String, EnsembleModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Model<T>>) - Constructor for class org.tribuo.ensemble.EnsembleModel: Builds an EnsembleModel from the supplied model list.
EnsembleModelProvenance - Class in org.tribuo.provenance: Model provenance for ensemble models.
EnsembleModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, ListProvenance<? extends ModelProvenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance: Creates a provenance for an ensemble model tracking the class name, creation time, dataset provenance and trainer provenance along with the individual model provenances for each ensemble member.
EnsembleModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>, boolean, ListProvenance<? extends ModelProvenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance: Creates a provenance for an ensemble model tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance along with the individual model provenances for each ensemble member.
EnsembleModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>, ListProvenance<? extends ModelProvenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance: Creates a provenance for an ensemble model tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance along with the individual model provenances for each ensemble member.
EnsembleModelProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.EnsembleModelProvenance: Used by the provenance unmarshalling system.
ensembleName() - Method in class org.tribuo.ensemble.BaggingTrainer: Default name of the generated ensemble.
entrySet() - Method in class org.tribuo.transform.TransformerMap: Get the feature names and associated list of transformers.
EPSILON - Static variable in class org.tribuo.transform.transformations.SimpleTransform: Epsilon for determining when two double values are the same.
EQUAL_FREQUENCY - Enum constant in enum org.tribuo.transform.transformations.BinningTransformation.BinningType: Creates bins of equal frequency (i.e., equal numbers of data points).
EQUAL_WIDTH - Enum constant in enum org.tribuo.transform.transformations.BinningTransformation.BinningType: Creates bins of equal width over the data range.
equalFrequency(int) - Static method in class org.tribuo.transform.transformations.BinningTransformation: Returns a BinningTransformation which generates bins which contain the same amount of training data that is, each bin has an equal probability of occurrence in the training data.
equals(Object) - Method in class org.tribuo.CategoricalIDInfo
equals(Object) - Method in class org.tribuo.CategoricalInfo
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.dataset.SelectedFeatureDataset.SelectedFeatureDatasetProvenance
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.FeatureMap
equals(Object) - Method in class org.tribuo.hash.HashCodeHasher
equals(Object) - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
equals(Object) - Method in class org.tribuo.hash.MessageDigestHasher
equals(Object) - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
equals(Object) - Method in class org.tribuo.hash.ModHashCodeHasher
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.DatasetDataCarrier
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.impl.ModelDataCarrier
equals(Object) - Method in class org.tribuo.MutableFeatureMap
equals(Object) - Method in class org.tribuo.provenance.DatasetProvenance
equals(Object) - Method in class org.tribuo.provenance.EnsembleModelProvenance
equals(Object) - Method in class org.tribuo.provenance.EvaluationProvenance
equals(Object) - Method in class org.tribuo.provenance.FeatureSetProvenance
equals(Object) - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
equals(Object) - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
equals(Object) - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
equals(Object) - Method in class org.tribuo.provenance.ModelProvenance
equals(Object) - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
equals(Object) - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
equals(Object) - Method in class org.tribuo.RealIDInfo
equals(Object) - Method in class org.tribuo.RealInfo
equals(Object) - Method in class org.tribuo.SelectedFeatureSet: Checks if this SelectedFeatureSet is equal to the supplied object.
equals(Object) - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
equals(Object) - Method in class org.tribuo.sequence.SequenceExample
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.BinningTransformation.BinningTransformer
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
equals(Object) - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
equals(Object) - Method in class org.tribuo.transform.TransformerMap
equals(Object) - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
equals(Object) - Method in class org.tribuo.util.IntDoublePair
equals(Object) - Method in class org.tribuo.util.MeanVarianceAccumulator
equalWidth(int) - Static method in class org.tribuo.transform.transformations.BinningTransformation: Returns a BinningTransformation which generates fixed equal width bins between the observed min and max values.
evaluate() - Method in class org.tribuo.evaluation.CrossValidation: Performs k fold cross validation, returning the k evaluations.
evaluate() - Method in class org.tribuo.evaluation.OnlineEvaluator: Creates an Evaluation containing all the current predictions.
evaluate(Model<T>, List<Prediction<T>>, List<T>, DataProvenance) - Method in interface org.tribuo.evaluation.Evaluator: Evaluates the model performance using the supplied predictions, returning an immutable Evaluation of the appropriate type.
evaluate(Model<T>, List<Prediction<T>>, DataProvenance) - Method in class org.tribuo.evaluation.AbstractEvaluator: Produces an evaluation for the supplied model and predictions by aggregating the appropriate statistics.
evaluate(Model<T>, List<Prediction<T>>, DataProvenance) - Method in interface org.tribuo.evaluation.Evaluator: Evaluates the model performance using the supplied predictions, returning an immutable Evaluation of the appropriate type.
evaluate(Model<T>, Dataset<T>) - Method in class org.tribuo.evaluation.AbstractEvaluator: Produces an evaluation for the supplied model and dataset, by calling Model.predict(org.tribuo.Example<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(Model<T>, Dataset<T>) - Method in interface org.tribuo.evaluation.Evaluator: Evaluates the dataset using the supplied model, returning an immutable Evaluation of the appropriate type.
evaluate(Model<T>, DataSource<T>) - Method in class org.tribuo.evaluation.AbstractEvaluator: Produces an evaluation for the supplied model and datasource, by calling Model.predict(org.tribuo.Example<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(Model<T>, DataSource<T>) - Method in interface org.tribuo.evaluation.Evaluator: Evaluates the dataset using the supplied model, returning an immutable Evaluation of the appropriate type.
evaluate(SequenceModel<T>, List<List<Prediction<T>>>, DataProvenance) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator: Produces an evaluation for the supplied model and predictions by aggregating the appropriate statistics.
evaluate(SequenceModel<T>, List<List<Prediction<T>>>, DataProvenance) - Method in interface org.tribuo.sequence.SequenceEvaluator: Evaluates the supplied model and predictions by aggregating the appropriate statistics.
evaluate(SequenceModel<T>, SequenceDataset<T>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator: Produces an evaluation for the supplied model and dataset, by calling SequenceModel.predict(org.tribuo.sequence.SequenceExample<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(SequenceModel<T>, SequenceDataset<T>) - Method in interface org.tribuo.sequence.SequenceEvaluator: Evaluates the dataset using the supplied model, returning an immutable evaluation.
evaluate(SequenceModel<T>, SequenceDataSource<T>) - Method in class org.tribuo.sequence.AbstractSequenceEvaluator: Produces an evaluation for the supplied model and datasource, by calling SequenceModel.predict(org.tribuo.sequence.SequenceExample<T>) to create the predictions, then aggregating the appropriate statistics.
evaluate(SequenceModel<T>, SequenceDataSource<T>) - Method in interface org.tribuo.sequence.SequenceEvaluator: Evaluates the datasource using the supplied model, returning an immutable evaluation.
Evaluation<T> - 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,C> - Interface in org.tribuo.evaluation.metrics: A metric that can be calculated for the specified output type.
EvaluationMetric.Average - Enum in org.tribuo.evaluation.metrics: Specifies what form of average to use for a EvaluationMetric.
EvaluationProvenance - Class in org.tribuo.provenance: Provenance for evaluations.
EvaluationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.EvaluationProvenance: Deserialization constructor.
EvaluationProvenance(ModelProvenance, DataProvenance) - Constructor for class org.tribuo.provenance.EvaluationProvenance: Constructs an evaluation provenance from the supplied provenances.
EvaluationRenderer<T,E> - Interface in org.tribuo.evaluation: Renders an Evaluation into a String.
Evaluator<T,E> - Interface in org.tribuo.evaluation: An evaluation factory which produces immutable Evaluations of a given Dataset using the given Model.
Example<T> - Class in org.tribuo: An example used for training and evaluation.
Example(Example<T>) - Constructor for class org.tribuo.Example: Copies the output, weight and metadata into this example.
Example(T) - Constructor for class org.tribuo.Example: Construct an empty example using the supplied output and Example.DEFAULT_WEIGHT as the weight.
Example(T, float) - Constructor for class org.tribuo.Example: Construct an empty example using the supplied output and weight.
Example(T, float, Map<String, Object>) - Constructor for class org.tribuo.Example: Construct an empty example using the supplied output, weight and metadata.
Example(T, Map<String, Object>) - Constructor for class org.tribuo.Example: Construct an empty example using the supplied output, metadata and Example.DEFAULT_WEIGHT as the weight.
excuse(String) - Method in class org.tribuo.Excuse: Returns the features involved in this excuse.
Excuse<T> - Class in org.tribuo: Holds an Example, a Prediction and a Map from String to List of Pairs that contains the per output explanation.
Excuse(Example<T>, Prediction<T>, Map<String, List<Pair<String, Double>>>) - Constructor for class org.tribuo.Excuse: Constructs an excuse for the prediction of the supplied example, using the feature weights.
exp - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Exponentiates the inputs
exp() - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that applies Math.exp(double).
exportCombiner(ONNXNode) - Method in interface org.tribuo.ensemble.EnsembleCombiner: Exports this ensemble combiner into the ONNX context of its input.
exportCombiner(ONNXNode, U) - Method in interface org.tribuo.ensemble.EnsembleCombiner: Exports this ensemble combiner into the ONNX context of its input.
exportONNXModel(String, long) - Method in class org.tribuo.ensemble.WeightedEnsembleModel: Exports this EnsembleModel as an ONNX model.
exportONNXModel(String, long) - Method in interface org.tribuo.ONNXExportable: Exports this Model as an ONNX protobuf.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.datasource.AggregateConfigurableDataSource.AggregateConfigurableDataSourceProvenance: Extracts the class name and host type fields from the provenance map.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance: Separates out the configured and non-configured provenance values.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance: Separates out the configured and non-configured provenance values.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.provenance.impl.FeatureSelectorProvenanceImpl: Extracts the class name and host short name provenances.
extractProvenanceInfo(Map<String, Provenance>) - Static method in class org.tribuo.provenance.SkeletalTrainerProvenance: Extracts the provenance information from the supplied map, splitting it into configuration and instance information.

F

Feature - Class in org.tribuo: A class for features.
Feature(String, double) - Constructor for class org.tribuo.Feature: Creates an immutable feature.
FEATURE_TYPE - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance: The name of the provenance field for the idx feature type.
featureDomain() - Method in class org.tribuo.impl.DatasetDataCarrier: Get the feature domain.
featureDomain() - Method in class org.tribuo.impl.ModelDataCarrier: The feature domain.
featureIDMap - Variable in class org.tribuo.ImmutableDataset: A map from feature names to IDs for the features found in this dataset.
featureIDMap - Variable in class org.tribuo.Model: The features this model knows about.
featureIDMap - Variable in class org.tribuo.sequence.ImmutableSequenceDataset: A map from feature names to IDs for the features found in this dataset.
featureIDMap - Variable in class org.tribuo.sequence.SequenceModel: The feature domain.
featureIDs - Variable in class org.tribuo.impl.IndexedArrayExample: Feature id numbers from the internal featureMap.
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.ModelExplorer: Shows a specific feature's information.
featureInfo(CommandInterpreter, String) - Method in class org.tribuo.sequence.SequenceModelExplorer: Shows information on a particular feature.
featureIterator() - Method in class org.tribuo.sequence.SequenceExample: Creates an iterator over every feature in this sequence.
featureMap - Variable in class org.tribuo.MutableDataset: A map from feature names to feature info objects.
featureMap - Variable in class org.tribuo.sequence.MutableSequenceDataset: A map from feature names to IDs for the features found in this dataset.
FeatureMap - Class in org.tribuo: A map from Strings to VariableInfo objects storing information about a feature.
FeatureMap() - Constructor for class org.tribuo.FeatureMap: Constructs an empty feature map.
FeatureMap(Map<String, ? extends VariableInfo>) - Constructor for class org.tribuo.FeatureMap: Constructs a feature map wrapping the supplied map.
FeatureMap(FeatureMap) - Constructor for class org.tribuo.FeatureMap: Constructs a deep copy of the supplied feature map.
featureNameComparator() - Static method in class org.tribuo.Feature: A comparator using the lexicographic ordering of feature names.
featureNames - Variable in class org.tribuo.impl.ArrayExample: Feature names array.
featureNames - Variable in class org.tribuo.impl.BinaryFeaturesExample: Feature names array.
featureNames() - Method in class org.tribuo.SelectedFeatureSet: The selected feature names in a possibly ordered list.
FEATURES_FILE_MODIFIED_TIME - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance: The name of the features file modified time provenance field.
FEATURES_RESOURCE_HASH - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance: The name of the provenance field for the feature file hash.
featureScores() - Method in class org.tribuo.SelectedFeatureSet: The selected feature scores in a possibly ordered list.
FeatureSelector<T> - Interface in org.tribuo: An interface for feature selection algorithms.
FeatureSelectorProvenance - Interface in org.tribuo.provenance: A tag interface for feature selection algorithms.
FeatureSelectorProvenanceImpl - Class in org.tribuo.provenance.impl: An implementation of FeatureSelectorProvenance which delegates everything to SkeletalConfiguredObjectProvenance.
FeatureSelectorProvenanceImpl(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.FeatureSelectorProvenanceImpl: Construct a FeatureSelectorProvenanceImpl by extracting the necessary fields from the supplied map.
FeatureSelectorProvenanceImpl(T) - Constructor for class org.tribuo.provenance.impl.FeatureSelectorProvenanceImpl: Creates a FeatureSelectorProvenanceImpl by reading the configured fields from the host object.
FeatureSetProvenance - Class in org.tribuo.provenance: Contains provenance information for an instance of a SelectedFeatureSet.
FeatureSetProvenance(String, DatasetProvenance, FeatureSelectorProvenance) - Constructor for class org.tribuo.provenance.FeatureSetProvenance: Creates a feature set provenance tracking the dataset provenance and feature selector provenance.
FeatureSetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.FeatureSetProvenance: Used by the provenance unmarshalling system.
FeatureTuple() - Constructor for class org.tribuo.impl.IndexedArrayExample.FeatureTuple: Constructs an empty feature tuple.
FeatureTuple(String, int, double) - Constructor for class org.tribuo.impl.IndexedArrayExample.FeatureTuple: Constructs a feature tuple using the specified values.
featureValues - Variable in class org.tribuo.impl.ArrayExample: Feature values array.
FILE_MODIFIED_TIME - Static variable in interface org.tribuo.provenance.DataSourceProvenance: The name of the provenance field for the file timestamp.
fileCompleter() - Method in class org.tribuo.ModelExplorer: Completers for files.
fileCompleter() - Method in class org.tribuo.sequence.SequenceModelExplorer: Completers for files.
FLOAT - Enum constant in enum org.tribuo.datasource.IDXDataSource.IDXType: A 32-bit float.
fmix32(int) - Static method in class org.tribuo.util.MurmurHash3: 32-bit mixing function.
fmix64(long) - Static method in class org.tribuo.util.MurmurHash3: 64-bit mixing function.
formatDuration(long, long) - Static method in class org.tribuo.util.Util: Formats a duration given two times in milliseconds.
frequencyBasedSample(Random, long) - Method in class org.tribuo.CategoricalInfo: Samples a value from this feature according to the frequency of observation.
frequencyBasedSample(SplittableRandom, long) - Method in class org.tribuo.CategoricalInfo: Samples a value from this feature according to the frequency of observation.
fullEquals(T) - Method in interface org.tribuo.Output: Compares other to this output.
fullEquals(T, double) - Method in interface org.tribuo.Output: Compares other to this output.

G

generateBootstrap() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance: Generates the indices from this DatasetViewProvenance by rerunning the bootstrap sample.
generateBootstrapIndices(int, int, SplittableRandom) - Static method in class org.tribuo.util.Util: Draws a bootstrap sample of indices.
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.
generateHashedFeatureMap(FeatureMap, Hasher) - Static method in class org.tribuo.hash.HashedFeatureMap: Converts a standard FeatureMap by hashing each entry using the supplied hash function Hasher.
generateIDs(List<? extends VariableInfo>) - Static method in class org.tribuo.ImmutableFeatureMap: Generates the feature ids by sorting the features with the String comparator, then sequentially numbering them.
generateIDs(FeatureMap) - Static method in class org.tribuo.ImmutableFeatureMap: Generates the feature ids by sorting the features with the String comparator, then sequentially numbering them.
generateImmutableOutputInfo() - Method in 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.
generateInfo() - Method in interface org.tribuo.OutputFactory: Generates the appropriate MutableOutputInfo so the output values can be tracked by a Dataset or other aggregate.
generateMethodName(String, String) - Static method in class org.tribuo.protos.ProtoUtil: Generate the method name for the type from the protobuf.
generateMutableOutputInfo() - Method in interface org.tribuo.OutputInfo: Generates a mutable copy of this OutputInfo.
generateOutput(V) - Method in interface org.tribuo.OutputFactory: Parses the V and generates the appropriate Output value.
generateOutputs(List<V>) - Method in interface org.tribuo.OutputFactory: Generate a list of outputs from the supplied list of inputs.
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.
generatesProbabilities - Variable in class org.tribuo.Model: Does this model generate probability distributions in the output.
generatesProbabilities() - Method in class org.tribuo.impl.ModelDataCarrier: Does this model generate probabilities?
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.
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.
generateUniformFloatVector(int, float) - Static method in class org.tribuo.util.Util: Generates a float vector of the specified length filled with the specified value.
generateUniformVector(int, double) - Static method in class org.tribuo.util.Util: Generates an array of the specified length filled with the specified value.
generateUniformVector(int, float) - Static method in class org.tribuo.util.Util: Generates an array of the specified length filled with the specified value.
generateWeightedIndicesSample(int, double[], Random) - Static method in class org.tribuo.util.Util: Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSample(int, double[], SplittableRandom) - Static method in class org.tribuo.util.Util: Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSample(int, float[], Random) - Static method in class org.tribuo.util.Util: Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSample(int, float[], SplittableRandom) - Static method in class org.tribuo.util.Util: Generates a sample of indices weighted by the provided weights.
generateWeightedIndicesSampleWithoutReplacement(int, double[], Random) - Static method in class org.tribuo.util.Util: Generates a sample of indices weighted by the provided weights without replacement.
generateWeightedIndicesSampleWithoutReplacement(int, float[], Random) - Static method in class org.tribuo.util.Util: Generates a sample of indices weighted by the provided weights without replacement.
get(int) - Method in class org.tribuo.ImmutableFeatureMap: Gets the VariableIDInfo for this id number.
get(int) - Method in class org.tribuo.sequence.SequenceExample: Gets the example found at the specified index.
get(String) - Method in class org.tribuo.FeatureMap: Gets the variable info associated with that feature name, or null if it's unknown.
get(String) - Method in class org.tribuo.hash.HashedFeatureMap
get(String) - Method in class org.tribuo.ImmutableFeatureMap: Gets the VariableIDInfo for this name.
get(String) - Method in class org.tribuo.transform.TransformerMap: Gets the transformers associated with a given feature name.
get(MetricID<T>) - Method in interface org.tribuo.evaluation.Evaluation: Gets the value associated with the specific metric.
get(MetricID<T>) - Method in interface org.tribuo.sequence.SequenceEvaluation: Gets the value associated with the specific metric.
getActiveFeatures() - Method in class org.tribuo.SparseModel: Return an immutable view on the active features for each dimension.
getArch() - Method in class org.tribuo.provenance.ModelProvenance: The CPU architecture used to create this model.
getAverageTarget() - Method in class org.tribuo.evaluation.metrics.MetricTarget: Returns the average this metric computes, or Optional.empty() if it targets an output.
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.provenance.DatasetProvenance
getClassName() - Method in class org.tribuo.provenance.EvaluationProvenance
getClassName() - Method in class org.tribuo.provenance.FeatureSetProvenance
getClassName() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
getClassName() - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
getClassName() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
getClassName() - Method in class org.tribuo.provenance.ModelProvenance
getClassName() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
getClassName() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
getClassName() - Method in class org.tribuo.transform.transformations.IDFTransformation.IDFTransformationProvenance
getClassName() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
getClassName() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
getClassName() - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
getClassName() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
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.provenance.impl.EmptyTrainerProvenance
getConfiguredParameters() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
getConfiguredParameters() - Method in interface org.tribuo.provenance.OutputFactoryProvenance
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.IDFTransformation.IDFTransformationProvenance
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
getConfiguredParameters() - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
getCount() - Method in class org.tribuo.SkeletalVariableInfo: Returns the occurrence count of this feature.
getCount() - Method in class org.tribuo.util.MeanVarianceAccumulator: Gets the observation count.
getCount() - Method in interface org.tribuo.VariableInfo: The occurrence count of this feature.
getCurrentVersion(Class<? extends ProtoSerializable<?>>) - Static method in class org.tribuo.protos.ProtoUtil: If this class is annotated with ProtoSerializableClass returns the version number, otherwise returns -1.
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.FeatureSetProvenance: The training dataset provenance.
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.
getDensify() - Method in class org.tribuo.transform.TransformedModel: Returns true if the model densifies the feature space before applying the transformations.
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.
getDomain() - Method in interface org.tribuo.OutputInfo: Returns a set of Output which represent the space of possible values the Output has taken.
getDropInvalidExamples() - Method in class org.tribuo.ImmutableDataset: Returns true if this immutable dataset dropped any invalid examples on construction.
getEvaluator() - Method in interface org.tribuo.OutputFactory: Gets an Evaluator suitable for measuring performance of predictions for the Output subclass.
getExample() - Method in class org.tribuo.Excuse: The example being excused.
getExample() - Method in class org.tribuo.Prediction: Returns the example itself.
getExample(int) - Method in class org.tribuo.dataset.DatasetView
getExample(int) - Method in class org.tribuo.Dataset: Gets the example at the supplied index.
getExample(int) - Method in class org.tribuo.sequence.SequenceDataset: Gets the example at the specified index, or throws IllegalArgumentException if the index is out of bounds.
getExampleIndices() - Method in class org.tribuo.dataset.DatasetView: Returns a copy of the indices used in this view.
getExampleSize() - Method in class org.tribuo.Prediction: Returns the number of features in the example.
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.Model: Generates an excuse for an example.
getExcuse(Example<T>) - Method in class org.tribuo.transform.TransformedModel
getExcuses(Iterable<Example<T>>) - Method in class org.tribuo.Model: Generates an excuse for each example.
getFeatureIDMap() - Method in class org.tribuo.Dataset: Returns or generates an ImmutableFeatureMap.
getFeatureIDMap() - Method in class org.tribuo.ImmutableDataset
getFeatureIDMap() - Method in class org.tribuo.Model: Gets the feature domain.
getFeatureIDMap() - Method in class org.tribuo.MutableDataset
getFeatureIDMap() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
getFeatureIDMap() - Method in class org.tribuo.sequence.MutableSequenceDataset
getFeatureIDMap() - Method in class org.tribuo.sequence.SequenceDataset: An immutable view on the feature map.
getFeatureIDMap() - Method in class org.tribuo.sequence.SequenceModel: Gets the feature domain.
getFeatureMap() - Method in class org.tribuo.dataset.DatasetView
getFeatureMap() - Method in class org.tribuo.Dataset: Returns this dataset's FeatureMap.
getFeatureMap() - Method in class org.tribuo.ImmutableDataset
getFeatureMap() - Method in class org.tribuo.MutableDataset
getFeatureMap() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
getFeatureMap() - Method in class org.tribuo.sequence.MutableSequenceDataset
getFeatureMap() - Method in class org.tribuo.sequence.SequenceDataset: The feature map.
getFeatureSelectorProvenance() - Method in class org.tribuo.provenance.FeatureSetProvenance: The feature selector provenance.
getFeatureSet() - Method in class org.tribuo.dataset.SelectedFeatureDataset: The feature set.
getFeatureTransformations() - Method in class org.tribuo.transform.TransformationMap: Gets the map of feature specific transformations.
getFlatDataset() - Method in class org.tribuo.sequence.SequenceDataset: Returns a view on this SequenceDataset which aggregates all the examples and ignores the sequence structure.
getGlobalTransformations() - Method in class org.tribuo.transform.TransformationMap: Gets the global transformations in this TransformationMap.
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.
getID() - Method in class org.tribuo.CategoricalIDInfo
getID() - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric: The metric ID, a combination of the metric target and metric name.
getID() - Method in class org.tribuo.RealIDInfo
getID() - Method in interface org.tribuo.VariableIDInfo: The id number associated with this variable.
getID(String) - Method in class org.tribuo.hash.HashedFeatureMap: Gets the id number for this feature, returns -1 if it's unknown.
getID(String) - Method in class org.tribuo.ImmutableFeatureMap: Gets the id number for this feature, returns -1 if it's unknown.
getID(T) - Method in interface org.tribuo.ImmutableOutputInfo: Return the id number associated with this output, or -1 if the output is unknown.
getIdx(int) - Method in class org.tribuo.impl.IndexedArrayExample: Gets the feature at internal index i.
getInnerExcuses() - Method in class org.tribuo.ensemble.EnsembleExcuse: The individual ensemble member's excuses.
getInnerModel() - Method in class org.tribuo.transform.TransformedModel: Gets the inner model to allow access to any class specific methods that model contains (e.g., to examine cluster centroids).
getInstanceProvenance() - Method in class org.tribuo.provenance.ModelProvenance: Provenance for the specific training run which created this model.
getInstanceValues() - Method in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance
getInstanceValues() - Method in class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance
getInstanceValues() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
getInstanceValues() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
getInvocationCount() - Method in class org.tribuo.ensemble.BaggingTrainer
getInvocationCount() - Method in class org.tribuo.hash.HashingTrainer
getInvocationCount() - Method in class org.tribuo.sequence.HashingSequenceTrainer
getInvocationCount() - Method in class org.tribuo.sequence.IndependentSequenceTrainer
getInvocationCount() - Method in interface org.tribuo.sequence.SequenceTrainer: Returns the number of times the train method has been invoked.
getInvocationCount() - Method in interface org.tribuo.Trainer: The number of times this trainer instance has had it's train method invoked.
getInvocationCount() - Method in class org.tribuo.transform.TransformTrainer
getJavaVersion() - Method in class org.tribuo.provenance.ModelProvenance: The Java version used to create this model.
getK() - Method in class org.tribuo.dataset.SelectedFeatureDataset: The number of features to use.
getK() - Method in class org.tribuo.evaluation.CrossValidation: Returns the number of folds.
getLongLittleEndian(byte[], int) - Static method in class org.tribuo.util.MurmurHash3: Gets a long from a byte buffer in little endian byte order.
getMax() - Method in class org.tribuo.evaluation.DescriptiveStats: Calculates the max of the values.
getMax() - Method in class org.tribuo.RealInfo: Gets the maximum observed value.
getMax() - Method in class org.tribuo.util.MeanVarianceAccumulator: Gets the maximum observed value.
getMaxFeatureID() - Method in class org.tribuo.datasource.LibSVMDataSource: Gets the maximum feature ID found.
getMean() - Method in class org.tribuo.evaluation.DescriptiveStats: Calculates the mean of the values.
getMean() - Method in class org.tribuo.RealInfo: Gets the sample mean.
getMean() - Method in class org.tribuo.util.MeanVarianceAccumulator: Gets the sample mean.
getMemberProvenance() - Method in class org.tribuo.provenance.EnsembleModelProvenance: Get the provenances for each ensemble member.
getMetadata() - Method in class org.tribuo.Example: Returns a copy of this example's metadata.
getMetadataValue(String) - Method in class org.tribuo.Example: Gets the associated metadata value for this key, if it exists.
getMin() - Method in class org.tribuo.evaluation.DescriptiveStats: Calculates the min of the values.
getMin() - Method in class org.tribuo.RealInfo: Gets the minimum observed value.
getMin() - Method in class org.tribuo.util.MeanVarianceAccumulator: Gets the minimum observed value.
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 class org.tribuo.evaluation.metrics.MetricContext: Gets the Model used by this context.
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 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.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.
getNumActiveFeatures() - Method in class org.tribuo.Prediction: Returns the number of features used in the prediction.
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.dataset.SelectedFeatureDataset: 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.
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.
getOS() - Method in class org.tribuo.provenance.ModelProvenance: The name of the OS used to create this model.
getOutput() - Method in class org.tribuo.Example: Gets the example's Output.
getOutput() - Method in class org.tribuo.Prediction: Returns the predicted output.
getOutput(int) - Method in interface org.tribuo.ImmutableOutputInfo: Returns the output associated with this id, or null if the id is unknown.
getOutputFactory() - Method in class org.tribuo.Dataset: Gets the output factory this dataset contains.
getOutputFactory() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
getOutputFactory() - Method in class org.tribuo.datasource.AggregateDataSource
getOutputFactory() - Method in interface org.tribuo.DataSource: Returns the OutputFactory associated with this Output subclass.
getOutputFactory() - Method in class org.tribuo.datasource.IDXDataSource
getOutputFactory() - Method in class org.tribuo.datasource.LibSVMDataSource
getOutputFactory() - Method in class org.tribuo.datasource.ListDataSource
getOutputFactory() - Method in class org.tribuo.sequence.SequenceDataset: Gets the output factory.
getOutputFactory() - Method in interface org.tribuo.sequence.SequenceDataSource: Gets the OutputFactory which was used to generate the Outputs in this SequenceDataSource.
getOutputID() - Method in class org.tribuo.impl.IndexedArrayExample: Gets the output id dimension number.
getOutputIDInfo() - Method in class org.tribuo.Dataset: Returns or generates an ImmutableOutputInfo.
getOutputIDInfo() - Method in class org.tribuo.ImmutableDataset
getOutputIDInfo() - Method in class org.tribuo.Model: Gets the output domain.
getOutputIDInfo() - Method in class org.tribuo.MutableDataset
getOutputIDInfo() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
getOutputIDInfo() - Method in class org.tribuo.sequence.MutableSequenceDataset
getOutputIDInfo() - Method in class org.tribuo.sequence.SequenceDataset: An immutable view on the output info in this dataset.
getOutputIDInfo() - Method in class org.tribuo.sequence.SequenceModel: Gets the output domain.
getOutputInfo() - Method in class org.tribuo.dataset.DatasetView
getOutputInfo() - Method in class org.tribuo.Dataset: Returns this dataset's OutputInfo.
getOutputInfo() - Method in class org.tribuo.ImmutableDataset
getOutputInfo() - Method in class org.tribuo.MutableDataset
getOutputInfo() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
getOutputInfo() - Method in class org.tribuo.sequence.MutableSequenceDataset
getOutputInfo() - Method in class org.tribuo.sequence.SequenceDataset: The output info in this dataset.
getOutputs() - Method in class org.tribuo.dataset.DatasetView: Gets the set of outputs that occur in the examples in this dataset.
getOutputs() - Method in class org.tribuo.Dataset: Gets the set of outputs that occur in the examples in this dataset.
getOutputs() - Method in class org.tribuo.ImmutableDataset
getOutputs() - Method in class org.tribuo.MutableDataset: Gets the set of possible outputs in this dataset.
getOutputs() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
getOutputs() - Method in class org.tribuo.sequence.MutableSequenceDataset
getOutputs() - Method in class org.tribuo.sequence.SequenceDataset: Gets the set of labels that occur in the examples in this dataset.
getOutputScores() - Method in class org.tribuo.Prediction: Gets the output scores for each output.
getOutputTarget() - Method in class org.tribuo.evaluation.metrics.MetricTarget: Returns the Output this metric targets, or Optional.empty() if it's an average.
getPrediction() - Method in class org.tribuo.Excuse: Returns the prediction being excused.
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.
getProvenance() - Method in class org.tribuo.dataset.DatasetView
getProvenance() - Method in class org.tribuo.dataset.MinimumCardinalityDataset
getProvenance() - Method in class org.tribuo.dataset.SelectedFeatureDataset
getProvenance() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
getProvenance() - Method in class org.tribuo.datasource.AggregateDataSource
getProvenance() - Method in class org.tribuo.datasource.IDXDataSource
getProvenance() - Method in class org.tribuo.datasource.LibSVMDataSource
getProvenance() - Method in class org.tribuo.datasource.ListDataSource
getProvenance() - Method in class org.tribuo.ensemble.BaggingTrainer
getProvenance() - Method in class org.tribuo.ensemble.EnsembleModel
getProvenance() - Method in class org.tribuo.hash.HashCodeHasher
getProvenance() - Method in class org.tribuo.hash.HashingTrainer
getProvenance() - Method in class org.tribuo.hash.MessageDigestHasher
getProvenance() - Method in class org.tribuo.hash.ModHashCodeHasher
getProvenance() - Method in class org.tribuo.ImmutableDataset
getProvenance() - Method in class org.tribuo.Model
getProvenance() - Method in class org.tribuo.MutableDataset
getProvenance() - Method in class org.tribuo.SelectedFeatureSet
getProvenance() - Method in class org.tribuo.sequence.HashingSequenceTrainer
getProvenance() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
getProvenance() - Method in class org.tribuo.sequence.IndependentSequenceTrainer
getProvenance() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset
getProvenance() - Method in class org.tribuo.sequence.MutableSequenceDataset
getProvenance() - Method in class org.tribuo.sequence.SequenceModel
getProvenance() - Method in class org.tribuo.transform.TransformationMap
getProvenance() - Method in class org.tribuo.transform.TransformationMap.TransformationList
getProvenance() - Method in class org.tribuo.transform.transformations.BinningTransformation
getProvenance() - Method in class org.tribuo.transform.transformations.IDFTransformation
getProvenance() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation
getProvenance() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation
getProvenance() - Method in class org.tribuo.transform.transformations.SimpleTransform
getProvenance() - Method in class org.tribuo.transform.TransformerMap
getProvenance() - Method in class org.tribuo.transform.TransformTrainer
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.
getScores() - Method in class org.tribuo.Excuse: Returns the scores for all outputs and the relevant feature values.
getSelectedFeatures() - Method in class org.tribuo.dataset.SelectedFeatureDataset: The subset of the selected feature set.
getSequenceModel() - Method in class org.tribuo.evaluation.metrics.MetricContext: Gets the SequenceModel used by this context.
getSerializableForm(boolean) - Method in interface org.tribuo.Output: Generates a String suitable for writing to a csv or json file.
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.
getStandardDeviation() - Method in class org.tribuo.evaluation.DescriptiveStats: Calculates the standard deviation of the values.
getStdDev() - Method in class org.tribuo.util.MeanVarianceAccumulator: Gets the sample standard deviation.
getTag() - Method in class org.tribuo.dataset.DatasetView: The tag associated with this dataset, if it exists.
getTarget() - Method in interface org.tribuo.evaluation.metrics.EvaluationMetric: The target for this metric instance.
getTest() - Method in class org.tribuo.evaluation.TrainTestSplitter: Gets the testing datasource.
getTestDatasetProvenance() - Method in class org.tribuo.provenance.EvaluationProvenance: The test dataset provenance.
getTopFeatures(int) - Method in class org.tribuo.ensemble.EnsembleModel
getTopFeatures(int) - Method in class org.tribuo.Model: Gets the top n features associated with this model.
getTopFeatures(int) - Method in class org.tribuo.sequence.IndependentSequenceModel
getTopFeatures(int) - Method in class org.tribuo.sequence.SequenceModel: Gets the top n features associated with this model.
getTopFeatures(int) - Method in class org.tribuo.transform.TransformedModel
getTotalObservations() - Method in interface org.tribuo.ImmutableOutputInfo: Returns the total number of observed outputs seen by this ImmutableOutputInfo.
getTrain() - Method in class org.tribuo.evaluation.TrainTestSplitter: Gets the training data source.
getTrainerProvenance() - Method in class org.tribuo.provenance.ModelProvenance: The trainer provenance.
getTrainingTime() - Method in class org.tribuo.provenance.ModelProvenance: The training timestamp.
getTransformationProvenance() - Method in class org.tribuo.provenance.DatasetProvenance: The transformation provenances, in application order.
getTransformerMap() - Method in class org.tribuo.transform.TransformedModel: Gets the transformers that this model applies to each example.
getTribuoVersion() - Method in class org.tribuo.provenance.DatasetProvenance: The Tribuo version used to create this dataset.
getTribuoVersion() - Method in class org.tribuo.provenance.EvaluationProvenance: The Tribuo version used to create this dataset.
getTribuoVersion() - Method in class org.tribuo.provenance.FeatureSetProvenance: The Tribuo version used to create this feature set.
getTribuoVersion() - Method in class org.tribuo.provenance.ModelProvenance: The Tribuo version used to create this model.
getTribuoVersion() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance: The Tribuo version.
getTypeWitness() - Method in interface org.tribuo.ensemble.EnsembleCombiner: The type witness used when deserializing the combiner from a protobuf.
getTypeWitness() - Method in interface org.tribuo.OutputFactory: Gets the output class that this factory supports.
getUniqueObservations() - Method in class org.tribuo.CategoricalInfo: Gets the number of unique values this CategoricalInfo has observed.
getUnknownCount() - Method in interface org.tribuo.OutputInfo: Returns the number of unknown Output instances (generated by OutputFactory.getUnknownOutput()) that this OutputInfo has seen.
getUnknownOutput() - Method in interface org.tribuo.OutputFactory: Returns the singleton unknown output of type T which can be used for prediction time examples.
getValue() - Method in class org.tribuo.Feature: Returns the feature value.
getValues() - Method in class org.tribuo.CategoricalInfo: Returns an array containing the observed values ordered by Double.compare(double, double).
getVariance() - Method in class org.tribuo.evaluation.DescriptiveStats: Calculates the sample variance of the values.
getVariance() - Method in class org.tribuo.RealInfo: Gets the sample variance.
getVariance() - Method in class org.tribuo.util.MeanVarianceAccumulator: Gets the sample variance.
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.
growArray() - Method in class org.tribuo.impl.ArrayExample: Grows the backing arrays by size+1.
growArray() - Method in class org.tribuo.impl.BinaryFeaturesExample: Grows the backing arrays by size+1.
growArray(int) - Method in class org.tribuo.impl.ArrayExample: Grows the backing arrays storing the names and values.
growArray(int) - Method in class org.tribuo.impl.BinaryFeaturesExample: Grows the backing arrays storing the names.
growArray(int) - Method in class org.tribuo.impl.IndexedArrayExample

H

hash(String) - Method in class org.tribuo.hash.HashCodeHasher
hash(String) - Method in class org.tribuo.hash.Hasher: Hashes the supplied input using the hashing function.
hash(String) - Method in class org.tribuo.hash.MessageDigestHasher
hash(String) - Method in class org.tribuo.hash.ModHashCodeHasher
hashCode() - Method in class org.tribuo.CategoricalIDInfo
hashCode() - Method in class org.tribuo.CategoricalInfo
hashCode() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance
hashCode() - Method in class org.tribuo.dataset.MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance
hashCode() - Method in class org.tribuo.dataset.SelectedFeatureDataset.SelectedFeatureDatasetProvenance
hashCode() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
hashCode() - Method in class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance
hashCode() - Method in class org.tribuo.evaluation.DescriptiveStats
hashCode() - Method in class org.tribuo.evaluation.metrics.MetricTarget
hashCode() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
hashCode() - Method in class org.tribuo.Feature
hashCode() - Method in class org.tribuo.FeatureMap
hashCode() - Method in class org.tribuo.hash.HashCodeHasher
hashCode() - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
hashCode() - Method in class org.tribuo.hash.MessageDigestHasher
hashCode() - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
hashCode() - Method in class org.tribuo.hash.ModHashCodeHasher
hashCode() - Method in class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
hashCode() - Method in class org.tribuo.impl.ArrayExample
hashCode() - Method in class org.tribuo.impl.BinaryFeaturesExample
hashCode() - Method in class org.tribuo.impl.DatasetDataCarrier
hashCode() - Method in class org.tribuo.impl.IndexedArrayExample
hashCode() - Method in class org.tribuo.impl.ListExample
hashCode() - Method in class org.tribuo.impl.ModelDataCarrier
hashCode() - Method in class org.tribuo.MutableFeatureMap
hashCode() - Method in class org.tribuo.provenance.DatasetProvenance
hashCode() - Method in class org.tribuo.provenance.EnsembleModelProvenance
hashCode() - Method in class org.tribuo.provenance.EvaluationProvenance
hashCode() - Method in class org.tribuo.provenance.FeatureSetProvenance
hashCode() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
hashCode() - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
hashCode() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
hashCode() - Method in class org.tribuo.provenance.ModelProvenance
hashCode() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
hashCode() - Method in class org.tribuo.provenance.SkeletalTrainerProvenance
hashCode() - Method in class org.tribuo.RealIDInfo
hashCode() - Method in class org.tribuo.RealInfo
hashCode() - Method in class org.tribuo.SelectedFeatureSet: Computes the hash code.
hashCode() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance
hashCode() - Method in class org.tribuo.sequence.SequenceExample
hashCode() - Method in class org.tribuo.SkeletalVariableInfo
hashCode() - Method in class org.tribuo.transform.TransformationMap.TransformationList
hashCode() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformationProvenance
hashCode() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformer
hashCode() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance
hashCode() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance
hashCode() - Method in class org.tribuo.transform.transformations.SimpleTransform
hashCode() - Method in class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance
hashCode() - Method in class org.tribuo.transform.TransformerMap
hashCode() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
hashCode() - Method in class org.tribuo.util.IntDoublePair
hashCode() - Method in class org.tribuo.util.MeanVarianceAccumulator
HashCodeHasher - Class in org.tribuo.hash: Hashes names using String.hashCode().
HashCodeHasher(String) - Constructor for class org.tribuo.hash.HashCodeHasher: Constructs a HashCodeHasher using the specified salt value.
HashCodeHasher.HashCodeHasherProvenance - Class in org.tribuo.hash: Provenance for the HashCodeHasher.
HashCodeHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance: Deserialization constructor.
HashedFeatureMap - Class in org.tribuo.hash: A FeatureMap used by the HashingTrainer to provide feature name hashing and guarantee that the Model does not contain feature name information, but still works with unhashed features names.
Hasher - Class in org.tribuo.hash: An abstract base class for hash functions used to hash the names of features.
Hasher() - Constructor for class org.tribuo.hash.Hasher
hashFeatureMap(Dataset<T>, Hasher) - Static method in class org.tribuo.ImmutableDataset: Creates an immutable shallow copy of the supplied dataset, using the hasher to generate a HashedFeatureMap which transparently maps from the feature name to the hashed variant.
HashingOptions - Class in org.tribuo.hash: An Options implementation which provides CLI arguments for the model hashing functionality.
HashingOptions() - Constructor for class org.tribuo.hash.HashingOptions
HashingOptions.ModelHashingType - Enum in org.tribuo.hash: Supported types of hashes in CLI programs.
HashingSequenceTrainer<T> - Class in org.tribuo.sequence: A SequenceTrainer that hashes all the feature names on the way in.
HashingSequenceTrainer(SequenceTrainer<T>, Hasher) - Constructor for class org.tribuo.sequence.HashingSequenceTrainer: Constructs a hashing sequence trainer using the supplied parameters.
HashingSequenceTrainer.HashingSequenceTrainerProvenance - Class in org.tribuo.sequence: Provenance for HashingSequenceTrainer.
HashingSequenceTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.sequence.HashingSequenceTrainer.HashingSequenceTrainerProvenance: Deserialization constructor.
HashingTrainer<T> - Class in org.tribuo.hash: A Trainer which hashes the Dataset before the Model is produced.
HashingTrainer(Trainer<T>, Hasher) - Constructor for class org.tribuo.hash.HashingTrainer: Constructs a hashing trainer using the supplied parameters.
hasProbabilities() - Method in class org.tribuo.Prediction: Are the scores probabilities?
HC - Enum constant in enum org.tribuo.hash.HashingOptions.ModelHashingType: Uses the String hash code.
HTMLOutput - Class in org.tribuo.util: Utilities for nice HTML output that can be put in wikis and such.

I

id - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple: The feature id number.
IDFTransformation - Class in org.tribuo.transform.transformations: A feature transformation that computes the IDF for features and then transforms them with a TF-IDF weighting.
IDFTransformation() - Constructor for class org.tribuo.transform.transformations.IDFTransformation: Constructs an IDFTransformation.
IDFTransformation.IDFTransformationProvenance - Class in org.tribuo.transform.transformations: Provenance for IDFTransformation.
IDFTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.IDFTransformation.IDFTransformationProvenance: Deserialization constructor.
idIterator() - Method in class org.tribuo.impl.IndexedArrayExample: Iterator over the feature ids and values.
idMap - Variable in class org.tribuo.ImmutableFeatureMap: The map from id numbers to the feature infos.
IDXDataSource<T> - Class in org.tribuo.datasource: A DataSource which can read IDX formatted data (i.e., MNIST).
IDXDataSource(Path, Path, OutputFactory<T>) - Constructor for class org.tribuo.datasource.IDXDataSource: Constructs an IDXDataSource from the supplied paths.
IDXDataSource.IDXData - Class in org.tribuo.datasource: Java side representation for an IDX file.
IDXDataSource.IDXDataSourceProvenance - Class in org.tribuo.datasource: Provenance class for IDXDataSource.
IDXDataSource.IDXType - Enum in org.tribuo.datasource: The possible IDX input formats.
IDXDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance: Deserialization constructor.
ImmutableDataset<T> - Class in org.tribuo: This is a Dataset which has an ImmutableFeatureMap to store the feature information.
ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(DataSource<T>, FeatureMap, OutputInfo<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(DataSource<T>, Model<T>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Creates a dataset from a data source.
ImmutableDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.ImmutableDataset: If you call this it's your job to setup outputMap, featureIDMap and fill it with examples.
ImmutableDataset(DataProvenance, OutputFactory<T>, String, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Example<T>>, boolean) - Constructor for class org.tribuo.ImmutableDataset: Deserialization constructor.
ImmutableDataset(DataProvenance, OutputFactory<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.ImmutableDataset: This is dangerous, and should not be used unless you've overridden everything in ImmutableDataset.
ImmutableFeatureMap - Class in org.tribuo: ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
ImmutableFeatureMap() - Constructor for class org.tribuo.ImmutableFeatureMap: Constructs a new empty immutable feature map.
ImmutableFeatureMap(List<VariableInfo>) - Constructor for class org.tribuo.ImmutableFeatureMap: Constructs a new immutable feature map copying the supplied variable infos and generating appropriate ID numbers.
ImmutableFeatureMap(FeatureMap) - Constructor for class org.tribuo.ImmutableFeatureMap: Constructs a new immutable version which is a deep copy of the supplied feature map, generating new ID numbers.
ImmutableOutputInfo<T> - Interface in org.tribuo: An OutputInfo that is fixed, and contains an id number for each valid output.
ImmutableSequenceDataset<T> - Class in org.tribuo.sequence: This is a SequenceDataset which has an ImmutableFeatureMap to store the feature information.
ImmutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, FeatureMap, OutputInfo<T>, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: Creates a dataset from a data source.
ImmutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: Creates a dataset from a data source.
ImmutableSequenceDataset(DataProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: This is dangerous, and should not be used unless you've overridden everything in ImmutableSequenceDataset.
ImmutableSequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: If you call this it's your job to setup outputIDInfo and featureIDMap.
ImmutableSequenceDataset(DataProvenance, OutputFactory<T>, String, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<SequenceExample<T>>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: Deserialization constructor.
ImmutableSequenceDataset(SequenceDataSource<T>, FeatureMap, OutputInfo<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: Creates a dataset from a data source, using the specified output and feature domains.
ImmutableSequenceDataset(SequenceDataSource<T>, SequenceModel<T>) - Constructor for class org.tribuo.sequence.ImmutableSequenceDataset: Creates a dataset from a data source, taking the output and feature domains from the supplied model.
INCREMENT_INVOCATION_COUNT - Static variable in interface org.tribuo.Trainer: When training a model, passing this value will inform the trainer to simply increment the invocation count rather than set a new one
incrementalTrain(Dataset<T>, U) - Method in interface org.tribuo.IncrementalTrainer: Incrementally trains the supplied model with the new data.
IncrementalTrainer<T,U> - Interface in org.tribuo: An interface for incremental training of Models.
IndependentSequenceModel<T> - Class in org.tribuo.sequence: A SequenceModel which independently predicts each element of the sequence.
IndependentSequenceTrainer<T> - Class in org.tribuo.sequence: Trains a sequence model by training a regular model to independently predict every example in each sequence.
IndependentSequenceTrainer(Trainer<T>) - Constructor for class org.tribuo.sequence.IndependentSequenceTrainer: Builds a sequence trainer which uses a Trainer to independently predict each sequence element.
index - Variable in class org.tribuo.util.IntDoublePair: The key.
IndexedArrayExample<T> - Class in org.tribuo.impl: A version of ArrayExample which also has the id numbers.
IndexedArrayExample(Example<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample: This constructor removes unknown features.
IndexedArrayExample(IndexedArrayExample<T>) - Constructor for class org.tribuo.impl.IndexedArrayExample: Copy constructor.
IndexedArrayExample.FeatureTuple - Class in org.tribuo.impl: A tuple of the feature name, id and value.
indices - Variable in class org.tribuo.Dataset: The indices of the shuffled order.
innerPredict(Iterable<Example<T>>) - Method in class org.tribuo.Model: Called by the base implementations of Model.predict(Iterable) and Model.predict(Dataset).
innerTrainer - Variable in class org.tribuo.ensemble.BaggingTrainer
inPlaceAdd(double[], double[]) - Static method in class org.tribuo.util.Util: Adds update to input in place.
inPlaceAdd(float[], float[]) - Static method in class org.tribuo.util.Util: Adds update to input in place.
inplaceNormalizeToDistribution(double[]) - Static method in class org.tribuo.util.Util: Normalizes the input array in place.
inplaceNormalizeToDistribution(float[]) - Static method in class org.tribuo.util.Util: Normalizes the input array in place.
inPlaceSubtract(double[], double[]) - Static method in class org.tribuo.util.Util: Subtracts update from input in place.
inPlaceSubtract(float[], float[]) - Static method in class org.tribuo.util.Util: Subtracts update from input in place.
INSTANCE_VALUES - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the instance values field.
instanceProvenance - Variable in class org.tribuo.provenance.ModelProvenance: Any instance time information supplied by the users.
INT - Enum constant in enum org.tribuo.datasource.IDXDataSource.IDXType: A 32-bit integer.
IntDoublePair - Class in org.tribuo.util: A Pair of a primitive int and a primitive double.
IntDoublePair(int, double) - Constructor for class org.tribuo.util.IntDoublePair: Constructs a tuple out of an int and a double.
internalProvenances() - Method in class org.tribuo.provenance.EnsembleModelProvenance
internalProvenances() - Method in class org.tribuo.provenance.FeatureSetProvenance: Returns a list of all the provenances in this model provenance so subclasses can append to the list.
internalProvenances() - Method in class org.tribuo.provenance.ModelProvenance: Returns a list of all the provenances in this model provenance so subclasses can append to the list.
IS_SEQUENCE - Static variable in interface org.tribuo.provenance.TrainerProvenance: The name of the provenance field recording if this is a sequence trainer.
IS_SNAPSHOT - Static variable in class org.tribuo.Tribuo: Is this a snapshot build.
isBinary(Feature) - Static method in class org.tribuo.impl.BinaryFeaturesExample: Is the supplied feature binary (i.e., does it have a value of 1.0)?
isDense() - Method in class org.tribuo.MutableDataset: Is the dataset dense (i.e., do all features in the domain have a value in each example).
isDense() - Method in class org.tribuo.provenance.DatasetProvenance: Is the Dataset dense?
isDense() - Method in class org.tribuo.sequence.MutableSequenceDataset: Is the dataset dense (i.e., do all features in the domain have a value in each example).
isDense(FeatureMap) - Method in class org.tribuo.Example: Is this example dense wrt the supplied feature map.
isDense(FeatureMap) - Method in class org.tribuo.impl.ArrayExample
isDense(FeatureMap) - Method in class org.tribuo.impl.BinaryFeaturesExample
isDense(FeatureMap) - Method in class org.tribuo.impl.ListExample
isDense(FeatureMap) - Method in class org.tribuo.sequence.SequenceExample: Is this sequence example dense wrt the supplied feature map.
isOrdered() - Method in interface org.tribuo.FeatureSelector: Does this feature selection algorithm return an ordered feature set?
isOrdered() - Method in class org.tribuo.SelectedFeatureSet: Is this feature set ordered?
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.
isWeighted() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance: Is this view a weighted bootstrap sample.
isZeroIndexed() - Method in class org.tribuo.datasource.LibSVMDataSource: Returns true if this dataset is zero indexed, false otherwise (i.e., it starts from 1).
iterator() - Method in class org.tribuo.dataset.DatasetView
iterator() - Method in class org.tribuo.Dataset
iterator() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
iterator() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
iterator() - Method in class org.tribuo.datasource.AggregateDataSource
iterator() - Method in class org.tribuo.datasource.IDXDataSource
iterator() - Method in class org.tribuo.datasource.LibSVMDataSource
iterator() - Method in class org.tribuo.datasource.ListDataSource
iterator() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
iterator() - Method in class org.tribuo.FeatureMap
iterator() - Method in class org.tribuo.impl.ArrayExample
iterator() - Method in class org.tribuo.impl.BinaryFeaturesExample
iterator() - Method in class org.tribuo.impl.ListExample
iterator() - Method in class org.tribuo.provenance.DatasetProvenance
iterator() - Method in class org.tribuo.provenance.EvaluationProvenance
iterator() - Method in class org.tribuo.provenance.FeatureSetProvenance: Calls FeatureSetProvenance.internalProvenances() and returns the iterator from that list.
iterator() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
iterator() - Method in class org.tribuo.provenance.ModelProvenance: Calls ModelProvenance.internalProvenances() and returns the iterator from that list.
iterator() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
iterator() - Method in class org.tribuo.sequence.SequenceDataset
iterator() - Method in class org.tribuo.sequence.SequenceExample
iterator() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance

J

JAVA_VERSION_STRING - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the Java version field.
javaVersionString - Variable in class org.tribuo.provenance.ModelProvenance: The Java version string.

K

keySet() - Method in class org.tribuo.FeatureMap: Returns all the feature names in the domain.
keysName() - Element in annotation type org.tribuo.protos.ProtoSerializableKeysValuesField: The name of the key field in the protobuf in Java.
KFoldSplitter<T> - Class in org.tribuo.evaluation: A k-fold splitter to be used in cross-validation.
KFoldSplitter(int) - Constructor for class org.tribuo.evaluation.KFoldSplitter: Builds a k-fold splitter using Trainer.DEFAULT_SEED as the seed.
KFoldSplitter(int, long) - Constructor for class org.tribuo.evaluation.KFoldSplitter: Builds a k-fold splitter.
KFoldSplitter.TrainTestFold<T> - Class in org.tribuo.evaluation: Stores a train/test split for a dataset.

L

LibSVMDataSource<T> - Class in org.tribuo.datasource: A DataSource which can read LibSVM formatted data.
LibSVMDataSource(URL, OutputFactory<T>) - Constructor for class org.tribuo.datasource.LibSVMDataSource: Constructs a LibSVMDataSource from the supplied URL and output factory.
LibSVMDataSource(URL, OutputFactory<T>, boolean, int) - Constructor for class org.tribuo.datasource.LibSVMDataSource: Constructs a LibSVMDataSource from the supplied URL and output factory.
LibSVMDataSource(Path, OutputFactory<T>) - Constructor for class org.tribuo.datasource.LibSVMDataSource: Constructs a LibSVMDataSource from the supplied path and output factory.
LibSVMDataSource(Path, OutputFactory<T>, boolean, int) - Constructor for class org.tribuo.datasource.LibSVMDataSource: Constructs a LibSVMDataSource from the supplied path and output factory.
LibSVMDataSource.LibSVMDataSourceProvenance - Class in org.tribuo.datasource: The provenance for a LibSVMDataSource.
LibSVMDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.datasource.LibSVMDataSource.LibSVMDataSourceProvenance: Constructs a provenance during unmarshalling.
LinearScalingTransformation - Class in org.tribuo.transform.transformations: A Transformation which takes an observed distribution and rescales it so all values are between the desired min and max.
LinearScalingTransformation() - Constructor for class org.tribuo.transform.transformations.LinearScalingTransformation: Defaults to zero - one.
LinearScalingTransformation(double, double) - Constructor for class org.tribuo.transform.transformations.LinearScalingTransformation: Constructs a LinearScalingTransformation which puts feature values into the specified range.
LinearScalingTransformation.LinearScalingTransformationProvenance - Class in org.tribuo.transform.transformations: Provenance for LinearScalingTransformation.
LinearScalingTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.LinearScalingTransformation.LinearScalingTransformationProvenance: Deserialization constructor.
list - Variable in class org.tribuo.transform.TransformationMap.TransformationList: The list of transformations.
ListDataSource<T> - Class in org.tribuo.datasource: A data source which wraps up a list of Examples along with their DataSourceProvenance and an OutputFactory.
ListDataSource(List<Example<T>>, OutputFactory<T>, DataSourceProvenance) - Constructor for class org.tribuo.datasource.ListDataSource: Constructs an in-memory data source wrapping the supplied examples.
ListExample<T> - Class in org.tribuo.impl: This class will not be performant until value types are available in Java.
ListExample(Example<T>) - Constructor for class org.tribuo.impl.ListExample: Copies the supplied example's features, weight, output and metadata into this example.
ListExample(T) - Constructor for class org.tribuo.impl.ListExample: Constructs a ListExample for the specified output with a weight of Example.DEFAULT_WEIGHT.
ListExample(T, float) - Constructor for class org.tribuo.impl.ListExample: Constructs a ListExample for the specified output and weight.
ListExample(T, String[], double[]) - Constructor for class org.tribuo.impl.ListExample: Constructs a ListExample from the specified output, feature names and feature values.
ListExample(T, List<? extends Feature>) - Constructor for class org.tribuo.impl.ListExample: Constructs a ListExample using the specified output and feature list.
loadModel(CommandInterpreter, File, boolean) - Method in class org.tribuo.ModelExplorer: Loads a model.
loadModel(CommandInterpreter, File, boolean) - Method in class org.tribuo.sequence.SequenceModelExplorer: Loads a model.
log - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Logs the inputs (base_e)
log() - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that applies Math.log(double).
logVector(Logger, Level, double[]) - Static method in class org.tribuo.util.Util: Logs the supplied array to the supplied logger at the specified level.
logVector(Logger, Level, float[]) - Static method in class org.tribuo.util.Util: Logs the supplied array to the supplied logger at the specified level.
LongPair() - Constructor for class org.tribuo.util.MurmurHash3.LongPair
lookup(String) - Method in class org.tribuo.Example: Returns the Feature in this Example which has the supplied name, if it's present.
lookup(String) - Method in class org.tribuo.impl.ArrayExample
lookup(String) - Method in class org.tribuo.impl.BinaryFeaturesExample
lookup(String) - Method in class org.tribuo.impl.ListExample

M

m - Variable in class org.tribuo.FeatureMap: Map from the feature names to their info.
MACRO - Enum constant in enum org.tribuo.evaluation.metrics.EvaluationMetric.Average: The macro average.
macroAverageTarget() - Static method in class org.tribuo.evaluation.metrics.MetricTarget: Get the singleton MetricTarget which contains the EvaluationMetric.Average.MACRO.
main(String[]) - Static method in class org.tribuo.ModelExplorer: Entry point.
main(String[]) - Static method in class org.tribuo.sequence.SequenceModelExplorer: Runs the sequence model explorer.
MAJOR_VERSION - Static variable in class org.tribuo.Tribuo: The major version number.
makeIDInfo(int) - Method in class org.tribuo.CategoricalIDInfo
makeIDInfo(int) - Method in class org.tribuo.CategoricalInfo
makeIDInfo(int) - Method in class org.tribuo.RealIDInfo
makeIDInfo(int) - Method in class org.tribuo.RealInfo
makeIDInfo(int) - Method in interface org.tribuo.VariableInfo: Generates a VariableIDInfo subclass which represents the same feature.
max - Variable in class org.tribuo.RealInfo: The maximum observed feature value.
max() - Static method in interface org.tribuo.util.Merger: A merger which takes the maximum element.
mean - Variable in class org.tribuo.RealInfo: The feature mean.
mean(double[]) - Static method in class org.tribuo.util.Util: Returns the mean of the input array.
mean(double[], int) - Static method in class org.tribuo.util.Util: Computes the mean of the first length elements of array.
mean(Collection<V>) - Static method in class org.tribuo.util.Util: Computes the mean of the collection.
meanAndVariance(double[]) - Static method in class org.tribuo.util.Util: Returns the mean and variance of the input.
meanAndVariance(double[], int) - Static method in class org.tribuo.util.Util: Returns the mean and variance of the input's first length elements.
MeanStdDevTransformation - Class in org.tribuo.transform.transformations: A Transformation which takes an observed distribution and rescales it so it has the desired mean and standard deviation.
MeanStdDevTransformation() - Constructor for class org.tribuo.transform.transformations.MeanStdDevTransformation: Defaults to zero mean, one std dev.
MeanStdDevTransformation(double, double) - Constructor for class org.tribuo.transform.transformations.MeanStdDevTransformation: Constructs a MeanStdDevTransformation targetting the specified mean and standard deviation.
MeanStdDevTransformation.MeanStdDevTransformationProvenance - Class in org.tribuo.transform.transformations: Provenance for MeanStdDevTransformation.
MeanStdDevTransformationProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.MeanStdDevTransformation.MeanStdDevTransformationProvenance: Deserialization constructor.
MeanVarianceAccumulator - Class in org.tribuo.util: An accumulator for online calculation of the mean and variance of a stream of doubles.
MeanVarianceAccumulator() - Constructor for class org.tribuo.util.MeanVarianceAccumulator: Constructs an empty mean/variance accumulator.
MeanVarianceAccumulator(double[]) - Constructor for class org.tribuo.util.MeanVarianceAccumulator: Constructs a mean/variance accumulator and observes the supplied array.
MeanVarianceAccumulator(MeanVarianceAccumulator) - Constructor for class org.tribuo.util.MeanVarianceAccumulator: Copy constructor.
MEMBERS - Static variable in class org.tribuo.provenance.EnsembleModelProvenance: The name of the provenance field where the member provenances are stored.
merge(double, double) - Method in interface org.tribuo.util.Merger: Merges first and second.
merge(MeanVarianceAccumulator, MeanVarianceAccumulator) - Static method in class org.tribuo.util.MeanVarianceAccumulator: Implement Chan's algorithm for merging two mean variance accumulators.
Merger - Interface in org.tribuo.util: An interface which can merge double values.
MessageDigestHasher - Class in org.tribuo.hash: Hashes Strings using the supplied MessageDigest type.
MessageDigestHasher(String, String) - Constructor for class org.tribuo.hash.MessageDigestHasher: Constructs a message digest hasher.
MessageDigestHasher.MessageDigestHasherProvenance - Class in org.tribuo.hash: Provenance for MessageDigestHasher.
MessageDigestHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance: Deserialization constructor.
metadata - Variable in class org.tribuo.Example: The example metadata.
MetricContext<T> - Class in org.tribuo.evaluation.metrics: The context for a metric or set of metrics.
MetricContext(Model<T>, List<Prediction<T>>) - Constructor for class org.tribuo.evaluation.metrics.MetricContext: Constructs a metric context.
MetricContext(SequenceModel<T>, List<Prediction<T>>) - Constructor for class org.tribuo.evaluation.metrics.MetricContext: Constructs a metric context for a sequence model.
MetricID<T> - Class in org.tribuo.evaluation.metrics: Just an easier-to-read alias for Pair<MetricTarget<T>, String>.
MetricID(MetricTarget<T>, String) - Constructor for class org.tribuo.evaluation.metrics.MetricID: Constructs a metric id.
MetricTarget<T> - Class in org.tribuo.evaluation.metrics: Used by a given EvaluationMetric to determine whether it should compute its value for a specific Output value or whether it should average them.
MetricTarget(EvaluationMetric.Average) - Constructor for class org.tribuo.evaluation.metrics.MetricTarget: Builds a metric target for an average.
MetricTarget(T) - Constructor for class org.tribuo.evaluation.metrics.MetricTarget: Builds a metric target for an output.
MICRO - Enum constant in enum org.tribuo.evaluation.metrics.EvaluationMetric.Average: The micro average.
microAverageTarget() - Static method in class org.tribuo.evaluation.metrics.MetricTarget: Get the singleton MetricTarget which contains the EvaluationMetric.Average.MICRO.
min - Variable in class org.tribuo.RealInfo: The minimum observed feature value.
min() - Static method in interface org.tribuo.util.Merger: A merger which takes the minimum element.
MIN_LENGTH - Static variable in class org.tribuo.hash.Hasher: The minimum length of the salt.
minCount(CommandInterpreter, int) - Method in class org.tribuo.ModelExplorer: Shows the number of features which occurred more than min count times.
minCount(CommandInterpreter, int) - Method in class org.tribuo.sequence.SequenceModelExplorer: Shows the number of features which occurred more than minCount times in the training data.
MinimumCardinalityDataset<T> - Class in org.tribuo.dataset: This class creates a pruned dataset in which low frequency features that occur less than the provided minimum cardinality have been removed.
MinimumCardinalityDataset(Dataset<T>, int) - Constructor for class org.tribuo.dataset.MinimumCardinalityDataset
MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance - Class in org.tribuo.dataset: Provenance for MinimumCardinalityDataset.
MinimumCardinalityDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.dataset.MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance: Deserialization constructor.
MinimumCardinalitySequenceDataset<T> - Class in org.tribuo.sequence: This class creates a pruned dataset in which low frequency features that occur less than the provided minimum cardinality have been removed.
MinimumCardinalitySequenceDataset(SequenceDataset<T>, int) - Constructor for class org.tribuo.sequence.MinimumCardinalitySequenceDataset
MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance - Class in org.tribuo.sequence: Provenance for MinimumCardinalitySequenceDataset.
MinimumCardinalitySequenceDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.sequence.MinimumCardinalitySequenceDataset.MinimumCardinalitySequenceDatasetProvenance: Deserialization constructor.
MINOR_VERSION - Static variable in class org.tribuo.Tribuo: The minor version number.
MOD - Enum constant in enum org.tribuo.hash.HashingOptions.ModelHashingType: Takes the String hash code mod some value.
Model<T> - Class in org.tribuo: A prediction model, which is used to predict outputs for unseen instances.
Model(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean) - Constructor for class org.tribuo.Model: Constructs a new model, storing the supplied fields.
ModelDataCarrier<T> - Class in org.tribuo.impl: Serialization carrier for common fields in Model and SequenceModel.
ModelDataCarrier(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, String) - Constructor for class org.tribuo.impl.ModelDataCarrier: Constructs a new ModelDataCarrier.
modelDescription(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer: Shows the model description.
ModelExplorer - Class in org.tribuo: A command line interface for loading in models and inspecting their feature and output spaces.
ModelExplorer() - Constructor for class org.tribuo.ModelExplorer: Builds a new model explorer shell.
ModelExplorer.ModelExplorerOptions - Class in org.tribuo: CLI options for ModelExplorer.
ModelExplorerOptions() - Constructor for class org.tribuo.ModelExplorer.ModelExplorerOptions
modelFilename - Variable in class org.tribuo.ModelExplorer.ModelExplorerOptions: Model file to load.
modelFilename - Variable in class org.tribuo.sequence.SequenceModelExplorer.SequenceModelExplorerOptions: Model file to load.
modelHashingAlgorithm - Variable in class org.tribuo.hash.HashingOptions: Hash the model during training, options are {NONE,MOD,HC,SHA1,SHA256}
modelHashingSalt - Variable in class org.tribuo.hash.HashingOptions: Salt for hashing the model
modelProvenance(CommandInterpreter) - Method in class org.tribuo.ModelExplorer: Displays the model provenance.
ModelProvenance - Class in org.tribuo.provenance: Contains provenance information for an instance of a Model.
ModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance) - Constructor for class org.tribuo.provenance.ModelProvenance: Creates a model provenance tracking the class name, creation time, dataset provenance and trainer provenance.
ModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>) - Constructor for class org.tribuo.provenance.ModelProvenance: Creates a model provenance tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance.
ModelProvenance(String, OffsetDateTime, DatasetProvenance, TrainerProvenance, Map<String, Provenance>, boolean) - Constructor for class org.tribuo.provenance.ModelProvenance: Creates a model provenance tracking the class name, creation time, dataset provenance, trainer provenance and any instance specific provenance.
ModelProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.ModelProvenance: Used by the provenance unmarshalling system.
models - Variable in class org.tribuo.ensemble.EnsembleModel: The list of models in this ensemble.
ModHashCodeHasher - Class in org.tribuo.hash: Hashes names using String.hashCode(), then reduces the dimension.
ModHashCodeHasher(int, String) - Constructor for class org.tribuo.hash.ModHashCodeHasher: Constructs a ModHashCodeHasher with the supplied parameters.
ModHashCodeHasher(String) - Constructor for class org.tribuo.hash.ModHashCodeHasher: Constructs a ModHashCodeHasher with a fixed dimensionality of 100.
ModHashCodeHasher.ModHashCodeHasherProvenance - Class in org.tribuo.hash: Provenance for the ModHashCodeHasher.
ModHashCodeHasherProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance: Deserialization constructor.
mul - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Multiplies by the specified constant.
mul(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that multiplies each value by the operand.
MurmurHash3 - Class in org.tribuo.util: The MurmurHash3 algorithm was created by Austin Appleby and placed in the public domain.
MurmurHash3() - Constructor for class org.tribuo.util.MurmurHash3
murmurhash3_x64_128(byte[], int, int, int, MurmurHash3.LongPair) - Static method in class org.tribuo.util.MurmurHash3: Returns the MurmurHash3_x64_128 hash, placing the result in "out".
murmurhash3_x86_32(byte[], int, int, int) - Static method in class org.tribuo.util.MurmurHash3: Returns the MurmurHash3_x86_32 hash.
murmurhash3_x86_32(CharSequence, int, int, int) - Static method in class org.tribuo.util.MurmurHash3: Returns the MurmurHash3_x86_32 hash of the UTF-8 bytes of the String without actually encoding the string to a temporary buffer.
MurmurHash3.LongPair - Class in org.tribuo.util: 128 bits of state
MutableDataset<T> - Class in org.tribuo: A MutableDataset is a Dataset with a MutableFeatureMap which grows over time.
MutableDataset(Iterable<Example<T>>, DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.MutableDataset: Creates a dataset from a data source.
MutableDataset(DataSource<T>) - Constructor for class org.tribuo.MutableDataset: Creates a dataset from a data source.
MutableDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.MutableDataset: Creates an empty dataset.
MutableFeatureMap - Class in org.tribuo: A feature map that can record new feature value observations.
MutableFeatureMap() - Constructor for class org.tribuo.MutableFeatureMap: Creates an empty feature map which converts high cardinality categorical variable infos into reals.
MutableFeatureMap(boolean) - Constructor for class org.tribuo.MutableFeatureMap: Creates an empty feature map which can optionally convert high cardinality categorical variable infos into reals.
MutableOutputInfo<T> - Interface in org.tribuo: A mutable OutputInfo that can record observed output values.
MutableSequenceDataset<T> - Class in org.tribuo.sequence: A MutableSequenceDataset is a SequenceDataset with a MutableFeatureMap which grows over time.
MutableSequenceDataset(Iterable<SequenceExample<T>>, DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset: Creates a dataset from a data source.
MutableSequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset: Creates an empty sequence dataset.
MutableSequenceDataset(ImmutableSequenceDataset<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset: Copies the immutable dataset into a mutable dataset.
MutableSequenceDataset(SequenceDataSource<T>) - Constructor for class org.tribuo.sequence.MutableSequenceDataset: Builds a dataset from the supplied data source.

N

name - Variable in class org.tribuo.Feature: The feature name.
name - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple: The feature name.
name - Variable in class org.tribuo.Model: The model's name.
name - Variable in class org.tribuo.sequence.SequenceModel: The model name.
name - Variable in class org.tribuo.SkeletalVariableInfo: The name of the feature.
name() - Method in class org.tribuo.impl.ModelDataCarrier: The model name.
name() - Element in annotation type org.tribuo.protos.ProtoSerializableField: The name of the field in the protobuf in Java.
name() - Element in annotation type org.tribuo.protos.ProtoSerializableMapField: The name of the field in the protobuf in Java.
NAME - Static variable in class org.tribuo.Example: By convention the example name is stored using this metadata key.
newCapacity(int) - Method in class org.tribuo.impl.ArrayExample: Returns a capacity at least as large as the given minimum capacity.
newCapacity(int) - Method in class org.tribuo.impl.BinaryFeaturesExample: Returns a capacity at least as large as the given minimum capacity.
NONE - Enum constant in enum org.tribuo.hash.HashingOptions.ModelHashingType: No hashing applied.
normalizeToDistribution(double[]) - Static method in class org.tribuo.util.Util: Generates a normalized version of the input array.
normalizeToDistribution(float[]) - Static method in class org.tribuo.util.Util: Generates a normalized version of the input array.
nsplits - Variable in class org.tribuo.evaluation.KFoldSplitter
numFeatures(CommandInterpreter) - Method in class org.tribuo.ModelExplorer: Displays the number of features.
numFeatures(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer: Shows the number of features in this model.
numMembers - Variable in class org.tribuo.ensemble.BaggingTrainer

O

observe(double) - Method in class org.tribuo.CategoricalInfo
observe(double) - Method in class org.tribuo.RealInfo
observe(double) - Method in class org.tribuo.SkeletalVariableInfo: Records the value.
observe(double) - Method in class org.tribuo.util.MeanVarianceAccumulator: Observes a value, i.e., updates the sufficient statistics for computing mean, variance, max and min.
observe(double[]) - Method in class org.tribuo.util.MeanVarianceAccumulator: Observes a value, i.e., updates the sufficient statistics for computing mean, variance, max and min.
observe(List<Prediction<T>>) - Method in class org.tribuo.evaluation.OnlineEvaluator: Records all the supplied predictions.
observe(Prediction<T>) - Method in class org.tribuo.evaluation.OnlineEvaluator: Records the supplied prediction.
observe(T) - Method in interface org.tribuo.MutableOutputInfo: Records an output value or statistics thereof.
observedCount - Variable in class org.tribuo.CategoricalInfo: The count of the observed value if it's only seen a single one.
observedValue - Variable in class org.tribuo.CategoricalInfo: The observed value if it's only seen a single one.
observeSparse() - Method in class org.tribuo.transform.transformations.SimpleTransform: Deprecated.
observeSparse() - Method in interface org.tribuo.transform.TransformStatistics: Deprecated.
in 4.1 as it's unnecessary.
observeSparse(int) - Method in class org.tribuo.transform.transformations.SimpleTransform: No-op on this TransformStatistics.
observeSparse(int) - Method in interface org.tribuo.transform.TransformStatistics: Observes count sparse values.
observeValue(double) - Method in class org.tribuo.transform.transformations.SimpleTransform: No-op on this TransformStatistics.
observeValue(double) - Method in interface org.tribuo.transform.TransformStatistics: Observes a value and updates the statistics.
OnlineEvaluator<T,E> - Class in org.tribuo.evaluation: An evaluator which aggregates predictions and produces Evaluations covering all the Predictions it has seen or created.
OnlineEvaluator(Evaluator<T, E>, Model<T>, DataProvenance) - Constructor for class org.tribuo.evaluation.OnlineEvaluator: Constructs an OnlineEvaluator which accumulates predictions.
ONNXExportable - Interface in org.tribuo: An interface which denotes this Model can be exported as an ONNX model.
org.tribuo - package org.tribuo: Provides the core interfaces and classes for using Tribuo.
org.tribuo.dataset - package org.tribuo.dataset: Provides utility datasets which subsample or otherwise transform the wrapped dataset.
org.tribuo.datasource - package org.tribuo.datasource: Simple data sources for ingesting or aggregating data.
org.tribuo.ensemble - package org.tribuo.ensemble: Provides an interface for model prediction combinations, two base classes for ensemble models, a base class for ensemble excuses, and a Bagging implementation.
org.tribuo.evaluation - package org.tribuo.evaluation: Evaluation base classes, along with code for train/test splits and cross validation.
org.tribuo.evaluation.metrics - package org.tribuo.evaluation.metrics: This package contains the infrastructure classes for building evaluation metrics.
org.tribuo.hash - package org.tribuo.hash: Provides the base interface and implementations of the Model hashing which obscures the feature names stored in a model.
org.tribuo.impl - package org.tribuo.impl: Provides implementations of base classes and interfaces from org.tribuo.
org.tribuo.protos - package org.tribuo.protos: Classes which control the serialization of Tribuo objects to and from protocol buffers.
org.tribuo.provenance - package org.tribuo.provenance: Provides Tribuo specific infrastructure for the Provenance system which tracks models and datasets.
org.tribuo.provenance.impl - package org.tribuo.provenance.impl: Provides internal implementations for empty provenance classes and TrainerProvenance.
org.tribuo.sequence - package org.tribuo.sequence: Provides core classes for working with sequences of Examples.
org.tribuo.transform - package org.tribuo.transform: Provides infrastructure for applying transformations to a Dataset.
org.tribuo.transform.transformations - package org.tribuo.transform.transformations: Provides implementations of standard transformations like binning, scaling, taking logs and exponents.
org.tribuo.util - package org.tribuo.util: Provides utilities which don't have other Tribuo dependencies.
OS_STRING - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the OS name field.
osString - Variable in class org.tribuo.provenance.ModelProvenance: The OS string.
output - Variable in class org.tribuo.Example: The output associated with this example.
Output<T> - Interface in org.tribuo: Output is the root interface for the supported prediction types.
OUTPUT_FACTORY - Static variable in interface org.tribuo.provenance.DataSourceProvenance: The name of the provenance field for the output factory.
OUTPUT_FILE_MODIFIED_TIME - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance: The name of the output file modified time provenance field.
OUTPUT_RESOURCE_HASH - Static variable in class org.tribuo.datasource.IDXDataSource.IDXDataSourceProvenance: The name of the provenance field for the output file hash.
outputCountsIterable() - Method in interface org.tribuo.OutputInfo: An Iterable over the possible outputs and the number of times they were observed.
outputDomain() - Method in class org.tribuo.impl.DatasetDataCarrier: Get the output domain.
outputDomain() - Method in class org.tribuo.impl.ModelDataCarrier: The output domain.
outputFactory - Variable in class org.tribuo.Dataset: A factory for making OutputInfo and Output of the appropriate type.
outputFactory - Variable in class org.tribuo.sequence.SequenceDataset: A factory for making OutputInfo and Output of the appropriate type.
outputFactory() - Method in class org.tribuo.impl.DatasetDataCarrier: Get the output factory.
OutputFactory<T> - Interface in org.tribuo: An interface associated with a specific Output, which can generate the appropriate Output subclass, and OutputInfo subclass.
OutputFactoryProvenance - Interface in org.tribuo.provenance: A tag provenance for an output factory.
outputID - Variable in class org.tribuo.impl.IndexedArrayExample: Output id from the internal output map.
outputIDInfo - Variable in class org.tribuo.ImmutableDataset: Output information, and id numbers for outputs found in this dataset.
outputIDInfo - Variable in class org.tribuo.Model: The outputs this model predicts.
outputIDInfo - Variable in class org.tribuo.sequence.ImmutableSequenceDataset: A map from labels to IDs for the labels found in this dataset.
outputIDMap - Variable in class org.tribuo.sequence.SequenceModel: The output domain.
outputInfo - Variable in class org.tribuo.sequence.MutableSequenceDataset: A map from labels to IDs for the labels found in this dataset.
outputInfo(CommandInterpreter) - Method in class org.tribuo.ModelExplorer: Displays the output info.
outputInfo(CommandInterpreter) - Method in class org.tribuo.sequence.SequenceModelExplorer: Shows the output information.
OutputInfo<T> - Interface in org.tribuo: Tracks relevant properties of the appropriate Output subclass.
outputMap - Variable in class org.tribuo.MutableDataset: Information about the outputs in this dataset.

P

pairDescendingValueComparator() - Static method in class org.tribuo.util.IntDoublePair: Compare pairs by value.
pairIndexComparator() - Static method in class org.tribuo.util.IntDoublePair: Compare pairs by index.
pairValueComparator() - Static method in class org.tribuo.util.IntDoublePair: Compare pairs by value.
POINT_VERSION - Static variable in class org.tribuo.Tribuo: The patch release number.
postConfig() - Method in class org.tribuo.datasource.IDXDataSource: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.datasource.LibSVMDataSource: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.ensemble.BaggingTrainer: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.hash.HashCodeHasher: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.hash.MessageDigestHasher: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.hash.ModHashCodeHasher: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.TransformationMap: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.BinningTransformation: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.transform.transformations.SimpleTransform: Used by the OLCUT configuration system, and should not be called by external code.
predict(Iterable<Example<T>>) - Method in class org.tribuo.Model: Uses the model to predict the output for multiple examples.
predict(Iterable<SequenceExample<T>>) - Method in class org.tribuo.sequence.SequenceModel: Uses the model to predict the output for multiple examples.
predict(Dataset<T>) - Method in class org.tribuo.Model: Uses the model to predict the outputs for multiple examples contained in a data set.
predict(Dataset<T>) - Method in class org.tribuo.transform.TransformedModel
predict(Example<T>) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
predict(Example<T>) - Method in class org.tribuo.Model: Uses the model to predict the output for a single example.
predict(Example<T>) - Method in class org.tribuo.transform.TransformedModel
predict(SequenceDataset<T>) - Method in class org.tribuo.sequence.SequenceModel: Uses the model to predict the labels for multiple examples contained in a data set.
predict(SequenceExample<T>) - Method in class org.tribuo.sequence.IndependentSequenceModel
predict(SequenceExample<T>) - Method in class org.tribuo.sequence.SequenceModel: Uses the model to predict the output for a single example.
predictAndObserve(Iterable<Example<T>>) - Method in class org.tribuo.evaluation.OnlineEvaluator: Feeds the examples to the model, records the predictions and returns them.
predictAndObserve(Example<T>) - Method in class org.tribuo.evaluation.OnlineEvaluator: Feeds the example to the model, records the prediction and returns it.
Prediction<T> - Class in org.tribuo: A prediction made by a Model.
Prediction(Prediction<T>, int, Example<T>) - Constructor for class org.tribuo.Prediction: Constructs a prediction from the supplied arguments.
Prediction(T, int, Example<T>) - Constructor for class org.tribuo.Prediction: Constructs a prediction from the supplied arguments.
Prediction(T, Map<String, T>, int, Example<T>, boolean) - Constructor for class org.tribuo.Prediction: Constructs a prediction from the supplied arguments.
printFeatureMap(Map<String, List<Pair<String, Double>>>, List<String>, PrintStream) - Static method in class org.tribuo.util.HTMLOutput: Formats a feature ranking as a HTML table.
product(int[]) - Static method in class org.tribuo.util.Util: Computes the product of this array.
protobufFormat - Variable in class org.tribuo.ModelExplorer.ModelExplorerOptions: Load the model from a protobuf.
protobufFormat - Variable in class org.tribuo.sequence.SequenceModelExplorer.SequenceModelExplorerOptions: Load the model from a protobuf.
ProtoSerializable<T> - Interface in org.tribuo.protos: Interface for serializing an implementing object to the specified protobuf.
ProtoSerializableClass - Annotation Type in org.tribuo.protos: Mark a class as being ProtoSerializable and specify the class type used to serialize the "serialized_data".
ProtoSerializableField - Annotation Type in org.tribuo.protos: Annotation which denotes that a field should be part of the protobuf serialized representation.
ProtoSerializableKeysValuesField - Annotation Type in org.tribuo.protos: Annotation which denotes that the map field this is applied to is serialized as two repeated fields, one for keys and one for values.
ProtoSerializableMapField - Annotation Type in org.tribuo.protos: Annotation which denotes that a map field should be part of the protobuf serialized representation.
ProtoSerializableMapValuesField - Annotation Type in org.tribuo.protos: Annotation which denotes that the map field this is applied to is serialized as a list of values.
ProtoUtil - Class in org.tribuo.protos: Utilities for working with Tribuo protobufs.
provenance - Variable in class org.tribuo.Model: The model provenance.
provenance() - Method in class org.tribuo.impl.DatasetDataCarrier: Get the dataset provenance.
provenance() - Method in class org.tribuo.impl.ModelDataCarrier: The model provenance.
provenance() - Method in class org.tribuo.SelectedFeatureSet: The provenance of the feature set.
PROVENANCE_METADATA_FIELD - Static variable in interface org.tribuo.ONNXExportable: The name of the ONNX metadata field where the provenance information is stored in exported models.
PROVENANCE_SERIALIZER - Static variable in interface org.tribuo.protos.ProtoSerializable: Serializer used for provenance objects.
provenanceOutput - Variable in class org.tribuo.Model: The cached toString of the model provenance.
provenanceOutput - Variable in class org.tribuo.sequence.SequenceModel: The toString of the model provenance.
put(VariableInfo) - Method in class org.tribuo.MutableFeatureMap: Adds a variable info into the feature map.

R

randperm(int, Random) - Static method in class org.tribuo.util.Util: Shuffles the indices in the range [0,size).
randperm(int, SplittableRandom) - Static method in class org.tribuo.util.Util: Shuffles the indices in the range [0,size).
randpermInPlace(double[], SplittableRandom) - Static method in class org.tribuo.util.Util: Shuffles the input.
randpermInPlace(int[], Random) - Static method in class org.tribuo.util.Util: Shuffles the input.
randpermInPlace(int[], SplittableRandom) - Static method in class org.tribuo.util.Util: Shuffles the input.
RealIDInfo - Class in org.tribuo: Same as a RealInfo, but with an additional int id field.
RealIDInfo(String, int, double, double, double, double, int) - Constructor for class org.tribuo.RealIDInfo: Constructs a real id info from the supplied arguments.
RealIDInfo(RealInfo, int) - Constructor for class org.tribuo.RealIDInfo: Constructs a deep copy of the supplied real info and id.
RealInfo - Class in org.tribuo: Stores information about real valued features.
RealInfo(String) - Constructor for class org.tribuo.RealInfo: Creates an empty real info with the supplied name.
RealInfo(String, int) - Constructor for class org.tribuo.RealInfo: Creates a real info with the supplied starting conditions.
RealInfo(String, int, double, double, double, double) - Constructor for class org.tribuo.RealInfo: Creates a real info with the supplied starting conditions.
RealInfo(RealInfo) - Constructor for class org.tribuo.RealInfo: Copy constructor.
RealInfo(RealInfo, String) - Constructor for class org.tribuo.RealInfo: Copy constructor which renames the feature.
reduceByName(Merger) - Method in class org.tribuo.Example: Merges features with the same name using the supplied Merger.
reduceByName(Merger) - Method in class org.tribuo.impl.ArrayExample
reduceByName(Merger) - Method in class org.tribuo.impl.BinaryFeaturesExample
reduceByName(Merger) - Method in class org.tribuo.impl.IndexedArrayExample
reduceByName(Merger) - Method in class org.tribuo.impl.ListExample
reduceByName(Merger) - Method in class org.tribuo.sequence.SequenceExample: Reduces the features in each example using the supplied Merger.
regenerateFeatureInfo() - Method in class org.tribuo.MutableDataset: Rebuilds the feature info by inspecting each example.
regenerateOutputInfo() - Method in class org.tribuo.MutableDataset: Rebuilds the output info by inspecting each example.
removeFeatures(List<Feature>) - Method in class org.tribuo.Example: Removes all features in this list from the Example.
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.ArrayExample
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.BinaryFeaturesExample
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.IndexedArrayExample
removeFeatures(List<Feature>) - Method in class org.tribuo.impl.ListExample
removeFeatures(List<Feature>) - Method in class org.tribuo.sequence.SequenceExample: Removes the features in the supplied list from each example contained in this sequence.
rename(String) - Method in class org.tribuo.CategoricalIDInfo
rename(String) - Method in class org.tribuo.CategoricalInfo
rename(String) - Method in class org.tribuo.RealIDInfo
rename(String) - Method in class org.tribuo.RealInfo
rename(String) - Method in interface org.tribuo.VariableInfo: Rename generates a fresh VariableInfo with the new name.
reset() - Method in class org.tribuo.util.MeanVarianceAccumulator: Resets this accumulator to the starting state.
RESOURCE_HASH - Static variable in interface org.tribuo.provenance.DataSourceProvenance: The name of the provenance field for the resource hash.
rng - Static variable in class org.tribuo.Dataset: Users of this RNG should synchronize on the Dataset to prevent replicability issues.
rng - Variable in class org.tribuo.ensemble.BaggingTrainer
rng - Variable in class org.tribuo.evaluation.KFoldSplitter
ROUNDROBIN - Enum constant in enum org.tribuo.datasource.AggregateDataSource.IterationOrder: Round-robins the iterators (i.e., chooses one from each in turn).

S

sampleFromCDF(double[], Random) - Static method in class org.tribuo.util.Util: Samples an index from the supplied cdf.
sampleFromCDF(double[], SplittableRandom) - Static method in class org.tribuo.util.Util: Samples an index from the supplied cdf.
sampleInts(Random, int, int) - Static method in class org.tribuo.util.Util: Samples an array of ints from the supplied rng in [0,range).
sampleStandardDeviation(Collection<V>) - Static method in class org.tribuo.util.Util: Computes the sample standard deviation of the collection.
sampleVariance(Collection<V>) - Static method in class org.tribuo.util.Util: Computes the sample variance of the collection.
save(Path, boolean) - Method in class org.tribuo.datasource.IDXDataSource.IDXData: Writes out this IDXData to the specified path.
saveONNXModel(String, long, Path) - Method in interface org.tribuo.ONNXExportable: Exports this Model as an ONNX file.
seed - Variable in class org.tribuo.ensemble.BaggingTrainer
seed - Variable in class org.tribuo.evaluation.KFoldSplitter
select(Dataset<T>) - Method in interface org.tribuo.FeatureSelector: Selects features according to this selection algorithm from the specified dataset.
SELECT_ALL - Static variable in interface org.tribuo.FeatureSelector: Constant which denotes a full feature ranking should be generated rather than a subset.
SelectedFeatureDataset<T> - Class in org.tribuo.dataset: This class creates a pruned dataset which only contains the selected features.
SelectedFeatureDataset(Dataset<T>, SelectedFeatureSet) - Constructor for class org.tribuo.dataset.SelectedFeatureDataset: Constructs a selected feature dataset using all the features in the supplied feature set.
SelectedFeatureDataset(Dataset<T>, SelectedFeatureSet, int) - Constructor for class org.tribuo.dataset.SelectedFeatureDataset: Constructs a selected feature dataset.
SelectedFeatureDataset.SelectedFeatureDatasetProvenance - Class in org.tribuo.dataset: Provenance for SelectedFeatureDataset.
SelectedFeatureDatasetProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.dataset.SelectedFeatureDataset.SelectedFeatureDatasetProvenance: Deserialization constructor.
SelectedFeatureSet - Class in org.tribuo: A record-like class for a selected feature set.
SelectedFeatureSet(List<String>, List<Double>, boolean, FeatureSetProvenance) - Constructor for class org.tribuo.SelectedFeatureSet: Create a selected feature set.
SequenceDataset<T> - Class in org.tribuo.sequence: A class for sets of data, which are used to train and evaluate classifiers.
SequenceDataset(DataProvenance, OutputFactory<T>) - Constructor for class org.tribuo.sequence.SequenceDataset: Constructs a sequence dataset using the current Tribuo version.
SequenceDataset(DataProvenance, OutputFactory<T>, String) - Constructor for class org.tribuo.sequence.SequenceDataset: Constructs a sequence dataset.
SequenceDataSource<T> - Interface in org.tribuo.sequence: A interface for things that can be given to a SequenceDataset's constructor.
SequenceEvaluation<T> - Interface in org.tribuo.sequence: An immutable evaluation of a specific sequence model and dataset.
SequenceEvaluator<T,E> - Interface in org.tribuo.sequence: An evaluation factory which produces immutable SequenceEvaluations of a given SequenceDataset using the given SequenceModel.
SequenceExample<T> - Class in org.tribuo.sequence: A sequence of examples, used for sequence classification.
SequenceExample() - Constructor for class org.tribuo.sequence.SequenceExample: Creates an empty sequence example.
SequenceExample(List<Example<T>>) - Constructor for class org.tribuo.sequence.SequenceExample: Creates a sequence example from the list of examples.
SequenceExample(List<Example<T>>, float) - Constructor for class org.tribuo.sequence.SequenceExample: Creates a sequence example from the list of examples, setting the weight.
SequenceExample(List<T>, List<? extends List<? extends Feature>>) - Constructor for class org.tribuo.sequence.SequenceExample: Creates a sequence example from the supplied outputs and list of list of features.
SequenceExample(List<T>, List<? extends List<? extends Feature>>, boolean) - Constructor for class org.tribuo.sequence.SequenceExample: Creates a sequence example from the supplied weight, outputs and list of list of features.
SequenceExample(List<T>, List<? extends List<? extends Feature>>, float) - Constructor for class org.tribuo.sequence.SequenceExample: Creates a sequence example from the supplied weight, outputs and list of list of features.
SequenceExample(List<T>, List<? extends List<? extends Feature>>, float, boolean) - Constructor for class org.tribuo.sequence.SequenceExample: Creates a sequence example from the supplied weight, outputs and list of list of features.
SequenceExample(SequenceExample<T>) - Constructor for class org.tribuo.sequence.SequenceExample: Creates a deep copy of the supplied sequence example.
SequenceModel<T> - Class in org.tribuo.sequence: A prediction model, which is used to predict outputs for unseen instances.
SequenceModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>) - Constructor for class org.tribuo.sequence.SequenceModel: Builds a SequenceModel.
SequenceModelExplorer - Class in org.tribuo.sequence: A CLI for interacting with a SequenceModel.
SequenceModelExplorer() - Constructor for class org.tribuo.sequence.SequenceModelExplorer: Builds a sequence model explorer shell.
SequenceModelExplorer.SequenceModelExplorerOptions - Class in org.tribuo.sequence: Command line options.
SequenceModelExplorerOptions() - Constructor for class org.tribuo.sequence.SequenceModelExplorer.SequenceModelExplorerOptions
SequenceTrainer<T> - Interface in org.tribuo.sequence: An interface for things that can train sequence prediction models.
SEQUENTIAL - Enum constant in enum org.tribuo.datasource.AggregateDataSource.IterationOrder: Iterates each dataset sequentially, in the order of the sources list.
serialize() - Method in class org.tribuo.CategoricalInfo
serialize() - Method in class org.tribuo.dataset.DatasetView
serialize() - Method in class org.tribuo.dataset.MinimumCardinalityDataset
serialize() - Method in class org.tribuo.dataset.SelectedFeatureDataset
serialize() - Method in class org.tribuo.ensemble.WeightedEnsembleModel
serialize() - Method in class org.tribuo.hash.HashCodeHasher
serialize() - Method in class org.tribuo.hash.MessageDigestHasher
serialize() - Method in class org.tribuo.hash.ModHashCodeHasher
serialize() - Method in class org.tribuo.ImmutableDataset
serialize() - Method in class org.tribuo.ImmutableFeatureMap
serialize() - Method in class org.tribuo.impl.ArrayExample
serialize() - Method in class org.tribuo.impl.BinaryFeaturesExample
serialize() - Method in class org.tribuo.impl.DatasetDataCarrier: Serializes this object to a protobuf.
serialize() - Method in class org.tribuo.impl.IndexedArrayExample
serialize() - Method in class org.tribuo.impl.ListExample
serialize() - Method in class org.tribuo.impl.ModelDataCarrier: Serializes this object to a protobuf.
serialize() - Method in class org.tribuo.Model
serialize() - Method in class org.tribuo.MutableDataset
serialize() - Method in class org.tribuo.MutableFeatureMap
serialize() - Method in class org.tribuo.Prediction
serialize() - Method in interface org.tribuo.protos.ProtoSerializable: Serializes this object to a protobuf.
serialize() - Method in class org.tribuo.RealInfo
serialize() - Method in class org.tribuo.SelectedFeatureSet
serialize() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
serialize() - Method in class org.tribuo.sequence.IndependentSequenceModel
serialize() - Method in class org.tribuo.sequence.MinimumCardinalitySequenceDataset
serialize() - Method in class org.tribuo.sequence.MutableSequenceDataset
serialize() - Method in class org.tribuo.sequence.SequenceExample
serialize() - Method in class org.tribuo.sequence.SequenceModel
serialize() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformer
serialize() - Method in class org.tribuo.transform.transformations.SimpleTransform
serialize() - Method in class org.tribuo.transform.TransformedModel
serialize() - Method in class org.tribuo.transform.TransformerMap
serialize(PROTO_SERIALIZABLE) - Static method in class org.tribuo.protos.ProtoUtil: Serializes a ProtoSerializable class which has the appropriate ProtoSerializableClass annotations.
serializedDataClass() - Element in annotation type org.tribuo.protos.ProtoSerializableClass: Specifies the type of the serialized data payload.
serializeProvenance(ModelProvenance) - Method in interface org.tribuo.ONNXExportable: Serializes the model provenance to a String.
SERIALIZER - Static variable in interface org.tribuo.ONNXExportable: The provenance serializer.
serializeToFile(Path) - Method in class org.tribuo.Dataset: Serializes this dataset to a DatasetProto and writes it to the supplied path.
serializeToFile(Path) - Method in class org.tribuo.Model: Serializes this model to a ModelProto and writes it to the supplied path.
serializeToFile(Path) - Method in class org.tribuo.sequence.SequenceDataset: Serializes this sequence dataset to a SequenceDatasetProto and writes it to the supplied path.
serializeToFile(Path) - Method in class org.tribuo.sequence.SequenceModel: Serializes this model to a SequenceModelProto and writes it to the supplied path.
serializeToStream(OutputStream) - Method in class org.tribuo.Dataset: Serializes this dataset to a DatasetProto and writes it to the supplied output stream.
serializeToStream(OutputStream) - Method in class org.tribuo.Model: Serializes this model to a ModelProto and writes it to the supplied output stream.
serializeToStream(OutputStream) - Method in class org.tribuo.sequence.SequenceDataset: Serializes this sequence dataset to a SequenceDatasetProto and writes it to the supplied output stream.
serializeToStream(OutputStream) - Method in class org.tribuo.sequence.SequenceModel: Serializes this model to a SequenceModelProto and writes it to the supplied output stream.
set(Feature) - Method in class org.tribuo.Example: Overwrites the feature with the matching name.
set(Feature) - Method in class org.tribuo.impl.ArrayExample
set(Feature) - Method in class org.tribuo.impl.BinaryFeaturesExample
set(Feature) - Method in class org.tribuo.impl.ListExample
setInvocationCount(int) - Method in class org.tribuo.ensemble.BaggingTrainer
setInvocationCount(int) - Method in class org.tribuo.hash.HashingTrainer
setInvocationCount(int) - Method in interface org.tribuo.Trainer: Set the internal state of the trainer to the provided number of invocations of the train method.
setInvocationCount(int) - Method in class org.tribuo.transform.TransformTrainer
setMetadataValue(String, Object) - Method in class org.tribuo.Example: Puts the specified key, value pair into the metadata.
setName(String) - Method in class org.tribuo.Model: Sets the model name.
setName(String) - Method in class org.tribuo.sequence.SequenceModel: Sets the model name.
setSalt(String) - Method in class org.tribuo.hash.HashCodeHasher
setSalt(String) - Method in class org.tribuo.hash.HashedFeatureMap: The salt is not serialised with the Model.
setSalt(String) - Method in class org.tribuo.hash.Hasher: The salt is transient, it must be set **to the same value as it was trained with** after the Model is deserialized.
setSalt(String) - Method in class org.tribuo.hash.MessageDigestHasher
setSalt(String) - Method in class org.tribuo.hash.ModHashCodeHasher
setStoreIndices(boolean) - Method in class org.tribuo.dataset.DatasetView: Set to true to store the indices in the provenance system.
setWeight(float) - Method in class org.tribuo.Example: Sets the example's weight.
setWeight(float) - Method in class org.tribuo.sequence.SequenceExample: Sets the weight of this sequence.
setWeights(Map<T, Float>) - Method in class org.tribuo.MutableDataset: Sets the weights in each example according to their output.
SHA1 - Enum constant in enum org.tribuo.hash.HashingOptions.ModelHashingType: Uses SHA-1.
SHA256 - Enum constant in enum org.tribuo.hash.HashingOptions.ModelHashingType: Uses SHA-256.
SHORT - Enum constant in enum org.tribuo.datasource.IDXDataSource.IDXType: A 16-bit integer.
shuffle(boolean) - Method in class org.tribuo.dataset.DatasetView
shuffle(boolean) - Method in class org.tribuo.Dataset: Shuffles the indices, or stops shuffling them.
shuffle(ArrayList<T>, SplittableRandom) - Static method in class org.tribuo.util.Util: Shuffles an ArrayList like Collections.shuffle(java.util.List<?>) but using a SplittableRandom.
SimpleDataSourceProvenance - Class in org.tribuo.provenance: This class stores a String describing the data source, along with a timestamp.
SimpleDataSourceProvenance(String, OffsetDateTime, OutputFactory<T>) - Constructor for class org.tribuo.provenance.SimpleDataSourceProvenance: This constructor initialises the provenance using the supplied description, time and output factory.
SimpleDataSourceProvenance(String, OutputFactory<T>) - Constructor for class org.tribuo.provenance.SimpleDataSourceProvenance: This constructor initialises the provenance using the current time in the system timezone.
SimpleDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.SimpleDataSourceProvenance: Used for provenance deserialization.
SimpleTransform - Class in org.tribuo.transform.transformations: This is used for stateless functions such as exp, log, addition or multiplication by a constant.
SimpleTransform.Operation - Enum in org.tribuo.transform.transformations: Operations understood by this Transformation.
SimpleTransform.SimpleTransformProvenance - Class in org.tribuo.transform.transformations: Provenance for SimpleTransform.
SimpleTransformProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.transformations.SimpleTransform.SimpleTransformProvenance: Deserialization constructor.
sinceVersion() - Element in annotation type org.tribuo.protos.ProtoSerializableField: The protobuf version when this field was added.
sinceVersion() - Element in annotation type org.tribuo.protos.ProtoSerializableKeysValuesField: The protobuf version when this field was added.
sinceVersion() - Element in annotation type org.tribuo.protos.ProtoSerializableMapField: The protobuf version when this field was added.
sinceVersion() - Element in annotation type org.tribuo.protos.ProtoSerializableMapValuesField: The protobuf version when this field was added.
size - Variable in class org.tribuo.ImmutableFeatureMap: The number of features.
size - Variable in class org.tribuo.impl.ArrayExample: Number of valid features in this example.
size - Variable in class org.tribuo.impl.BinaryFeaturesExample: Number of valid features in this example.
size() - Method in class org.tribuo.dataset.DatasetView: Gets the size of the data set.
size() - Method in class org.tribuo.Dataset: Gets the size of the data set.
size() - Method in class org.tribuo.datasource.IDXDataSource: The number of examples loaded.
size() - Method in class org.tribuo.datasource.LibSVMDataSource: The number of examples.
size() - Method in class org.tribuo.datasource.ListDataSource: Number of examples.
size() - Method in class org.tribuo.Example: Return how many features are in this example.
size() - Method in class org.tribuo.FeatureMap: Returns the number of features in the domain.
size() - Method in class org.tribuo.ImmutableFeatureMap
size() - Method in class org.tribuo.impl.ArrayExample
size() - Method in class org.tribuo.impl.BinaryFeaturesExample
size() - Method in class org.tribuo.impl.ListExample
size() - Method in interface org.tribuo.OutputInfo: Returns the number of possible values this OutputInfo knows about.
size() - Method in class org.tribuo.sequence.SequenceDataset: Gets the size of the data set.
size() - Method in class org.tribuo.sequence.SequenceExample: Return how many examples are in this sequence.
size() - Method in class org.tribuo.transform.TransformerMap: Gets the size of the map.
SkeletalTrainerProvenance - Class in org.tribuo.provenance: The skeleton of a TrainerProvenance that extracts the configured parameters.
SkeletalTrainerProvenance(SkeletalConfiguredObjectProvenance.ExtractedInfo) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance: Deserialization constructor.
SkeletalTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance: Deserialization constructor.
SkeletalTrainerProvenance(SequenceTrainer<T>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance: Builds a trainer provenance extracting the standard information from the host.
SkeletalTrainerProvenance(Trainer<T>) - Constructor for class org.tribuo.provenance.SkeletalTrainerProvenance: Builds a trainer provenance extracting the standard information from the host.
SkeletalVariableInfo - Class in org.tribuo: Contains information about a feature and can be stored in the feature map in a Dataset.
SkeletalVariableInfo(String) - Constructor for class org.tribuo.SkeletalVariableInfo: Constructs a variable info with the supplied name.
SkeletalVariableInfo(String, int) - Constructor for class org.tribuo.SkeletalVariableInfo: Constructs a variable info with the supplied name and initial count.
sort() - Method in class org.tribuo.Example: Sorts the example by the string comparator.
sort() - Method in class org.tribuo.impl.ArrayExample: Sorts the feature list to maintain the lexicographic order invariant.
sort() - Method in class org.tribuo.impl.BinaryFeaturesExample: Sorts the feature list to maintain the lexicographic order invariant.
sort() - Method in class org.tribuo.impl.IndexedArrayExample
sort() - Method in class org.tribuo.impl.ListExample: Sorts the feature list to maintain the lexicographic order invariant.
sortedDifference(int[], int[]) - Static method in class org.tribuo.util.Util: Expects sorted input arrays.
sourceProvenance - Variable in class org.tribuo.Dataset: The provenance of the data source, extracted on construction.
sourceProvenance - Variable in class org.tribuo.sequence.SequenceDataset: The provenance of the data source, extracted on construction.
SparseModel<T> - Class in org.tribuo: A model which uses a subset of the features it knows about to make predictions.
SparseModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, Map<String, List<String>>) - Constructor for class org.tribuo.SparseModel: Constructs a sparse model from the supplied arguments.
SparseTrainer<T> - Interface in org.tribuo: Denotes this trainer emits a SparseModel.
split(Dataset<T>, boolean) - Method in class org.tribuo.evaluation.KFoldSplitter: Splits a dataset into k consecutive folds; for each fold, the remaining k-1 folds form the training set.
SplitDataSourceProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance: Deserialization constructor.
standardize(double[]) - Method in class org.tribuo.util.MeanVarianceAccumulator: Standardizes the input using the computed mean and variance in this accumulator.
standardize(double[], double, double) - Static method in class org.tribuo.util.Util: Standardizes the input so it has zero mean and unit variance, i.e., subtracts the mean and divides by the variance.
standardizeInPlace(double[]) - Method in class org.tribuo.util.MeanVarianceAccumulator: Standardizes the input using the computed mean and variance in this accumulator.
standardizeInPlace(double[], double, double) - Static method in class org.tribuo.util.Util: Standardizes the input so it has zero mean and unit variance, i.e., subtracts the mean and divides by the variance.
startShell() - Method in class org.tribuo.ModelExplorer: Start the command shell
startShell() - Method in class org.tribuo.sequence.SequenceModelExplorer: Start the command shell
STD_DEVS - Enum constant in enum org.tribuo.transform.transformations.BinningTransformation.BinningType: Creates bins based on the mean and then +/- multiples of standard deviations.
stdDevs(int) - Static method in class org.tribuo.transform.transformations.BinningTransformation: Returns a BinningTransformation which generates bins based on the observed standard deviation of the training data.
storeIndicesInProvenance() - Method in class org.tribuo.dataset.DatasetView: Are the indices stored in the provenance system.
sub - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Subtracts the specified constant.
sub(double) - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that subtracts the operand from each value.
sum(double[]) - Static method in class org.tribuo.util.Util: Computes the sum of the input vector.
sum(double[], int) - Static method in class org.tribuo.util.Util: Computes the sum of the input vector up to length elements.
sum(float[]) - Static method in class org.tribuo.util.Util: Computes the sum of the input vector.
sum(float[], int) - Static method in class org.tribuo.util.Util: Computes the sum of the input vector up to length elements.
sum(int[], float[]) - Static method in class org.tribuo.util.Util: Computes the sum of the specified indices in the input array.
sum(int[], int, float[]) - Static method in class org.tribuo.util.Util: Computes the sum of the specified indices in the input array.
summarize(List<? extends EvaluationMetric<T, C>>, Model<T>, List<Prediction<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize model performance on dataset across several metrics.
summarize(List<? extends EvaluationMetric<T, C>>, Model<T>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize model performance on dataset across several metrics.
summarize(List<R>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize all fields of a list of evaluations.
summarize(List<R>, ToDoubleFunction<R>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize a single field of an evaluation across several evaluations.
summarize(Evaluator<T, R>, List<? extends Model<T>>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize performance using the supplied evaluator across several models on one dataset.
summarize(Evaluator<T, R>, Model<T>, List<? extends Dataset<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize performance according to evaluator for a single model across several datasets.
summarize(EvaluationMetric<T, C>, List<? extends Model<T>>, Dataset<T>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize performance w.r.t.
summarize(EvaluationMetric<T, C>, Model<T>, List<? extends Dataset<T>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize a model's performance w.r.t.
summarizeCrossValidation(List<Pair<R, Model<T>>>) - Static method in class org.tribuo.evaluation.EvaluationAggregator: Summarize all fields of a list of evaluations produced by CrossValidation.
sumSquares - Variable in class org.tribuo.RealInfo: The sum of the squared feature values (used to compute the variance).

T

TAG_VERSION - Static variable in class org.tribuo.Tribuo: Any tag on the version number, e.g., SNAPSHOT, ALPHA, etc.
test - Variable in class org.tribuo.evaluation.KFoldSplitter.TrainTestFold: The testing fold.
threshold - Enum constant in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Min and max thresholds applied to the input.
threshold(double, double) - Static method in class org.tribuo.transform.transformations.SimpleTransform: Generate a SimpleTransform that sets values below min to min, and values above max to max.
THRESHOLD - Static variable in class org.tribuo.CategoricalInfo: The default threshold for converting a categorical info into a RealInfo.
time - Variable in class org.tribuo.provenance.ModelProvenance: The time the model was created.
TimestampedTrainerProvenance - Class in org.tribuo.provenance.impl: A TrainerProvenance with a timestamp, used when there was no trainer involved in model construction (e.g., creating an EnsembleModel from existing models).
TimestampedTrainerProvenance() - Constructor for class org.tribuo.provenance.impl.TimestampedTrainerProvenance: Creates a TimestampedTrainerProvenance, tracking the creation time and Tribuo version.
TimestampedTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.TimestampedTrainerProvenance: Used for deserializing provenances from the marshalled form.
toBoxedFloats(float[]) - Static method in class org.tribuo.util.Util: Boxes an array of floats into a list.
toDoubleArray(float[]) - Static method in class org.tribuo.util.Util: Convert an array of floats to an array of doubles.
toFloatArray(double[]) - Static method in class org.tribuo.util.Util: Convert an array of doubles to an array of floats.
toHTML() - Method in class org.tribuo.Feature: Returns the feature name formatted as a table cell.
toHTML(Pair<String, Double>) - Static method in class org.tribuo.util.HTMLOutput: Formats a pair as a HTML table entry.
toMaxLabels(List<Prediction<T>>) - Static method in class org.tribuo.sequence.SequenceModel: Extracts a list of the predicted outputs from the list of prediction objects.
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.ModelExplorer: Displays the top n features.
topFeatures(CommandInterpreter, int) - Method in class org.tribuo.sequence.SequenceModelExplorer: Shows the top n features in this model.
toPrimitiveDouble(List<Double>) - Static method in class org.tribuo.util.Util: Converts a boxed list of doubles into an array of primitive doubles.
toPrimitiveDoubleFromInteger(List<Integer>) - Static method in class org.tribuo.util.Util: Converts a boxed list of integers into an array of primitive doubles.
toPrimitiveFloat(List<Float>) - Static method in class org.tribuo.util.Util: Converts a boxed list of floats into an array of primitive floats.
toPrimitiveInt(List<Integer>) - Static method in class org.tribuo.util.Util: Converts a boxed list of integers into an array of primitive ints.
toPrimitiveLong(List<Long>) - Static method in class org.tribuo.util.Util: Converts a boxed list of longs into an array of primitive longs.
toReadableString() - Method in class org.tribuo.FeatureMap: Same as the toString, but ordered by name, and with newlines.
toReadableString() - Method in interface org.tribuo.OutputInfo: Generates a String form of this OutputInfo.
toString() - Method in class org.tribuo.CategoricalIDInfo
toString() - Method in class org.tribuo.CategoricalInfo
toString() - Method in class org.tribuo.dataset.DatasetView.DatasetViewProvenance: This toString doesn't put the indices in the string, as it's likely to be huge.
toString() - Method in class org.tribuo.dataset.DatasetView
toString() - Method in class org.tribuo.Dataset
toString() - Method in class org.tribuo.datasource.AggregateConfigurableDataSource
toString() - Method in class org.tribuo.datasource.AggregateDataSource.AggregateDataSourceProvenance
toString() - Method in class org.tribuo.datasource.AggregateDataSource
toString() - Method in class org.tribuo.datasource.IDXDataSource
toString() - Method in class org.tribuo.datasource.LibSVMDataSource
toString() - Method in class org.tribuo.datasource.ListDataSource
toString() - Method in class org.tribuo.ensemble.BaggingTrainer
toString() - Method in class org.tribuo.evaluation.DescriptiveStats
toString() - Method in class org.tribuo.evaluation.metrics.MetricID
toString() - Method in class org.tribuo.evaluation.metrics.MetricTarget
toString() - Method in class org.tribuo.evaluation.TrainTestSplitter.SplitDataSourceProvenance
toString() - Method in class org.tribuo.Feature
toString() - Method in class org.tribuo.FeatureMap
toString() - Method in class org.tribuo.hash.HashCodeHasher.HashCodeHasherProvenance
toString() - Method in class org.tribuo.hash.HashCodeHasher
toString() - Method in class org.tribuo.hash.MessageDigestHasher.MessageDigestHasherProvenance
toString() - Method in class org.tribuo.hash.MessageDigestHasher
toString() - Method in class org.tribuo.hash.ModHashCodeHasher.ModHashCodeHasherProvenance
toString() - Method in class org.tribuo.hash.ModHashCodeHasher
toString() - Method in class org.tribuo.ImmutableDataset
toString() - Method in class org.tribuo.impl.ArrayExample
toString() - Method in class org.tribuo.impl.BinaryFeaturesExample
toString() - Method in class org.tribuo.impl.DatasetDataCarrier
toString() - Method in class org.tribuo.impl.ListExample
toString() - Method in class org.tribuo.impl.ModelDataCarrier
toString() - Method in class org.tribuo.Model
toString() - Method in class org.tribuo.MutableDataset
toString() - Method in class org.tribuo.Prediction
toString() - Method in class org.tribuo.provenance.DatasetProvenance
toString() - Method in class org.tribuo.provenance.EnsembleModelProvenance
toString() - Method in class org.tribuo.provenance.EvaluationProvenance
toString() - Method in class org.tribuo.provenance.FeatureSetProvenance
toString() - Method in class org.tribuo.provenance.impl.EmptyDatasetProvenance
toString() - Method in class org.tribuo.provenance.impl.EmptyDataSourceProvenance
toString() - Method in class org.tribuo.provenance.impl.EmptyTrainerProvenance
toString() - Method in class org.tribuo.provenance.impl.TimestampedTrainerProvenance
toString() - Method in class org.tribuo.provenance.ModelProvenance
toString() - Method in class org.tribuo.provenance.SimpleDataSourceProvenance
toString() - Method in class org.tribuo.RealIDInfo
toString() - Method in class org.tribuo.RealInfo
toString() - Method in class org.tribuo.SelectedFeatureSet
toString() - Method in class org.tribuo.sequence.HashingSequenceTrainer
toString() - Method in class org.tribuo.sequence.ImmutableSequenceDataset
toString() - Method in class org.tribuo.sequence.IndependentSequenceTrainer
toString() - Method in class org.tribuo.sequence.MutableSequenceDataset
toString() - Method in class org.tribuo.sequence.SequenceDataset
toString() - Method in class org.tribuo.sequence.SequenceModel
toString() - Method in class org.tribuo.SkeletalVariableInfo
toString() - Method in class org.tribuo.transform.TransformationMap
toString() - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformer
toString() - Method in class org.tribuo.transform.transformations.BinningTransformation
toString() - Method in class org.tribuo.transform.transformations.LinearScalingTransformation
toString() - Method in class org.tribuo.transform.transformations.MeanStdDevTransformation
toString() - Method in class org.tribuo.transform.transformations.SimpleTransform
toString() - Method in class org.tribuo.transform.TransformerMap
toString() - Method in class org.tribuo.transform.TransformerMap.TransformerMapProvenance
toString() - Method in class org.tribuo.util.IntDoublePair
toString() - Method in class org.tribuo.util.MeanVarianceAccumulator
totalObservations - Variable in class org.tribuo.CategoricalInfo: The total number of observations (including zeros).
totalSize() - Method in class org.tribuo.evaluation.TrainTestSplitter: The total amount of data in train and test combined.
train - Variable in class org.tribuo.evaluation.KFoldSplitter.TrainTestFold: The training fold.
train(Dataset<T>) - Method in class org.tribuo.ensemble.BaggingTrainer
train(Dataset<T>) - Method in interface org.tribuo.SparseTrainer: Trains a sparse predictive model using the examples in the given data set.
train(Dataset<T>) - Method in interface org.tribuo.Trainer: Trains a predictive model using the examples in the given data set.
train(Dataset<T>) - Method in class org.tribuo.transform.TransformTrainer
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.ensemble.BaggingTrainer
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.hash.HashingTrainer: This clones the Dataset, hashes each of the examples and rewrites their feature ids before passing it to the inner trainer.
train(Dataset<T>, Map<String, Provenance>) - Method in interface org.tribuo.SparseTrainer: Trains a sparse predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>) - Method in interface org.tribuo.Trainer: Trains a predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.transform.TransformTrainer
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.ensemble.BaggingTrainer
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.hash.HashingTrainer
train(Dataset<T>, Map<String, Provenance>, int) - Method in interface org.tribuo.SparseTrainer: Trains a predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>, int) - Method in interface org.tribuo.Trainer: Trains a predictive model using the examples in the given data set.
train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.transform.TransformTrainer
train(SequenceDataset<T>) - Method in class org.tribuo.sequence.IndependentSequenceTrainer
train(SequenceDataset<T>) - Method in interface org.tribuo.sequence.SequenceTrainer: Trains a sequence prediction model using the examples in the given data set.
train(SequenceDataset<T>, Map<String, Provenance>) - Method in class org.tribuo.sequence.HashingSequenceTrainer: This clones the SequenceDataset, hashes each of the examples and rewrites their feature ids before passing it to the inner trainer.
train(SequenceDataset<T>, Map<String, Provenance>) - Method in class org.tribuo.sequence.IndependentSequenceTrainer
train(SequenceDataset<T>, Map<String, Provenance>) - Method in interface org.tribuo.sequence.SequenceTrainer: Trains a sequence prediction model using the examples in the given data set.
TRAIN_INVOCATION_COUNT - Static variable in interface org.tribuo.provenance.TrainerProvenance: The name of the provenance field recording the train invocation count.
Trainer<T> - Interface in org.tribuo: An interface for things that can train predictive models.
TRAINER - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the trainer provenance field.
trainerProvenance - Variable in class org.tribuo.provenance.ModelProvenance: Provenance of the trainer which created this model.
TrainerProvenance - Interface in org.tribuo.provenance: A tag interface for trainer provenances.
TrainerProvenanceImpl - Class in org.tribuo.provenance.impl: An implementation of TrainerProvenance that delegates everything to SkeletalTrainerProvenance.
TrainerProvenanceImpl(Map<String, Provenance>) - Constructor for class org.tribuo.provenance.impl.TrainerProvenanceImpl: Construct a TrainerProvenance by extracting the necessary fields from the supplied map.
TrainerProvenanceImpl(SequenceTrainer<T>) - Constructor for class org.tribuo.provenance.impl.TrainerProvenanceImpl: Construct a TrainerProvenance by reading all the configurable parameters along with the train call count.
TrainerProvenanceImpl(Trainer<T>) - Constructor for class org.tribuo.provenance.impl.TrainerProvenanceImpl: Construct a TrainerProvenance by reading all the configurable parameters along with the train call count.
TRAINING_TIME - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the training time field.
trainInvocationCounter - Variable in class org.tribuo.ensemble.BaggingTrainer
trainSingleModel(Dataset<T>, ImmutableFeatureMap, ImmutableOutputInfo<T>, int, Map<String, Provenance>, int) - Method in class org.tribuo.ensemble.BaggingTrainer: Trains a single model.
TrainTestSplitter<T> - Class in org.tribuo.evaluation: Splits data into training and testing sets.
TrainTestSplitter(DataSource<T>) - Constructor for class org.tribuo.evaluation.TrainTestSplitter: Creates a splitter that splits a dataset 70/30 train and test using a default seed.
TrainTestSplitter(DataSource<T>, double, long) - Constructor for class org.tribuo.evaluation.TrainTestSplitter: Creates a splitter that will split the given data set into a training and testing set.
TrainTestSplitter(DataSource<T>, long) - Constructor for class org.tribuo.evaluation.TrainTestSplitter: Creates a splitter that splits a dataset 70/30 train and test.
TrainTestSplitter.SplitDataSourceProvenance - Class in org.tribuo.evaluation: Provenance for a split data source.
transform(double) - Method in class org.tribuo.transform.transformations.BinningTransformation.BinningTransformer
transform(double) - Method in class org.tribuo.transform.transformations.SimpleTransform: Apply the operation to the input.
transform(double) - Method in interface org.tribuo.transform.Transformer: Applies the transformation to the supplied input value.
transform(TransformerMap) - Method in class org.tribuo.Example: Transforms this example by applying the transformations from the supplied TransformerMap.
transform(TransformerMap) - Method in class org.tribuo.impl.ArrayExample
transform(TransformerMap) - Method in class org.tribuo.impl.BinaryFeaturesExample
transform(TransformerMap) - Method in class org.tribuo.impl.ListExample
transform(TransformerMap) - Method in class org.tribuo.MutableDataset: Applies all the transformations from the TransformerMap to this dataset.
Transformation - Interface in org.tribuo.transform: An interface representing a class of transformations which can be applied to a feature.
TransformationList(List<Transformation>) - Constructor for class org.tribuo.transform.TransformationMap.TransformationList: Constructs a transformation list.
TransformationMap - Class in org.tribuo.transform: A carrier type for a set of transformations to be applied to a Dataset.
TransformationMap(List<Transformation>) - Constructor for class org.tribuo.transform.TransformationMap: Creates a TransformationMap with only global transformations.
TransformationMap(List<Transformation>, Map<String, List<Transformation>>) - Constructor for class org.tribuo.transform.TransformationMap: Creates a transformation map from the supplied global transformation list, and per feature transformations.
TransformationMap(Map<String, List<Transformation>>) - Constructor for class org.tribuo.transform.TransformationMap: Creates a TransformationMap with only per feature transformations.
TransformationMap.TransformationList - Class in org.tribuo.transform: A carrier type as OLCUT does not support nested generics.
TransformationProvenance - Interface in org.tribuo.transform: A tag interface for provenances in the transformation system.
transformDataset(Dataset<T>) - Method in class org.tribuo.transform.TransformerMap: Copies the supplied dataset and applies the transformers to each example in it.
transformDataset(Dataset<T>, boolean) - Method in class org.tribuo.transform.TransformerMap: Copies the supplied dataset and applies the transformers to each example in it.
TransformedModel<T> - Class in org.tribuo.transform: Wraps a Model with it's TransformerMap so all Examples are transformed appropriately before the model makes predictions.
Transformer - Interface in org.tribuo.transform: A fitted Transformation which can apply a transform to the input value.
TransformerMap - Class in org.tribuo.transform: A collection of Transformers which can be applied to a Dataset or Example.
TransformerMap(Map<String, List<Transformer>>, DatasetProvenance, ConfiguredObjectProvenance) - Constructor for class org.tribuo.transform.TransformerMap: Constructs a transformer map which encapsulates a set of transformers that can be applied to features.
TransformerMap.TransformerMapProvenance - Class in org.tribuo.transform: Provenance for TransformerMap.
TransformerMapProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.transform.TransformerMap.TransformerMapProvenance: Deserialization constructor.
transformExample(Example<T>) - Method in class org.tribuo.transform.TransformerMap: Copies the supplied example and applies the transformers to it.
transformExample(Example<T>, List<String>) - Method in class org.tribuo.transform.TransformerMap: Copies the supplied example and applies the transformers to it.
transformProvenances - Variable in class org.tribuo.MutableDataset: The provenances of the transformations applied to this dataset.
transformProvenances() - Method in class org.tribuo.impl.DatasetDataCarrier: Get the transform provenances.
TransformStatistics - Interface in org.tribuo.transform: An interface for the statistics that need to be collected for a specific Transformation on a single feature.
TransformTrainer<T> - Class in org.tribuo.transform: A Trainer which encapsulates another trainer plus a TransformationMap object to apply to each Dataset before training each Model.
TransformTrainer(Trainer<T>, TransformationMap) - Constructor for class org.tribuo.transform.TransformTrainer: Creates a trainer which transforms the data before training, and stores the transformers along with the trained model in a TransformedModel.
TransformTrainer(Trainer<T>, TransformationMap, boolean) - Constructor for class org.tribuo.transform.TransformTrainer: Creates a trainer which transforms the data before training, and stores the transformers along with the trained model in a TransformedModel.
TransformTrainer(Trainer<T>, TransformationMap, boolean, boolean) - Constructor for class org.tribuo.transform.TransformTrainer: Creates a trainer which transforms the data before training, and stores the transformers along with the trained model in a TransformedModel.
Tribuo - Class in org.tribuo: This class stores the current Tribuo version, along with other compile time information.
Tribuo() - Constructor for class org.tribuo.Tribuo
TRIBUO_VERSION_STRING - Static variable in class org.tribuo.provenance.ModelProvenance: The name of the Tribuo version string field.
TRIBUO_VERSION_STRING - Static variable in interface org.tribuo.provenance.TrainerProvenance: The name of the provenance field recording the Tribuo version used in training.
tribuoVersion - Variable in class org.tribuo.Dataset: The Tribuo version which originally created this dataset
tribuoVersion - Variable in class org.tribuo.sequence.SequenceDataset: The version of Tribuo which created this dataset.
tribuoVersion() - Method in class org.tribuo.impl.DatasetDataCarrier: Gets the Tribuo version string.
tribuoVersion() - Method in class org.tribuo.impl.ModelDataCarrier: Gets the Tribuo version string.

U

UBYTE - Enum constant in enum org.tribuo.datasource.IDXDataSource.IDXType: An unsigned byte.
uniformSample(SplittableRandom) - Method in class org.tribuo.CategoricalInfo
uniformSample(SplittableRandom) - Method in class org.tribuo.RealInfo
uniformSample(SplittableRandom) - Method in interface org.tribuo.VariableInfo: Sample a value uniformly from the range of this variable.
UNKNOWN_VERSION - Static variable in class org.tribuo.provenance.ModelProvenance: The value returned for models from Tribuo 4.1 and earlier which don't record the Java, OS or architecture.
utf8Charset - Static variable in class org.tribuo.hash.MessageDigestHasher: Alias for StandardCharsets.UTF_8.
Util - Class in org.tribuo.util: Ye olde util class.

V

val1 - Variable in class org.tribuo.util.MurmurHash3.LongPair: First value.
val2 - Variable in class org.tribuo.util.MurmurHash3.LongPair: Second value.
validate(Class<? extends Output<?>>) - Method in class org.tribuo.Dataset: Validates that this Dataset does in fact contain the supplied output type.
validate(Class<? extends Output<?>>) - Method in class org.tribuo.Model: Validates that this Model does in fact support the supplied output type.
validate(Class<? extends Output<?>>) - Method in class org.tribuo.sequence.SequenceDataset: Validates that this SequenceDataset does in fact contain the supplied output type.
validate(Class<? extends Output<?>>) - Method in class org.tribuo.sequence.SequenceModel: Validates that this Model does in fact support the supplied output type.
validateExample() - Method in class org.tribuo.Example: Checks the example to see if all the feature names are unique, the feature values are not NaN, and there is at least one feature.
validateExample() - Method in class org.tribuo.impl.ArrayExample
validateExample() - Method in class org.tribuo.impl.BinaryFeaturesExample
validateExample() - Method in class org.tribuo.impl.ListExample
validateExample() - Method in class org.tribuo.sequence.SequenceExample: Checks that each Example in this sequence is valid.
validateMapping(Map<T, Integer>) - Static method in interface org.tribuo.OutputFactory: Validates that the mapping can be used as an output info, i.e.
validateSalt(String) - Static method in class org.tribuo.hash.Hasher: Salt validation is currently a test to see if the string is longer than Hasher.MIN_LENGTH.
validateTransformations(FeatureMap) - Method in class org.tribuo.transform.TransformationMap: Checks that a given transformation set doesn't have conflicts when applied to the supplied featureMap.
value - Variable in enum org.tribuo.datasource.IDXDataSource.IDXType: The encoded byte value.
value - Variable in class org.tribuo.Feature: The feature value.
value - Variable in class org.tribuo.impl.IndexedArrayExample.FeatureTuple: The feature value.
value - Variable in class org.tribuo.util.IntDoublePair: The value.
valueCounts - Variable in class org.tribuo.CategoricalInfo: The occurrence counts of each value.
valueOf(String) - Static method in enum org.tribuo.datasource.AggregateDataSource.IterationOrder: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.evaluation.metrics.EvaluationMetric.Average: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.hash.HashingOptions.ModelHashingType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.transform.transformations.BinningTransformation.BinningType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Returns the enum constant of this type with the specified name.
values - Variable in class org.tribuo.CategoricalInfo: The values array.
values() - Static method in enum org.tribuo.datasource.AggregateDataSource.IterationOrder: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.datasource.IDXDataSource.IDXType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Method in class org.tribuo.evaluation.DescriptiveStats: Returns a copy of the values.
values() - Static method in enum org.tribuo.evaluation.metrics.EvaluationMetric.Average: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.hash.HashingOptions.ModelHashingType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.transform.transformations.BinningTransformation.BinningType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.transform.transformations.SimpleTransform.Operation: Returns an array containing the constants of this enum type, in the order they are declared.
valuesName() - Element in annotation type org.tribuo.protos.ProtoSerializableKeysValuesField: The name of the value field in the protobuf in Java.
valuesName() - Element in annotation type org.tribuo.protos.ProtoSerializableMapValuesField: The name of the value field in the protobuf in Java.
VariableIDInfo - Interface in org.tribuo: Adds an id number to a VariableInfo.
VariableInfo - Interface in org.tribuo: A VariableInfo subclass contains information about a feature and its observed values.
vectorNorm(double[]) - Static method in class org.tribuo.util.Util: Computes the vector two-norm.
version() - Element in annotation type org.tribuo.protos.ProtoSerializableClass: The current version of this proto serialized class.
VERSION - Static variable in class org.tribuo.Tribuo: The full Tribuo version string.
versionString - Variable in class org.tribuo.provenance.ModelProvenance: The Tribuo version string.

W

weight - Variable in class org.tribuo.Example: The weight associated with this example.
WeightedEnsembleModel<T> - Class in org.tribuo.ensemble: An ensemble model that uses weights to combine the ensemble member predictions.
WeightedEnsembleModel(String, EnsembleModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Model<T>>, EnsembleCombiner<T>) - Constructor for class org.tribuo.ensemble.WeightedEnsembleModel: Unless you are implementing a Trainer you should not use this constructor directly.
WeightedEnsembleModel(String, EnsembleModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, List<Model<T>>, EnsembleCombiner<T>, float[]) - Constructor for class org.tribuo.ensemble.WeightedEnsembleModel: Unless you are implementing a Trainer you should not use this constructor directly.
WeightedExamples - Interface in org.tribuo: Tag interface denoting that a Trainer can use example weights.
weightedMean(double[], double[]) - Static method in class org.tribuo.util.Util: Returns the weighted mean of the input.
weightedMean(double[], float[], int) - Static method in class org.tribuo.util.Util: Computes the weighted mean of the first length elements of the array.
weightedSum(double[], float[], int) - Static method in class org.tribuo.util.Util: Computes the weighted sum of the first length elements of the array.
weights - Variable in class org.tribuo.ensemble.WeightedEnsembleModel: The ensemble member combination weights.
writeLibSVMFormat(Dataset<T>, PrintStream, boolean, Function<T, Number>) - Static method in class org.tribuo.datasource.LibSVMDataSource: Writes out a dataset in LibSVM format.
writeONNXGraph(ONNXRef<?>) - Method in class org.tribuo.ensemble.WeightedEnsembleModel
writeONNXGraph(ONNXRef<?>) - Method in interface org.tribuo.ONNXExportable: Writes this Model into OnnxMl.GraphProto.Builder inside the input's ONNXContext.

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