Uses of Interface
org.tribuo.ensemble.EnsembleCombiner
Package
Description
Provides majority vote ensemble combiners for classification
along with an implementation of multiclass Adaboost.
Provides a K-Nearest Neighbours implementation which works across
all Tribuo
Output
types.Provides common functionality for building decision trees, irrespective
of the predicted
Output
.Provides an interface for model prediction combinations,
two base classes for ensemble models, a base class for
ensemble excuses, and a Bagging implementation.
Provides a multi-label ensemble combiner that performs a (possibly
weighted) majority vote among each label independently, along with an
implementation of classifier chain ensembles.
Provides
EnsembleCombiner
implementations
for working with multi-output regression problems.-
Uses of EnsembleCombiner in org.tribuo.classification.ensemble
Modifier and TypeClassDescriptionfinal class
A combiner which performs a weighted or unweighted vote across the predicted labels.final class
A combiner which performs a weighted or unweighted vote across the predicted labels. -
Uses of EnsembleCombiner in org.tribuo.common.nearest
ModifierConstructorDescriptionKNNTrainer
(int k, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend, NeighboursQueryFactory neighboursQueryFactory) Creates a K-NN trainer using the supplied parameters.KNNTrainer
(int k, KNNTrainer.Distance distance, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend) Deprecated.This Constructor is deprecated in version 4.3.KNNTrainer
(int k, Distance dist, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend, NeighboursQueryFactoryType nqFactoryType) Creates a K-NN trainer using the supplied parameters. -
Uses of EnsembleCombiner in org.tribuo.common.tree
ModifierConstructorDescriptionExtraTreesTrainer
(DecisionTreeTrainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers) Constructs an ExtraTreesTrainer with the default seedTrainer.DEFAULT_SEED
.ExtraTreesTrainer
(DecisionTreeTrainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers, long seed) Constructs an ExtraTreesTrainer with the supplied seed, trainer, combining function and number of members.RandomForestTrainer
(DecisionTreeTrainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers) Constructs a RandomForestTrainer with the default seedTrainer.DEFAULT_SEED
.RandomForestTrainer
(DecisionTreeTrainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers, long seed) Constructs a RandomForestTrainer with the supplied seed, trainer, combining function and number of members. -
Uses of EnsembleCombiner in org.tribuo.ensemble
Modifier and TypeFieldDescriptionprotected EnsembleCombiner<T>
BaggingTrainer.combiner
protected final EnsembleCombiner<T>
WeightedEnsembleModel.combiner
The ensemble combination function.Modifier and TypeMethodDescriptionstatic EnsembleCombiner<?>
EnsembleCombiner.deserialize
(org.tribuo.protos.core.EnsembleCombinerProto proto) Deserialization helper for EnsembleCombiner.Modifier and TypeMethodDescriptionstatic <T extends Output<T>>
WeightedEnsembleModel<T>WeightedEnsembleModel.createEnsembleFromExistingModels
(String name, List<Model<T>> models, EnsembleCombiner<T> combiner) Creates an ensemble from existing models.static <T extends Output<T>>
WeightedEnsembleModel<T>WeightedEnsembleModel.createEnsembleFromExistingModels
(String name, List<Model<T>> models, EnsembleCombiner<T> combiner, float[] weights) Creates an ensemble from existing models.ModifierConstructorDescriptionBaggingTrainer
(Trainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers) Constructs a bagging trainer with the supplied parameters usingTrainer.DEFAULT_SEED
as the RNG seed.BaggingTrainer
(Trainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers, long seed) Constructs a bagging trainer with the supplied parameters.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 EnsembleCombiner in org.tribuo.multilabel.ensemble
Modifier and TypeClassDescriptionfinal class
A combiner which performs a weighted or unweighted vote independently across the predicted labels in each multi-label. -
Uses of EnsembleCombiner in org.tribuo.regression.ensemble
Modifier and TypeClassDescriptionclass
A combiner which performs a weighted or unweighted average of the predicted regressors independently across the output dimensions.