Uses of Class
org.tribuo.ImmutableFeatureMap
Package
Description
Provides the core interfaces and classes for using Tribuo.
Provides an interface to LibLinear-java for anomaly detection problems.
Provides an interface to LibSVM for anomaly detection problems.
Provides an implementation of LIME (Locally Interpretable Model Explanations).
Provides an interface to LibLinear-java for classification problems.
Provides an interface to LibSVM for classification problems.
Provides infrastructure for
SequenceModel
s which
emit Label
s at each step of the sequence.Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
Provides an implementation of a classification factorization machine using Stochastic Gradient Descent.
Provides an implementation of a classification linear model using Stochastic Gradient Descent.
Provides base classes for using liblinear from Tribuo.
The base interface to LibSVM.
Provides the base classes for models trained with stochastic gradient descent.
Provides common functionality for building decision trees, irrespective
of the predicted
Output
.Provides abstract classes for interfacing with XGBoost abstracting away all the
Output
dependent parts.Provides classes for processing columnar data and generating
Example
s.Provides utility datasets which subsample or otherwise
transform the wrapped dataset.
Provides an interface for model prediction combinations,
two base classes for ensemble models, a base class for
ensemble excuses, and a Bagging implementation.
Provides the base interface and implementations of the
Model
hashing
which obscures the feature names stored in a model.Provides implementations of base classes and interfaces from
org.tribuo
.This package contains the abstract implementation of an external model
trained by something outside of Tribuo.
Provides an interface to TensorFlow, allowing the training of non-sequential models using any supported
Tribuo output type.
Provides an interface for working with TensorFlow sequence models, using Tribuo's
SequenceModel
abstraction.Provides a linear algebra system used for numerical operations in Tribuo.
Provides an implementation of a multi-label classification factorization machine model using Stochastic Gradient Descent.
Provides an implementation of a multi-label classification linear model using Stochastic Gradient Descent.
Provides an interface to liblinear for regression problems.
Provides an interface to LibSVM for regression problems.
Provides internal implementation classes for the regression trees.
Provides an implementation of factorization machines for regression using Stochastic Gradient Descent.
Provides an implementation of linear regression using Stochastic Gradient Descent.
Provides core classes for working with sequences of
Example
s.-
Uses of ImmutableFeatureMap in org.tribuo
Modifier and TypeFieldDescriptionprotected ImmutableFeatureMap
ImmutableDataset.featureIDMap
A map from feature names to IDs for the features found in this dataset.protected final ImmutableFeatureMap
Model.featureIDMap
The features this model knows about.Modifier and TypeMethodDescriptionabstract ImmutableFeatureMap
Dataset.getFeatureIDMap()
Returns or generates anImmutableFeatureMap
.ImmutableDataset.getFeatureIDMap()
Model.getFeatureIDMap()
Gets the feature domain.MutableDataset.getFeatureIDMap()
ImmutableDataset.getFeatureMap()
Modifier and TypeMethodDescriptionstatic <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.ModifierConstructorDescriptionImmutableDataset
(Iterable<Example<T>> dataSource, DataProvenance description, OutputFactory<T> outputFactory, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean dropInvalidExamples) Creates a dataset from a data source.protected
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.protected
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.liblinear
Modifier and TypeMethodDescriptionprotected LibLinearModel<Event>
LibLinearAnomalyTrainer.createModel
(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Event> outputIDInfo, List<de.bwaldvogel.liblinear.Model> models) protected com.oracle.labs.mlrg.olcut.util.Pair<de.bwaldvogel.liblinear.FeatureNode[][],
double[][]> LibLinearAnomalyTrainer.extractData
(Dataset<Event> data, ImmutableOutputInfo<Event> outputInfo, ImmutableFeatureMap featureMap) -
Uses of ImmutableFeatureMap in org.tribuo.anomaly.libsvm
Modifier and TypeMethodDescriptionprotected 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
Modifier and TypeMethodDescriptionstatic double
LIMEBase.measureDistance
(ImmutableFeatureMap fMap, long numTrainingExamples, SparseVector input, SparseVector sample) Measures the distance between an input point and a sampled point.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
Modifier and TypeMethodDescriptionprotected 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
Modifier and TypeMethodDescriptionprotected 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
ModifierConstructorDescriptionprotected
ConfidencePredictingSequenceModel
(String name, ModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Label> labelIDMap) Constructs a ConfidencePredictingSequenceModel with the supplied parameters. -
Uses of ImmutableFeatureMap in org.tribuo.classification.sgd.crf
Modifier and TypeMethodDescriptionstatic com.oracle.labs.mlrg.olcut.util.Pair<int[],
SparseVector[]> CRFModel.convert
(SequenceExample<Label> example, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Label> labelIDMap) Deprecated.static <T extends Output<T>>
SparseVector[]CRFModel.convert
(SequenceExample<T> example, ImmutableFeatureMap featureIDMap) Deprecated.As it's replaced withCRFModel.convertToVector(org.tribuo.sequence.SequenceExample<T>, org.tribuo.ImmutableFeatureMap)
which is more flexible.static com.oracle.labs.mlrg.olcut.util.Pair<int[],
SGDVector[]> CRFModel.convertToVector
(SequenceExample<Label> example, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Label> labelIDMap) Converts aSequenceExample
into an array ofSGDVector
s and labels suitable for CRF prediction.CRFModel.convertToVector
(SequenceExample<T> example, ImmutableFeatureMap featureIDMap) Converts aSequenceExample
into an array ofSGDVector
s suitable for CRF prediction. -
Uses of ImmutableFeatureMap in org.tribuo.classification.sgd.fm
Modifier and TypeMethodDescriptionprotected FMClassificationModel
FMClassificationTrainer.createModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Label> outputInfo, FMParameters parameters) -
Uses of ImmutableFeatureMap in org.tribuo.classification.sgd.linear
Modifier and TypeMethodDescriptionprotected LinearSGDModel
LinearSGDTrainer.createModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Label> outputInfo, LinearParameters parameters) -
Uses of ImmutableFeatureMap in org.tribuo.common.liblinear
Modifier and TypeMethodDescriptionprotected 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 TribuoExample
into a liblinearFeatureNode
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 andOutput
s in LibLinear's format.ModifierConstructorDescriptionprotected
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
Modifier and TypeMethodDescriptionprotected 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 andOutput
s in LibSVM's format.ModifierConstructorDescriptionprotected
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.sgd
Modifier and TypeMethodDescriptionprotected abstract V
AbstractSGDTrainer.createModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<T> outputInfo, X parameters) Creates the appropriate model subclass for this subclass of AbstractSGDTrainer.ModifierConstructorDescriptionprotected
AbstractFMModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, FMParameters parameters, boolean generatesProbabilities) Constructs a factorization machine model trained via SGD.protected
AbstractLinearSGDModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, LinearParameters parameters, boolean generatesProbabilities) Constructs a linear model trained via SGD.protected
AbstractSGDModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, FeedForwardParameters weights, boolean generatesProbabilities, boolean addBias) Constructs a linear model trained via SGD. -
Uses of ImmutableFeatureMap in org.tribuo.common.tree
ModifierConstructorDescriptionprotected
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
Modifier and TypeMethodDescriptionprotected 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>>
longXGBoostTrainer.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 suppliedArrayList
s.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
Modifier and TypeMethodDescriptionvoid
RowProcessor.expandRegexMapping
(ImmutableFeatureMap featureMap) Uses similar logic toTransformationMap.validateTransformations(org.tribuo.FeatureMap)
to check the regexes against the supplied feature map. -
Uses of ImmutableFeatureMap in org.tribuo.dataset
Modifier and TypeMethodDescriptionstatic <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.ModifierConstructorDescriptionDatasetView
(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
Modifier and TypeMethodDescriptionBaggingTrainer.trainSingleModel
(Dataset<T> examples, ImmutableFeatureMap featureIDs, ImmutableOutputInfo<T> labelIDs, int randInt, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance, int invocationCount) Trains a single model.ModifierConstructorDescriptionprotected
EnsembleModel
(String name, EnsembleModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<Model<T>> newModels) Builds an EnsembleModel from the supplied model list.WeightedEnsembleModel
(String name, EnsembleModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<Model<T>> newModels, EnsembleCombiner<T> combiner) Unless you are implementing aTrainer
you should not use this constructor directly.WeightedEnsembleModel
(String name, EnsembleModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, List<Model<T>> newModels, EnsembleCombiner<T> combiner, float[] weights) Unless you are implementing aTrainer
you should not use this constructor directly. -
Uses of ImmutableFeatureMap in org.tribuo.hash
Modifier and TypeClassDescriptionfinal class
AFeatureMap
used by theHashingTrainer
to provide feature name hashing and guarantee that theModel
does not contain feature name information, but still works with unhashed features names. -
Uses of ImmutableFeatureMap in org.tribuo.impl
ModifierConstructorDescriptionIndexedArrayExample
(Example<T> other, ImmutableFeatureMap featureMap, ImmutableOutputInfo<T> outputMap) This constructor removes unknown features. -
Uses of ImmutableFeatureMap in org.tribuo.interop
Modifier and TypeMethodDescriptionprotected static ImmutableFeatureMap
ExternalModel.createFeatureMap
(Set<String> featureNames) Creates an immutable feature map from a set of feature names.ModifierConstructorDescriptionprotected
ExternalModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean generatesProbabilities, Map<String, Integer> featureMapping) Constructs an external model from a model trained outside of Tribuo.protected
ExternalModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, int[] featureForwardMapping, int[] featureBackwardMapping, boolean generatesProbabilities) Constructs an external model from a model trained outside of Tribuo. -
Uses of ImmutableFeatureMap in org.tribuo.interop.tensorflow
Modifier and TypeMethodDescriptionDenseFeatureConverter.convert
(List<? extends Example<?>> examples, ImmutableFeatureMap featureIDMap) DenseFeatureConverter.convert
(Example<?> example, ImmutableFeatureMap featureIDMap) FeatureConverter.convert
(List<? extends Example<?>> example, ImmutableFeatureMap featureIDMap) FeatureConverter.convert
(Example<?> example, ImmutableFeatureMap featureIDMap) ImageConverter.convert
(List<? extends Example<?>> examples, ImmutableFeatureMap featureIDMap) Transform implicitly pads unseen values with zero.ImageConverter.convert
(Example<?> example, ImmutableFeatureMap featureIDMap) Transform implicitly pads unseen values with zero.ModifierConstructorDescriptionprotected
TensorFlowModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, org.tensorflow.proto.framework.GraphDef trainedGraphDef, int batchSize, String outputName, FeatureConverter featureConverter, OutputConverter<T> outputConverter) Builds a TFModel. -
Uses of ImmutableFeatureMap in org.tribuo.interop.tensorflow.sequence
Modifier and TypeMethodDescriptionSequenceFeatureConverter.encode
(List<? extends SequenceExample<?>> batch, ImmutableFeatureMap featureMap) Encodes a batch of examples as a feed dict.SequenceFeatureConverter.encode
(SequenceExample<?> example, ImmutableFeatureMap featureMap) Encodes an example as a feed dict. -
Uses of ImmutableFeatureMap in org.tribuo.math.la
Modifier and TypeMethodDescriptionstatic <T extends Output<T>>
DenseVectorDenseVector.createDenseVector
(Example<T> example, ImmutableFeatureMap featureInfo, boolean addBias) Builds aDenseVector
from anExample
.static <T extends Output<T>>
SparseVectorSparseVector.createSparseVector
(Example<T> example, ImmutableFeatureMap featureInfo, boolean addBias) Builds aSparseVector
from anExample
.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.multilabel.sgd.fm
Modifier and TypeMethodDescriptionprotected FMMultiLabelModel
FMMultiLabelTrainer.createModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<MultiLabel> outputInfo, FMParameters parameters) -
Uses of ImmutableFeatureMap in org.tribuo.multilabel.sgd.linear
Modifier and TypeMethodDescriptionprotected LinearSGDModel
LinearSGDTrainer.createModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<MultiLabel> outputInfo, LinearParameters parameters) -
Uses of ImmutableFeatureMap in org.tribuo.regression.impl
Modifier and TypeMethodDescriptionprotected abstract SkeletalIndependentRegressionSparseModel
SkeletalIndependentRegressionSparseTrainer.createModel
(Map<String, T> models, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo) Constructs the appropriate subclass ofSkeletalIndependentRegressionModel
for this trainer.protected abstract SkeletalIndependentRegressionModel
SkeletalIndependentRegressionTrainer.createModel
(Map<String, T> models, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo) Constructs the appropriate subclass ofSkeletalIndependentRegressionModel
for this trainer.ModifierConstructorDescriptionprotected
SkeletalIndependentRegressionModel
(String name, String[] dimensions, ModelProvenance modelProvenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo) models.size() must equal labelInfo.getDomain().size()protected
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
Modifier and TypeMethodDescriptionprotected 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
Modifier and TypeMethodDescriptionprotected 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
ModifierConstructorDescriptionRegressorTrainingNode
(RegressorImpurity impurity, RegressorTrainingNode.InvertedData tuple, int dimIndex, String dimName, int numExamples, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Regressor> outputInfo, AbstractTrainingNode.LeafDeterminer leafDeterminer) Constructs a tree training node for regression problems. -
Uses of ImmutableFeatureMap in org.tribuo.regression.sgd.fm
Modifier and TypeMethodDescriptionprotected FMRegressionModel
FMRegressionTrainer.createModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo, FMParameters parameters) -
Uses of ImmutableFeatureMap in org.tribuo.regression.sgd.linear
Modifier and TypeMethodDescriptionprotected LinearSGDModel
LinearSGDTrainer.createModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<Regressor> outputInfo, LinearParameters parameters) -
Uses of ImmutableFeatureMap in org.tribuo.sequence
Modifier and TypeFieldDescriptionprotected ImmutableFeatureMap
ImmutableSequenceDataset.featureIDMap
A map from feature names to IDs for the features found in this dataset.protected final ImmutableFeatureMap
SequenceModel.featureIDMap
Modifier and TypeMethodDescriptionImmutableSequenceDataset.getFeatureIDMap()
MutableSequenceDataset.getFeatureIDMap()
abstract ImmutableFeatureMap
SequenceDataset.getFeatureIDMap()
An immutable view on the feature map.SequenceModel.getFeatureIDMap()
Gets the feature domain.ImmutableSequenceDataset.getFeatureMap()
Modifier and TypeMethodDescriptionstatic <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.ModifierConstructorDescriptionImmutableSequenceDataset
(Iterable<SequenceExample<T>> dataSource, DataProvenance sourceProvenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, OutputFactory<T> outputFactory) Creates a dataset from a data source.protected
ImmutableSequenceDataset
(DataProvenance sourceProvenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo) This is dangerous, and should not be used unless you've overridden everything in ImmutableSequenceDataset.SequenceModel
(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDMap) Builds a SequenceModel.
CRFModel.convertToVector(org.tribuo.sequence.SequenceExample<T>, org.tribuo.ImmutableFeatureMap)
which is more flexible.