Uses of Interface
gov.sandia.cognition.learning.algorithm.BatchLearnerContainer

Packages that use BatchLearnerContainer

Package	Description
gov.sandia.cognition.learning.algorithm	Provides general interfaces for learning algorithms.
gov.sandia.cognition.learning.algorithm.ensemble	Provides ensemble methods.
gov.sandia.cognition.learning.function.categorization	Provides functions that output a discrete set of categories.
gov.sandia.cognition.learning.function.distance	Provides distance functions.
gov.sandia.cognition.learning.parameter	Provides utility classes for handling learning algorithm parameters.

Uses of BatchLearnerContainer in gov.sandia.cognition.learning.algorithm

Classes in gov.sandia.cognition.learning.algorithm that implement BatchLearnerContainer

Modifier and Type	Class and Description
class	AbstractBatchLearnerContainer<LearnerType extends BatchLearner<?,?>> An abstract class for objects that contain a batch learning algorithm.
class	InputOutputTransformedBatchLearner<InputType,TransformedInputType,TransformedOutputType,OutputType> An adapter class for performing supervised learning from data where both the input and output have to be transformed before they are passed to the learning algorithm.
class	SequencePredictionLearner<DataType,LearnedType> A wrapper learner that converts an unlabeled sequence of data into a sequence of prediction data using a fixed prediction horizon.

Uses of BatchLearnerContainer in gov.sandia.cognition.learning.algorithm.ensemble

Classes in gov.sandia.cognition.learning.algorithm.ensemble that implement BatchLearnerContainer

Modifier and Type	Class and Description
class	AbstractBaggingLearner<InputType,OutputType,MemberType,EnsembleType extends Evaluator<? super InputType,? extends OutputType>> Learns an ensemble by randomly sampling with replacement (duplicates allowed) some percentage of the size of the data (defaults to 100%) on each iteration to train a new ensemble member.
class	AdaBoost<InputType> The AdaBoost class implements the Adaptive Boosting (AdaBoost) algorithm formulated by Yoav Freund and Robert Shapire.
class	BaggingCategorizerLearner<InputType,CategoryType> Learns an categorization ensemble by randomly sampling with replacement (duplicates allowed) some percentage of the size of the data (defaults to 100%) on each iteration to train a new ensemble member.
class	BaggingRegressionLearner<InputType> Learns an ensemble for regression by randomly sampling with replacement (duplicates allowed) some percentage of the size of the data (defaults to 100%) on each iteration to train a new ensemble member.
class	BinaryBaggingLearner<InputType> The BinaryBaggingLearner implements the Bagging learning algorithm.
class	CategoryBalancedBaggingLearner<InputType,CategoryType> An extension of the basic bagging learner that attempts to sample bags that have equal numbers of examples from every category.
class	CategoryBalancedIVotingLearner<InputType,CategoryType> An extension of IVoting for dealing with skew problems that makes sure that there are an equal number of examples from each category in each sample that an ensemble member is trained on.
class	IVotingCategorizerLearner<InputType,CategoryType> Learns an ensemble in a method similar to bagging except that on each iteration the bag is built from two parts, each sampled from elements from disjoint sets.
class	MultiCategoryAdaBoost<InputType,CategoryType> An implementation of a multi-class version of the Adaptive Boosting (AdaBoost) algorithm, known as AdaBoost.M1.

Uses of BatchLearnerContainer in gov.sandia.cognition.learning.function.categorization

Classes in gov.sandia.cognition.learning.function.categorization that implement BatchLearnerContainer

Modifier and Type	Class and Description
static class	BinaryVersusCategorizer.Learner<InputType,CategoryType> A learner for the BinaryVersusCategorizer.
static class	EvaluatorToCategorizerAdapter.Learner<InputType,CategoryType> The EvaluatorToCategorizerAdapter.Learner class implements a simple supervised learner for a EvaluatorToCategorizerAdapter.
static class	WinnerTakeAllCategorizer.Learner<InputType,CategoryType> A learner for the adapter.

Uses of BatchLearnerContainer in gov.sandia.cognition.learning.function.distance

Classes in gov.sandia.cognition.learning.function.distance that implement BatchLearnerContainer

Modifier and Type	Class and Description
static class	DivergencesEvaluator.Learner<DataType,InputType,ValueType> A learner adapter for the DivergencesEvaluator.

Uses of BatchLearnerContainer in gov.sandia.cognition.learning.parameter

Classes in gov.sandia.cognition.learning.parameter that implement BatchLearnerContainer

Modifier and Type	Class and Description
class	ParameterAdaptableBatchLearnerWrapper<DataType,ResultType,LearnerType extends BatchLearner<? super DataType,? extends ResultType>> A wrapper for adding parameter adapters to a batch learner.