Uses of Class
org.tribuo.ImmutableFeatureMap

Packages that use ImmutableFeatureMap

Package	Description
org.tribuo	Provides the core interfaces and classes for using Tribuo.
org.tribuo.anomaly.libsvm	Provides an interface to LibSVM for anomaly detection problems.
org.tribuo.classification.explanations.lime	Provides an implementation of LIME (Locally Interpretable Model Explanations).
org.tribuo.classification.liblinear	Provides an interface to LibLinear-java for classification problems.
org.tribuo.classification.libsvm	Provides an interface to LibSVM for classification problems.
org.tribuo.classification.sequence	Provides infrastructure for SequenceModels which emit Labels at each step of the sequence.
org.tribuo.classification.sgd.crf	Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
org.tribuo.clustering.kmeans	Provides a multithreaded implementation of K-Means, with a configurable distance function.
org.tribuo.common.liblinear	Provides base classes for using liblinear from Tribuo.
org.tribuo.common.libsvm	The base interface to LibSVM.
org.tribuo.common.tree	Provides common functionality for building decision trees, irrespective of the predicted Output.
org.tribuo.common.xgboost	Provides abstract classes for interfacing with XGBoost abstracting away all the Output dependent parts.
org.tribuo.data.columnar	Provides classes for processing columnar data and generating Examples.
org.tribuo.dataset	Provides utility datasets which subsample or otherwise transform the wrapped dataset.
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.hash	Provides the base interface and implementations of the Model hashing which obscures the feature names stored in a model.
org.tribuo.impl	Provides implementations of base classes and interfaces from org.tribuo.
org.tribuo.interop	This package contains the abstract implementation of an external model trained by something outside of Tribuo.
org.tribuo.interop.tensorflow	Provides an interface to Tensorflow, allowing the training of non-sequential models using any supported Tribuo output type.
org.tribuo.interop.tensorflow.sequence	Provides an interface for working with Tensorflow sequence models, using Tribuo's SequenceModel abstraction.
org.tribuo.math.la	Provides a linear algebra system used for numerical operations in Tribuo.
org.tribuo.regression.impl	Provides skeletal implementations of Regressor Trainer that can wrap a single dimension trainer/model and produce one prediction per dimension independently.
org.tribuo.regression.liblinear	Provides an interface to liblinear for regression problems.
org.tribuo.regression.libsvm	Provides an interface to LibSVM for regression problems.
org.tribuo.regression.rtree.impl	Provides internal implementation classes for the regression trees.
org.tribuo.sequence	Provides core classes for working with sequences of Examples.

Uses of ImmutableFeatureMap in org.tribuo

Fields in org.tribuo declared as ImmutableFeatureMap

Modifier and Type	Field and Description
protected ImmutableFeatureMap	Model.featureIDMap The features this model knows about.
protected ImmutableFeatureMap	ImmutableDataset.featureIDMap A map from feature names to IDs for the features found in this dataset.

Methods in org.tribuo that return ImmutableFeatureMap

Modifier and Type	Method and Description
ImmutableFeatureMap	MutableDataset.getFeatureIDMap()
ImmutableFeatureMap	Model.getFeatureIDMap() Gets the feature domain.
ImmutableFeatureMap	ImmutableDataset.getFeatureIDMap()
abstract ImmutableFeatureMap	Dataset.getFeatureIDMap() Returns or generates an ImmutableFeatureMap.
ImmutableFeatureMap	ImmutableDataset.getFeatureMap()

Methods in org.tribuo with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
static <T extends Output<T>> ImmutableDataset<T>	ImmutableDataset.copyDataset(Dataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo) Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
static <T extends Output<T>> ImmutableDataset<T>	ImmutableDataset.copyDataset(Dataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, Merger merger) Creates an immutable deep copy of the supplied dataset.

Constructors in org.tribuo with parameters of type ImmutableFeatureMap

Constructor and Description
ImmutableDataset(DataProvenance description, OutputFactory<T> outputFactory, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo) This is dangerous, and should not be used unless you've overridden everything in ImmutableDataset.
ImmutableDataset(Iterable<Example<T>> dataSource, DataProvenance description, OutputFactory<T> outputFactory, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean dropInvalidExamples) Creates a dataset from a data source.
Model(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean generatesProbabilities) Constructs a new model, storing the supplied fields.
SparseModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean generatesProbabilities, Map<String,List<String>> activeFeatures) Constructs a sparse model from the supplied arguments.

Uses of ImmutableFeatureMap in org.tribuo.anomaly.libsvm

Methods in org.tribuo.anomaly.libsvm with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected LibSVMModel<Event>	LibSVMAnomalyTrainer.createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Event> outputIDInfo, List<libsvm.svm_model> models)
protected com.oracle.labs.mlrg.olcut.util.Pair<libsvm.svm_node[][],double[][]>	LibSVMAnomalyTrainer.extractData(Dataset<Event> data, ImmutableOutputInfo<Event> outputInfo, ImmutableFeatureMap featureMap)

Uses of ImmutableFeatureMap in org.tribuo.classification.explanations.lime

Methods in org.tribuo.classification.explanations.lime with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
static double	LIMEBase.measureDistance(ImmutableFeatureMap fMap, long numTrainingExamples, SparseVector input, SparseVector sample) Measures the distance between an input point and a sampled point.
static Example<Label>	LIMEBase.samplePoint(Random rng, ImmutableFeatureMap fMap, long numTrainingExamples, SparseVector input) Samples a single example from the supplied feature map and input vector.

Uses of ImmutableFeatureMap in org.tribuo.classification.liblinear

Methods in org.tribuo.classification.liblinear with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected LibLinearModel<Label>	LibLinearClassificationTrainer.createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Label> outputIDInfo, List<de.bwaldvogel.liblinear.Model> models)
protected com.oracle.labs.mlrg.olcut.util.Pair<de.bwaldvogel.liblinear.FeatureNode[][],double[][]>	LibLinearClassificationTrainer.extractData(Dataset<Label> data, ImmutableOutputInfo<Label> outputInfo, ImmutableFeatureMap featureMap)

Uses of ImmutableFeatureMap in org.tribuo.classification.libsvm

Methods in org.tribuo.classification.libsvm with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected LibSVMModel<Label>	LibSVMClassificationTrainer.createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Label> outputIDInfo, List<libsvm.svm_model> models)
protected com.oracle.labs.mlrg.olcut.util.Pair<libsvm.svm_node[][],double[][]>	LibSVMClassificationTrainer.extractData(Dataset<Label> data, ImmutableOutputInfo<Label> outputInfo, ImmutableFeatureMap featureMap)

Uses of ImmutableFeatureMap in org.tribuo.classification.sequence

Constructors in org.tribuo.classification.sequence with parameters of type ImmutableFeatureMap

Constructor and Description
ConfidencePredictingSequenceModel(String name, ModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Label> labelIDMap)

Uses of ImmutableFeatureMap in org.tribuo.classification.sgd.crf

Methods in org.tribuo.classification.sgd.crf with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
static com.oracle.labs.mlrg.olcut.util.Pair<int[],SparseVector[]>	CRFModel.convert(SequenceExample<Label> example, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Label> labelIDMap) Converts a SequenceExample into an array of SparseVectors and labels suitable for CRF prediction.
static <T extends Output<T>> SparseVector[]	CRFModel.convert(SequenceExample<T> example, ImmutableFeatureMap featureIDMap) Converts a SequenceExample into an array of SparseVectors suitable for CRF prediction.

Uses of ImmutableFeatureMap in org.tribuo.clustering.kmeans

Methods in org.tribuo.clustering.kmeans with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected static DenseVector[]	KMeansTrainer.initialiseCentroids(int centroids, Dataset<ClusterID> examples, ImmutableFeatureMap featureMap, SplittableRandom rng) Initialisation method called at the start of each train call.

Uses of ImmutableFeatureMap in org.tribuo.common.liblinear

Methods in org.tribuo.common.liblinear with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected abstract LibLinearModel<T>	LibLinearTrainer.createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<de.bwaldvogel.liblinear.Model> models) Construct the appropriate subtype of LibLinearModel for the prediction task.
static <T extends Output<T>> de.bwaldvogel.liblinear.FeatureNode[]	LibLinearTrainer.exampleToNodes(Example<T> example, ImmutableFeatureMap featureIDMap, List<de.bwaldvogel.liblinear.FeatureNode> features) Converts a Tribuo Example into a liblinear FeatureNode array, including a bias feature.
protected abstract com.oracle.labs.mlrg.olcut.util.Pair<de.bwaldvogel.liblinear.FeatureNode[][],double[][]>	LibLinearTrainer.extractData(Dataset<T> data, ImmutableOutputInfo<T> outputInfo, ImmutableFeatureMap featureMap) Extracts the features and Outputs in LibLinear's format.

Constructors in org.tribuo.common.liblinear with parameters of type ImmutableFeatureMap

Constructor and Description
LibLinearModel(String name, ModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> labelIDMap, boolean generatesProbabilities, List<de.bwaldvogel.liblinear.Model> models) Constructs a LibLinear model from the supplied arguments.

Uses of ImmutableFeatureMap in org.tribuo.common.libsvm

Methods in org.tribuo.common.libsvm with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected abstract LibSVMModel<T>	LibSVMTrainer.createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<libsvm.svm_model> models) Construct the appropriate subtype of LibSVMModel for the prediction task.
static <T extends Output<T>> libsvm.svm_node[]	LibSVMTrainer.exampleToNodes(Example<T> example, ImmutableFeatureMap featureIDMap, List<libsvm.svm_node> features) Convert the example into an array of svm_node which represents a sparse feature vector.
protected abstract com.oracle.labs.mlrg.olcut.util.Pair<libsvm.svm_node[][],double[][]>	LibSVMTrainer.extractData(Dataset<T> data, ImmutableOutputInfo<T> outputInfo, ImmutableFeatureMap featureMap) Extracts the features and Outputs in LibLinear's format.

Constructors in org.tribuo.common.libsvm with parameters of type ImmutableFeatureMap

Constructor and Description
LibSVMModel(String name, ModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean generatesProbabilities, List<libsvm.svm_model> models) Constructs a LibSVMModel from the supplied arguments.

Uses of ImmutableFeatureMap in org.tribuo.common.tree

Constructors in org.tribuo.common.tree with parameters of type ImmutableFeatureMap

Constructor and Description
TreeModel(String name, ModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean generatesProbabilities, Map<String,List<String>> activeFeatures) Constructs a trained decision tree model.

Uses of ImmutableFeatureMap in org.tribuo.common.xgboost

Methods in org.tribuo.common.xgboost with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExample(Example<T> example, ImmutableFeatureMap featureMap)
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExample(Example<T> example, ImmutableFeatureMap featureMap, Function<T,Float> responseExtractor) Converts an examples into a DMatrix.
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExamples(Iterable<Example<T>> examples, ImmutableFeatureMap featureMap)
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExamples(Iterable<Example<T>> examples, ImmutableFeatureMap featureMap, Function<T,Float> responseExtractor) Converts an iterable of examples into a DMatrix.
protected static <T extends Output<T>> long	XGBoostTrainer.convertSingleExample(Example<T> example, ImmutableFeatureMap featureMap, ArrayList<Float> dataList, ArrayList<Integer> indicesList, ArrayList<Long> headersList, long header) Writes out the features from an example into the three supplied ArrayLists.
protected XGBoostModel<T>	XGBoostTrainer.createModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<ml.dmlc.xgboost4j.java.Booster> models, XGBoostOutputConverter<T> converter)

Uses of ImmutableFeatureMap in org.tribuo.data.columnar

Methods in org.tribuo.data.columnar with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
void	RowProcessor.expandRegexMapping(ImmutableFeatureMap featureMap) Uses similar logic to TransformationMap.validateTransformations(org.tribuo.FeatureMap) to check the regexes against the supplied feature map.

Uses of ImmutableFeatureMap in org.tribuo.dataset

Methods in org.tribuo.dataset that return ImmutableFeatureMap

Modifier and Type	Method and Description
ImmutableFeatureMap	DatasetView.getFeatureMap()

Methods in org.tribuo.dataset with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
static <T extends Output<T>> DatasetView<T>	DatasetView.createBootstrapView(Dataset<T> dataset, int size, long seed, ImmutableFeatureMap featureIDs, ImmutableOutputInfo<T> outputIDs) Generates a DatasetView bootstrapped from the supplied Dataset.
static <T extends Output<T>> DatasetView<T>	DatasetView.createWeightedBootstrapView(Dataset<T> dataset, int size, long seed, float[] exampleWeights, ImmutableFeatureMap featureIDs, ImmutableOutputInfo<T> outputIDs) Generates a DatasetView bootstrapped from the supplied Dataset using the supplied example weights.

Constructors in org.tribuo.dataset with parameters of type ImmutableFeatureMap

Constructor and Description
DatasetView(Dataset<T> dataset, int[] exampleIndices, ImmutableFeatureMap featureIDs, ImmutableOutputInfo<T> labelIDs, String tag) Creates a DatasetView which includes the supplied indices from the dataset.

Uses of ImmutableFeatureMap in org.tribuo.ensemble

Methods in org.tribuo.ensemble with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected Model<T>	BaggingTrainer.trainSingleModel(Dataset<T> examples, ImmutableFeatureMap featureIDs, ImmutableOutputInfo<T> labelIDs, SplittableRandom localRNG, Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance)

Constructors in org.tribuo.ensemble with parameters of type ImmutableFeatureMap

Constructor and Description
EnsembleModel(String name, EnsembleModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<Model<T>> newModels)
WeightedEnsembleModel(String name, EnsembleModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<Model<T>> newModels, EnsembleCombiner<T> combiner)
WeightedEnsembleModel(String name, EnsembleModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<Model<T>> newModels, EnsembleCombiner<T> combiner, float[] weights)

Uses of ImmutableFeatureMap in org.tribuo.hash

Subclasses of ImmutableFeatureMap in org.tribuo.hash

Modifier and Type	Class and Description
class	HashedFeatureMap 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.

Uses of ImmutableFeatureMap in org.tribuo.impl

Constructors in org.tribuo.impl with parameters of type ImmutableFeatureMap

Constructor and Description
IndexedArrayExample(Example<T> other, ImmutableFeatureMap featureMap, ImmutableOutputInfo<T> outputMap) This constructor removes unknown features.

Uses of ImmutableFeatureMap in org.tribuo.interop

Methods in org.tribuo.interop that return ImmutableFeatureMap

Modifier and Type	Method and Description
protected static ImmutableFeatureMap	ExternalModel.createFeatureMap(Set<String> featureNames) Creates an immutable feature map from a set of feature names.

Constructors in org.tribuo.interop with parameters of type ImmutableFeatureMap

Constructor and Description
ExternalModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean generatesProbabilities, Map<String,Integer> featureMapping)
ExternalModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, int[] featureForwardMapping, int[] featureBackwardMapping, boolean generatesProbabilities)

Uses of ImmutableFeatureMap in org.tribuo.interop.tensorflow

Methods in org.tribuo.interop.tensorflow with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
org.tensorflow.Tensor<?>	ImageTransformer.transform(Example<T> example, ImmutableFeatureMap featureIDMap) Transform implicitly pads unseen values with zero.
org.tensorflow.Tensor<?>	ExampleTransformer.transform(Example<T> example, ImmutableFeatureMap featureIDMap) Converts an Example into a Tensor suitable for supplying as an input to a graph.
org.tensorflow.Tensor<?>	DenseTransformer.transform(Example<T> example, ImmutableFeatureMap featureIDMap)
org.tensorflow.Tensor<?>	ImageTransformer.transform(List<Example<T>> examples, ImmutableFeatureMap featureIDMap) Transform implicitly pads unseen values with zero.
org.tensorflow.Tensor<?>	ExampleTransformer.transform(List<Example<T>> example, ImmutableFeatureMap featureIDMap) Converts a batch of Examples into a single Tensor suitable for supplying as an input to a graph.
org.tensorflow.Tensor<?>	DenseTransformer.transform(List<Example<T>> examples, ImmutableFeatureMap featureIDMap)

Uses of ImmutableFeatureMap in org.tribuo.interop.tensorflow.sequence

Methods in org.tribuo.interop.tensorflow.sequence with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
Map<String,org.tensorflow.Tensor<?>>	SequenceExampleTransformer.encode(List<SequenceExample<T>> batch, ImmutableFeatureMap featureMap) Encodes a batch of examples as a feed dict.
Map<String,org.tensorflow.Tensor<?>>	SequenceExampleTransformer.encode(SequenceExample<T> example, ImmutableFeatureMap featureMap) Encodes an example as a feed dict.

Uses of ImmutableFeatureMap in org.tribuo.math.la

Methods in org.tribuo.math.la with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
static <T extends Output<T>> SparseVector	SparseVector.createSparseVector(Example<T> example, ImmutableFeatureMap featureInfo, boolean addBias) Builds a SparseVector from an Example.
static <T extends Output<T>> SparseVector[]	SparseVector.transpose(Dataset<T> dataset, ImmutableFeatureMap fMap) Converts a dataset of row-major examples into an array of column-major sparse vectors.

Uses of ImmutableFeatureMap in org.tribuo.regression.impl

Methods in org.tribuo.regression.impl with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected abstract SkeletalIndependentRegressionModel	SkeletalIndependentRegressionTrainer.createModel(Map<String,T> models, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo) Constructs the appropriate subclass of SkeletalIndependentRegressionModel for this trainer.
protected abstract SkeletalIndependentRegressionSparseModel	SkeletalIndependentRegressionSparseTrainer.createModel(Map<String,T> models, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo) Constructs the appropriate subclass of SkeletalIndependentRegressionModel for this trainer.

Constructors in org.tribuo.regression.impl with parameters of type ImmutableFeatureMap

Constructor and Description
SkeletalIndependentRegressionModel(String name, String[] dimensions, ModelProvenance modelProvenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo) models.size() must equal labelInfo.getDomain().size()
SkeletalIndependentRegressionSparseModel(String name, String[] dimensions, ModelProvenance modelProvenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo, Map<String,List<String>> activeFeatures) models.size() must equal labelInfo.getDomain().size()

Uses of ImmutableFeatureMap in org.tribuo.regression.liblinear

Methods in org.tribuo.regression.liblinear with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected LibLinearModel<Regressor>	LibLinearRegressionTrainer.createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Regressor> outputIDInfo, List<de.bwaldvogel.liblinear.Model> models)
protected com.oracle.labs.mlrg.olcut.util.Pair<de.bwaldvogel.liblinear.FeatureNode[][],double[][]>	LibLinearRegressionTrainer.extractData(Dataset<Regressor> data, ImmutableOutputInfo<Regressor> outputInfo, ImmutableFeatureMap featureMap)

Uses of ImmutableFeatureMap in org.tribuo.regression.libsvm

Methods in org.tribuo.regression.libsvm with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
protected LibSVMModel<Regressor>	LibSVMRegressionTrainer.createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Regressor> outputIDInfo, List<libsvm.svm_model> models)
protected com.oracle.labs.mlrg.olcut.util.Pair<libsvm.svm_node[][],double[][]>	LibSVMRegressionTrainer.extractData(Dataset<Regressor> data, ImmutableOutputInfo<Regressor> outputInfo, ImmutableFeatureMap featureMap)

Uses of ImmutableFeatureMap in org.tribuo.regression.rtree.impl

Constructors in org.tribuo.regression.rtree.impl with parameters of type ImmutableFeatureMap

Constructor and Description
RegressorTrainingNode(RegressorImpurity impurity, RegressorTrainingNode.InvertedData tuple, int dimIndex, String dimName, int numExamples, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Regressor> outputInfo)

Uses of ImmutableFeatureMap in org.tribuo.sequence

Fields in org.tribuo.sequence declared as ImmutableFeatureMap

Modifier and Type	Field and Description
protected ImmutableFeatureMap	SequenceModel.featureIDMap
protected ImmutableFeatureMap	ImmutableSequenceDataset.featureIDMap A map from feature names to IDs for the features found in this dataset.

Methods in org.tribuo.sequence that return ImmutableFeatureMap

Modifier and Type	Method and Description
ImmutableFeatureMap	SequenceModel.getFeatureIDMap() Gets the feature domain.
abstract ImmutableFeatureMap	SequenceDataset.getFeatureIDMap() An immutable view on the feature map.
ImmutableFeatureMap	MutableSequenceDataset.getFeatureIDMap()
ImmutableFeatureMap	ImmutableSequenceDataset.getFeatureIDMap()
ImmutableFeatureMap	ImmutableSequenceDataset.getFeatureMap()

Methods in org.tribuo.sequence with parameters of type ImmutableFeatureMap

Modifier and Type	Method and Description
static <T extends Output<T>> ImmutableSequenceDataset<T>	ImmutableSequenceDataset.copyDataset(SequenceDataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo) Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
static <T extends Output<T>> ImmutableSequenceDataset<T>	ImmutableSequenceDataset.copyDataset(SequenceDataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, Merger merger) Creates an immutable deep copy of the supplied dataset.

Constructors in org.tribuo.sequence with parameters of type ImmutableFeatureMap

Constructor and Description
ImmutableSequenceDataset(DataProvenance sourceProvenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo) This is dangerous, and should not be used unless you've overridden everything in ImmutableSequenceDataset.
ImmutableSequenceDataset(Iterable<SequenceExample<T>> dataSource, DataProvenance sourceProvenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, OutputFactory<T> outputFactory) Creates a dataset from a data source.
SequenceModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDMap)