Uses of Interface
org.tribuo.ensemble.EnsembleCombiner

Packages that use EnsembleCombiner

Package	Description
org.tribuo.classification.ensemble	Provides majority vote ensemble combiners for classification along with an implementation of multiclass Adaboost.
org.tribuo.common.nearest	Provides a K-Nearest Neighbours implementation which works across all Tribuo Output types.
org.tribuo.common.tree	Provides common functionality for building decision trees, irrespective of the predicted Output.
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.multilabel.ensemble	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.
org.tribuo.regression.ensemble	Provides EnsembleCombiner implementations for working with multi-output regression problems.

Uses of EnsembleCombiner in org.tribuo.classification.ensemble

Classes in org.tribuo.classification.ensemble that implement EnsembleCombiner

Modifier and Type	Class	Description
final class	FullyWeightedVotingCombiner	A combiner which performs a weighted or unweighted vote across the predicted labels.
final class	VotingCombiner	A combiner which performs a weighted or unweighted vote across the predicted labels.

Uses of EnsembleCombiner in org.tribuo.common.nearest

Constructors in org.tribuo.common.nearest with parameters of type EnsembleCombiner

Modifier	Constructor	Description
	KNNTrainer(int k, KNNTrainer.Distance distance, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend)	Creates a K-NN trainer using the supplied parameters.

Uses of EnsembleCombiner in org.tribuo.common.tree

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

Modifier	Constructor	Description
	ExtraTreesTrainer(DecisionTreeTrainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers)	Constructs an ExtraTreesTrainer with the default seed Trainer.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 seed Trainer.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

Fields in org.tribuo.ensemble declared as EnsembleCombiner

Modifier and Type	Field	Description
protected EnsembleCombiner<T>	BaggingTrainer.combiner
protected final EnsembleCombiner<T>	WeightedEnsembleModel.combiner

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

Modifier and Type	Method	Description
static <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.

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

Modifier	Constructor	Description
	BaggingTrainer(Trainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers)	Constructs a bagging trainer with the supplied parameters using Trainer.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 a Trainer 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 a Trainer you should not use this constructor directly.

Uses of EnsembleCombiner in org.tribuo.multilabel.ensemble

Classes in org.tribuo.multilabel.ensemble that implement EnsembleCombiner

Modifier and Type	Class	Description
final class	MultiLabelVotingCombiner	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

Classes in org.tribuo.regression.ensemble that implement EnsembleCombiner

Modifier and Type	Class	Description
class	AveragingCombiner	A combiner which performs a weighted or unweighted average of the predicted regressors independently across the output dimensions.