Package gov.sandia.cognition.learning.algorithm

Provides general interfaces for learning algorithms.

See:
          Description

Interface Summary
AnytimeBatchLearner<DataType,ResultType> A batch learner that is also and Anytime algorithm.
BatchAndIncrementalLearner<DataType,ResultType> Interface for an algorithm that is both a batch and incremental learner.
BatchCostMinimizationLearner<CostParametersType,ResultType> The BatchCostMinimizationLearner interface defines the functionality of a cost-minimization learning algorithm should follow.
BatchLearner<DataType,ResultType> The BatchLearner interface defines the general functionality of an object that is the implementation of a data-driven, batch machine learning algorithm.
BatchLearnerContainer<LearnerType extends BatchLearner<?,?>> An interface for an object that contains a batch learner.
IncrementalLearner<DataType,ResultType> The IncrementalLearner interface defines the general functionality of an object that is the implementation of a data-driven, incremental machine learning algorithm.
SupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> Interface for a class that is a supervised learning algorithm that can be used both batch and incremental contexts.
SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> The BatchSupervisedLearner interface is an extension of the BatchLearner interface that contains the typical generic definition conventions for a batch, supervised learning algorithm.
SupervisedIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> Interface for supervised incremental learning algorithms.
 

Class Summary
AbstractAnytimeBatchLearner<DataType,ResultType> The AbstractAnytimeBatchLearner abstract class implements a standard method for conforming to the BatchLearner and AnytimeLearner (IterativeAlgorithm and StoppableAlgorithm) interfaces.
AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> The AbstractAnytimeSupervisedBatchLearner abstract class extends the AbstractAnytimeBatchLearner to implement the SupervisedBatchLearner interface.
AbstractBatchAndIncrementalLearner<DataType,ResultType> An abstract class that has both batch learning ability as well as online learning ability by taking a Collection of input data.
AbstractBatchLearnerContainer<LearnerType extends BatchLearner<?,?>> An abstract class for objects that contain a batch learning algorithm.
AbstractSupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> An abstract implementation of the batch and incremental learning for an incremental supervised learner.
CompositeBatchLearnerPair<InputType,IntermediateType,OutputType> Composes together a pair of batch (typically unsupervised) learners.
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.
SequencePredictionLearner<DataType,LearnedType> A wrapper learner that converts an unlabeled sequence of data into a sequence of prediction data using a fixed prediction horizon.
TimeSeriesPredictionLearner<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>> A learner used to predict the future of a sequence of data by wrapping another learner and created a future-aligned data set.
 

Package gov.sandia.cognition.learning.algorithm Description

Provides general interfaces for learning algorithms.

Since:
2.0
Author:
Justin Basilico