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

Packages that use BatchLearnerContainer
gov.sandia.cognition.learning.algorithm Provides general interfaces for learning algorithms. 
gov.sandia.cognition.learning.algorithm.ensemble Provides ensmble 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
 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
 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
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
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
 class ParameterAdaptableBatchLearnerWrapper<DataType,ResultType,LearnerType extends BatchLearner<? super DataType,? extends ResultType>>
          A wrapper for adding parameter adapters to a batch learner.