A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

absoluteValue() - Method in class gov.sandia.cognition.math.LogNumber
Returns a new LogNumber that represents the absolute value of this LogNumber.
absoluteValue() - Method in class gov.sandia.cognition.time.DefaultDuration
 
absoluteValue() - Method in interface gov.sandia.cognition.time.Duration
Returns the absolute value of this duration.
absoluteValueEquals() - Method in class gov.sandia.cognition.math.LogNumber
Transforms this value to be its absolute value.
AbstractAnytimeAlgorithm<ResultType> - Class in gov.sandia.cognition.algorithm
A partial implementation of the common functionality of an AnytimeAlgorithm.
AbstractAnytimeAlgorithm(int) - Constructor for class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm
Creates a new instance of AbstractAnytimeAlgorithm.
AbstractAnytimeBatchLearner<DataType,ResultType> - Class in gov.sandia.cognition.learning.algorithm
The AbstractAnytimeBatchLearner abstract class implements a standard method for conforming to the BatchLearner and AnytimeLearner (IterativeAlgorithm and StoppableAlgorithm) interfaces.
AbstractAnytimeBatchLearner(int) - Constructor for class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
Creates a new instance of AbstractAnytimeBatchLearner.
AbstractAnytimeFunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>> - Class in gov.sandia.cognition.learning.algorithm.minimization
A partial implementation of a minimization algorithm that is iterative, stoppable, and approximate.
AbstractAnytimeFunctionMinimizer(InputType, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer
Creates a new instance of AbstractStandardIterativeMinimizationAlgorithm
AbstractAnytimeLineMinimizer<EvaluatorType extends Evaluator<Double,Double>> - Class in gov.sandia.cognition.learning.algorithm.minimization.line
Partial AnytimeAlgorithm implementation of a LineMinimizer.
AbstractAnytimeLineMinimizer(LineBracketInterpolator<? super EvaluatorType>) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Creates a new instance of AbstractAnytimeLineMinimizer
AbstractAnytimeLineMinimizer(LineBracketInterpolator<? super EvaluatorType>, LineBracket, Double, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Creates a new instance of AbstractAnytimeLineMinimizer
AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> - Class in gov.sandia.cognition.learning.algorithm
The AbstractAnytimeSupervisedBatchLearner abstract class extends the AbstractAnytimeBatchLearner to implement the SupervisedBatchLearner interface.
AbstractAnytimeSupervisedBatchLearner(int) - Constructor for class gov.sandia.cognition.learning.algorithm.AbstractAnytimeSupervisedBatchLearner
Creates a new instance of AbstractAnytimeSupervisedBatchLearner.
AbstractBaggingLearner<InputType,OutputType,MemberType,EnsembleType extends Evaluator<? super InputType,? extends OutputType>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
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.
AbstractBaggingLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Creates a new instance of AbstractBaggingLearner.
AbstractBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, OutputType>>, ? extends MemberType>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Creates a new instance of AbstractBaggingLearner.
AbstractBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, OutputType>>, ? extends MemberType>, int, double, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Creates a new instance of AbstractBaggingLearner.
AbstractBatchAndIncrementalLearner<DataType,ResultType> - Class in gov.sandia.cognition.learning.algorithm
An abstract class that has both batch learning ability as well as online learning ability by taking a Collection of input data.
AbstractBatchAndIncrementalLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner
Creates a new instance of AbstractBatchAndIncrementalLearner.
AbstractBatchLearnerContainer<LearnerType extends BatchLearner<?,?>> - Class in gov.sandia.cognition.learning.algorithm
An abstract class for objects that contain a batch learning algorithm.
AbstractBatchLearnerContainer() - Constructor for class gov.sandia.cognition.learning.algorithm.AbstractBatchLearnerContainer
Creates a new AbstractBatchLearnerWrapper with a null learner.
AbstractBatchLearnerContainer(LearnerType) - Constructor for class gov.sandia.cognition.learning.algorithm.AbstractBatchLearnerContainer
Creates a new AbstractBatchLearnerWrapper with the given learner.
AbstractBaumWelchAlgorithm<ObservationType,DataType> - Class in gov.sandia.cognition.learning.algorithm.hmm
Partial implementation of the Baum-Welch algorithm.
AbstractBaumWelchAlgorithm(HiddenMarkovModel<ObservationType>, BatchLearner<Collection<? extends WeightedValue<? extends ObservationType>>, ? extends ComputableDistribution<ObservationType>>, boolean) - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
Creates a new instance of AbstractBaumWelchAlgorithm
AbstractBayesianParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>,PriorType extends Distribution<ParameterType>> - Class in gov.sandia.cognition.statistics.bayesian
Partial implementation of BayesianParameter
AbstractBayesianParameter() - Constructor for class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter
Creates a new instance of AbstractBayesianParameter
AbstractBayesianParameter(ConditionalType, String, PriorType) - Constructor for class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter
Creates a new instance of AbstractBayesianParameter
AbstractBinaryCategorizer<InputType> - Class in gov.sandia.cognition.learning.function.categorization
The AbstractBinaryCategorizer implements the commonality of the BinaryCategorizer, holding the collection of possible values.
AbstractBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer
Creates a new AbstractBinaryCategorizer.
AbstractBinaryConfusionMatrix - Class in gov.sandia.cognition.learning.performance.categorization
An abstract implementation of the BinaryConfusionMatrix interface.
AbstractBinaryConfusionMatrix() - Constructor for class gov.sandia.cognition.learning.performance.categorization.AbstractBinaryConfusionMatrix
Creates a new AbstractBinaryConfusionMatrix.
AbstractBracketedRootFinder - Class in gov.sandia.cognition.learning.algorithm.root
Partial implementation of RootFinder that maintains a bracket on the root.
AbstractBracketedRootFinder() - Constructor for class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder
Creates a new instance of AbstractBracketedRootFinder
AbstractCategorizer<InputType,CategoryType> - Class in gov.sandia.cognition.learning.function.categorization
An abstract implementation of the Categorizer interface.
AbstractCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractCategorizer
Creates a new AbstractCategorizer with an empty category set.
AbstractCategorizer(Set<CategoryType>) - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractCategorizer
Creates a new AbstractCategorizer with the given category set.
AbstractCharacterBasedTokenizer - Class in gov.sandia.cognition.text.token
An abstract implementation of a tokenizer that considers each character individually.
AbstractCharacterBasedTokenizer() - Constructor for class gov.sandia.cognition.text.token.AbstractCharacterBasedTokenizer
Creates a new LetterNumberTokenizer.
AbstractCloneableSerializable - Class in gov.sandia.cognition.util
The AbstractCloneableserializable abstract class implements a default version of the clone method that calls the Object clone method, but traps the exception that can be thrown.
AbstractCloneableSerializable() - Constructor for class gov.sandia.cognition.util.AbstractCloneableSerializable
Creates a new instance of AbstractCloneableSerializable.
AbstractClosedFormSmoothUnivariateDistribution - Class in gov.sandia.cognition.statistics
Partial implementation of SmoothUnivariateDistribution
AbstractClosedFormSmoothUnivariateDistribution() - Constructor for class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution
 
AbstractClosedFormUnivariateDistribution<NumberType extends Number> - Class in gov.sandia.cognition.statistics
Partial implementation of a ClosedFormUnivariateDistribution.
AbstractClosedFormUnivariateDistribution() - Constructor for class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution
 
AbstractClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering.hierarchy
An abstract implementation of the ClusterHierarchyNode class.
AbstractClusterHierarchyNode() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.AbstractClusterHierarchyNode
Creates a new AbstractClusterHierarchyNode.
AbstractClusterHierarchyNode(ClusterType) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.AbstractClusterHierarchyNode
Creates a new AbstractClusterHierarchyNode.
AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
The AbstractClusterToClusterDivergenceFunction class is an abstract class that helps out implementations of ClusterToClusterDivergenceFunction implementations by holding a DivergenceFunction between elements of a cluster.
AbstractClusterToClusterDivergenceFunction(DivergenceFunction<? super DataType, ? super DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.AbstractClusterToClusterDivergenceFunction
Creates a new instance of AbstractClusterToClusterDivergenceFunction
AbstractCognitiveModel - Class in gov.sandia.cognition.framework
The AbstractCognitiveModel class is an abstract class that implements common functionality of classes that implement the CognitiveModel interface may wish to have.
AbstractCognitiveModel() - Constructor for class gov.sandia.cognition.framework.AbstractCognitiveModel
Creates a new instance of AbstractCognitiveModel.
AbstractCognitiveModelFactory - Class in gov.sandia.cognition.framework
The AbstractCognitiveModelFactory class defines common functionality among CognitiveModelFactory implementations.
AbstractCognitiveModelFactory() - Constructor for class gov.sandia.cognition.framework.AbstractCognitiveModelFactory
Creates a new instance of AbstractCognitiveModelFactory.
AbstractCognitiveModelFactory(Collection<CognitiveModuleFactory>) - Constructor for class gov.sandia.cognition.framework.AbstractCognitiveModelFactory
Creates a new instance of AbstractCognitiveModelFactory.
AbstractCognitiveModelLite - Class in gov.sandia.cognition.framework.lite
The AbstractCognitiveModelLite class is an abstract class that implements common functionality of classes that share general functionality with the CognitiveModelLite - i.e.
AbstractCognitiveModelLite() - Constructor for class gov.sandia.cognition.framework.lite.AbstractCognitiveModelLite
Creates a new instance of AbstractCognitiveModelLite.
AbstractCogxelConverter<DataType> - Class in gov.sandia.cognition.framework.learning.converter
Partial implementation of CogxelConverter
AbstractCogxelConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.AbstractCogxelConverter
Default constructor
AbstractCogxelConverter(SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.AbstractCogxelConverter
Creates a new instance of AbstractCogxelConverter
AbstractCogxelPairConverter<FirstType,SecondType,PairType extends Pair<FirstType,SecondType>> - Class in gov.sandia.cognition.framework.learning.converter
Partial implementation of CogxelConverters based on a Pair
AbstractCogxelPairConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
Creates a new instance of AbstractCogxelPairConverter
AbstractCogxelPairConverter(CogxelConverter<FirstType>, CogxelConverter<SecondType>) - Constructor for class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
Creates a new instance of AbstractCogxelPairConverter
AbstractCogxelPairConverter(CogxelConverter<FirstType>, CogxelConverter<SecondType>, SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
Creates a new instance of AbstractCogxelPairConverter
AbstractConcurrentCognitiveModule - Class in gov.sandia.cognition.framework.concurrent
The AbstractConcurrentCognitiveModule class is an abstract class that implements common functionality of classes that implement the ConcurrentCognitiveModule interface.
AbstractConcurrentCognitiveModule() - Constructor for class gov.sandia.cognition.framework.concurrent.AbstractConcurrentCognitiveModule
 
AbstractConfidenceStatistic - Class in gov.sandia.cognition.statistics.method
Abstract implementation of ConfidenceStatistic.
AbstractConfidenceStatistic(double) - Constructor for class gov.sandia.cognition.statistics.method.AbstractConfidenceStatistic
Creates a new instance of AbstractConfidenceStatistic
AbstractConfidenceWeightedBinaryCategorizer - Class in gov.sandia.cognition.learning.function.categorization
Unit tests for class AbstractConfidenceWeightedBinaryCategorizer.
AbstractConfidenceWeightedBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer
Creates a new, uninitialized AbstractConfidenceWeightedBinaryCategorizer.
AbstractConfidenceWeightedBinaryCategorizer(Vector) - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer
Creates a new AbstractConfidenceWeightedBinaryCategorizer with the given mean vector.
AbstractConfusionMatrix<CategoryType> - Class in gov.sandia.cognition.learning.performance.categorization
An abstract implementation of the ConfusionMatrix interface.
AbstractConfusionMatrix() - Constructor for class gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix
Creates a new AbstractConfusionMatrix.
AbstractConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> - Class in gov.sandia.cognition.statistics.bayesian.conjugate
Partial implementation of ConjugatePriorBayesianEstimator that contains a initial belief (prior) distribution function.
AbstractConjugatePriorBayesianEstimator(BayesianParameter<ParameterType, ConditionalType, BeliefType>) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator
Creates a new instance of AbstractConjugatePriorBayesianEstimator
AbstractCostFunction<EvaluatedType,CostParametersType> - Class in gov.sandia.cognition.learning.function.cost
Partial implementation of CostFunction.
AbstractCostFunction() - Constructor for class gov.sandia.cognition.learning.function.cost.AbstractCostFunction
Creates a new instance of AbstractCostFunction
AbstractCostFunction(CostParametersType) - Constructor for class gov.sandia.cognition.learning.function.cost.AbstractCostFunction
Creates a new instance of AbstractCostFunction
AbstractDataConverter<InputType,OutputType> - Class in gov.sandia.cognition.data.convert
Abstract implementation of DataConverter interface.
AbstractDataConverter() - Constructor for class gov.sandia.cognition.data.convert.AbstractDataConverter
Creates a new AbstractDataConverter.
AbstractDataDistribution<KeyType> - Class in gov.sandia.cognition.statistics
An abstract implementation of the DataDistribution interface.
AbstractDataDistribution(Map<KeyType, MutableDouble>) - Constructor for class gov.sandia.cognition.statistics.AbstractDataDistribution
Creates a new AbstractDataDistribution.
AbstractDecisionTreeLearner<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.tree
The AbstractDecisionTreeLearner implements common functionality for learning algorithms that learn a decision tree.
AbstractDecisionTreeLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner
Creates a new instance of AbstractDecisionTreeLearner
AbstractDecisionTreeLearner(DeciderLearner<? super InputType, OutputType, ?, ?>) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner
Creates a new instance of AbstractDecisionTreeLearner.
AbstractDecisionTreeNode<InputType,OutputType,InteriorType> - Class in gov.sandia.cognition.learning.algorithm.tree
The AbstractDecisionTreeNode class implements common functionality for a decision tree node.
AbstractDecisionTreeNode() - Constructor for class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
Creates a new instance of AbstractDecisionTreeNode
AbstractDecisionTreeNode(DecisionTreeNode<InputType, OutputType>, Categorizer<? super InputType, ? extends InteriorType>, Object) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
Creates a new instance of CategorizationTreeNode.
AbstractDifferentiableUnivariateScalarFunction - Class in gov.sandia.cognition.math
Partial implementation of DifferentiableUnivariateScalarFunction that implements the differentiate(Double) method with a callback to the differentiate(double) method, so that a concrete class only to implement the differentiate(double) method
AbstractDifferentiableUnivariateScalarFunction() - Constructor for class gov.sandia.cognition.math.AbstractDifferentiableUnivariateScalarFunction
Creates a new instance of AbstractDifferentiableUnivariateScalarFunction
AbstractDiscriminantBinaryCategorizer<InputType> - Class in gov.sandia.cognition.learning.function.categorization
An abstract implementation of the DiscriminantBinaryCategorizer interface.
AbstractDiscriminantBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantBinaryCategorizer
Creates a new AbstractDiscriminantBinaryCategorizer.
AbstractDiscriminantCategorizer<InputType,CategoryType,DiscriminantType extends Comparable<? super DiscriminantType>> - Class in gov.sandia.cognition.learning.function.categorization
An abstract implementation of the DiscriminantCategorizer interface.
AbstractDiscriminantCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantCategorizer
Creates a new AbstractDiscriminantCategorizer with an empty set of categories.
AbstractDiscriminantCategorizer(Set<CategoryType>) - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantCategorizer
Creates a new AbstractCategorizer with the given category set.
AbstractDistribution<DataType> - Class in gov.sandia.cognition.statistics
Partial implementation of Distribution.
AbstractDistribution() - Constructor for class gov.sandia.cognition.statistics.AbstractDistribution
 
AbstractDocument - Class in gov.sandia.cognition.text.document
An abstract implementation of the Document interface.
AbstractDocument() - Constructor for class gov.sandia.cognition.text.document.AbstractDocument
Creates a new AbstractDocument.
AbstractDocumentExtractor - Class in gov.sandia.cognition.text.document.extractor
An abstract implementation of the DocumentExtractor interface.
AbstractDocumentExtractor() - Constructor for class gov.sandia.cognition.text.document.extractor.AbstractDocumentExtractor
Creates a new AbstractDocumentExtractor.
AbstractEigenDecomposition - Class in gov.sandia.cognition.math.matrix.decomposition
Abstract partial implementation of the EigenDecomposition interface
AbstractEigenDecomposition(ComplexNumber[], Matrix, Matrix) - Constructor for class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
Stores the given eigenvalues and eigenvectors internally, the eigenvalues and eigenvectors will not be sorted.
AbstractEigenDecomposition(ComplexNumber[], Matrix, Matrix, boolean) - Constructor for class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
Creates a new eigendecomposition using the given eigenvalues and eigenvectors...
AbstractEntropyBasedGlobalTermWeighter - Class in gov.sandia.cognition.text.term.vector.weighter.global
An abstract implementation of a global term weighting scheme that keeps track of the sum of the entropy term (f_ij * log(f_ij)) over all documents.
AbstractEntropyBasedGlobalTermWeighter() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.AbstractEntropyBasedGlobalTermWeighter
Creates a new AbstractEntropyBasedGlobalTermWeighter.
AbstractEntropyBasedGlobalTermWeighter(VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.AbstractEntropyBasedGlobalTermWeighter
Creates a new AbstractEntropyBasedGlobalTermWeighter.
AbstractEuclideanRing<RingType extends EuclideanRing<RingType>> - Class in gov.sandia.cognition.math
An abstract implementation of the EuclideanRing interface.
AbstractEuclideanRing() - Constructor for class gov.sandia.cognition.math.AbstractEuclideanRing
Creates a new AbstractEuclideanRing.
AbstractField<FieldType extends Field<FieldType>> - Class in gov.sandia.cognition.math
An abstract implementation of the Field interface.
AbstractField() - Constructor for class gov.sandia.cognition.math.AbstractField
Creates a new AbstractField.
AbstractField - Class in gov.sandia.cognition.text.document
An abstract implementation of the Field interface.
AbstractField() - Constructor for class gov.sandia.cognition.text.document.AbstractField
Creates a new AbstractField.
AbstractField(String) - Constructor for class gov.sandia.cognition.text.document.AbstractField
Creates a new AbstractField
AbstractFileSerializationHandler<SerializedType> - Class in gov.sandia.cognition.io.serialization
An abstract implementation of FileSerializationHandler.
AbstractFileSerializationHandler() - Constructor for class gov.sandia.cognition.io.serialization.AbstractFileSerializationHandler
Creates a new AbstractFileSerializationHandler.
AbstractFrequencyBasedGlobalTermWeighter - Class in gov.sandia.cognition.text.term.vector.weighter.global
An abstract GlobalTermWeighter that keeps track of term frequencies in documents.
AbstractFrequencyBasedGlobalTermWeighter() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
Creates a new AbstractCountingBasedGlobalTermWeighter.
AbstractFrequencyBasedGlobalTermWeighter(VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
Creates a new AbstractCountingBasedGlobalTermWeighter.
AbstractGlobalTermWeighter - Class in gov.sandia.cognition.text.term.vector.weighter.global
An abstract implementation of the GlobalTermWeighter interface.
AbstractGlobalTermWeighter() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.AbstractGlobalTermWeighter
Creates a new AbstractGlobalTermWeighter.
AbstractGlobalTermWeighter(VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.AbstractGlobalTermWeighter
Creates a new AbstractGlobalTermWeighter.
AbstractIncrementalEstimator<DataType,DistributionType extends Distribution<? extends DataType>,SufficientStatisticsType extends SufficientStatistic<DataType,DistributionType>> - Class in gov.sandia.cognition.statistics
Partial implementation of IncrementalEstimator.
AbstractIncrementalEstimator() - Constructor for class gov.sandia.cognition.statistics.AbstractIncrementalEstimator
Creates a new instance of AbstractIncrementalEstimator
AbstractInputOutputPair<InputType,OutputType> - Class in gov.sandia.cognition.learning.data
An abstract implementation of the InputOutputPair interface.
AbstractInputOutputPair() - Constructor for class gov.sandia.cognition.learning.data.AbstractInputOutputPair
Creates a new AbstractInputOutputPair.
AbstractIterativeAlgorithm - Class in gov.sandia.cognition.algorithm
The AbstractIterativeAlgorithm class implements a simple part of the IterativeAlgorithm interface that manages the listeners for the algorithm.
AbstractIterativeAlgorithm() - Constructor for class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
Creates a new instance of AbstractIterativeAlgorithm.
AbstractIterativeAlgorithm(int) - Constructor for class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
Creates a new instance of AbstractIterativeAlgorithm.
AbstractIterativeAlgorithmListener - Class in gov.sandia.cognition.algorithm.event
An abstract implementation of the IterativeAlgorithmListener interface that provides default implementations of the event methods that do nothing.
AbstractIterativeAlgorithmListener() - Constructor for class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener
Creates a new AbstractIterativeAlgorithmListener.
AbstractKalmanFilter - Class in gov.sandia.cognition.statistics.bayesian
Contains fields useful to both Kalman filters and extended Kalman filters.
AbstractKalmanFilter(Vector, Matrix, Matrix) - Constructor for class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
Creates a new instance of AbstractKalmanFilter
AbstractKernelizableBinaryCategorizerOnlineLearner - Class in gov.sandia.cognition.learning.algorithm.perceptron
An abstract implementation of the KernelizableBinaryCategorizerOnlineLearner interface.
AbstractKernelizableBinaryCategorizerOnlineLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AbstractKernelizableBinaryCategorizerOnlineLearner
Creates a new AbstractKernelizableBinaryCategorizerOnlineLearner.
AbstractKernelizableBinaryCategorizerOnlineLearner(VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AbstractKernelizableBinaryCategorizerOnlineLearner
Creates a new AbstractKernelizableBinaryCategorizerOnlineLearner with the given vector factory.
AbstractKNearestNeighbor<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.nearest
Partial implementation of KNearestNeighbor.
AbstractKNearestNeighbor(int, DivergenceFunction<? super InputType, ? super InputType>, Summarizer<? super OutputType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor
Creates a new instance of KNearestNeighbor
AbstractLearningExperiment - Class in gov.sandia.cognition.learning.experiment
The AbstractLearningExperiment class implements the general functionality of the LearningExperiment interface, which is mainly the handling of listeners and firing of events.
AbstractLearningExperiment() - Constructor for class gov.sandia.cognition.learning.experiment.AbstractLearningExperiment
Creates a new instance of AbstractLearningExperiment.
AbstractLinearCombinationOnlineLearner - Class in gov.sandia.cognition.learning.algorithm.perceptron
An abstract class for online learning of linear binary categorizers that take the form of a weighted sum of inputs.
AbstractLinearCombinationOnlineLearner(boolean) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Creates a new AbstractLinearCombinationOnlineLearner with default parameters.
AbstractLinearCombinationOnlineLearner(boolean, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Creates a new AbstractLinearCombinationOnlineLearner with the given parameters.
AbstractLineBracketInterpolator<EvaluatorType extends Evaluator<Double,Double>> - Class in gov.sandia.cognition.learning.algorithm.minimization.line.interpolator
Partial implementation of LinearBracketInterpolator
AbstractLineBracketInterpolator() - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolator
Default constructor
AbstractLineBracketInterpolator(double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolator
Creates a new instance of AbstractLineBracketInterpolator
AbstractLineBracketInterpolatorPolynomial<EvaluatorType extends Evaluator<Double,Double>> - Class in gov.sandia.cognition.learning.algorithm.minimization.line.interpolator
Partial implementation of a LineBracketInterpolator based on a closed-form polynomial function.
AbstractLineBracketInterpolatorPolynomial(double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolatorPolynomial
Creates a new instance of AbstractLineBracketInterpolatorPolynomial
AbstractLocalTermWeighter - Class in gov.sandia.cognition.text.term.vector.weighter.local
Abstract implementation of the LocalTermWeighter interface.
AbstractLocalTermWeighter() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.local.AbstractLocalTermWeighter
Creates a new AbstractLocalTermWeighter.
AbstractLocalTermWeighter(VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.text.term.vector.weighter.local.AbstractLocalTermWeighter
Creates a new AbstractLocalTermWeighter.
AbstractMarkovChainMonteCarlo<ObservationType,ParameterType> - Class in gov.sandia.cognition.statistics.bayesian
Partial abstract implementation of MarkovChainMonteCarlo.
AbstractMarkovChainMonteCarlo() - Constructor for class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
Creates a new instance of AbstractMarkovChainMonteCarlo
AbstractMatrix - Class in gov.sandia.cognition.math.matrix
Abstract implementation of some low-hanging functions in the Matrix interface.
AbstractMatrix() - Constructor for class gov.sandia.cognition.math.matrix.AbstractMatrix
Creates a new instance of AbstractMatrix.
AbstractMinDistanceFixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.initializer
Implements an abstract FixedClusterInitializer that works by using the minimum distance from a point to the cluster.
AbstractMinDistanceFixedClusterInitializer() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
Creates a new, empty instance of AbstractMinDistanceFixedClusterInitializer.
AbstractMinDistanceFixedClusterInitializer(DivergenceFunction<? super DataType, ? super DataType>, ClusterCreator<ClusterType, DataType>, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
Creates a new instance of AbstractMinDistanceFixedClusterInitializer.
AbstractMinimizerBasedParameterCostMinimizer<ResultType extends VectorizableVectorFunction,EvaluatorType extends Evaluator<? super Vector,? extends Double>> - Class in gov.sandia.cognition.learning.algorithm.regression
Partial implementation of ParameterCostMinimizer, based on the algorithms from the minimization package.
AbstractMinimizerBasedParameterCostMinimizer(FunctionMinimizer<Vector, Double, ? super EvaluatorType>) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
Creates a new instance of AbstractMinimizerBasedParameterCostMinimizer
AbstractMinimizerBasedParameterCostMinimizer(FunctionMinimizer<Vector, Double, ? super EvaluatorType>, SupervisedCostFunction<Vector, Vector>) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
Creates a new instance of AbstractMinimizerBasedParameterCostMinimizer
AbstractMTJMatrix - Class in gov.sandia.cognition.math.matrix.mtj
Relies on internal MTJ matrix to do some of the heavy lifting, without assuming that the underlying matrix is Dense or Sparse
AbstractMTJMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
Creates a new instance of AbstractMTJMatrix
AbstractMTJVector - Class in gov.sandia.cognition.math.matrix.mtj
Implementation of the Vector interface that relies on MTJ Vectors, but does not specify sparse or dense storage.
AbstractMTJVector(Vector) - Constructor for class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
Creates a new instance of AbstractMTJVector
AbstractMultipleHypothesisComparison<TreatmentData,StatisticType extends MultipleHypothesisComparison.Statistic> - Class in gov.sandia.cognition.statistics.method
Partial implementation of MultipleHypothesisComparison
AbstractMultipleHypothesisComparison() - Constructor for class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison
Default constructor
AbstractMultipleHypothesisComparison.Statistic - Class in gov.sandia.cognition.statistics.method
Partial implementation of MultipleHypothesisComparison.Statistic
AbstractMultipleHypothesisComparison.Statistic() - Constructor for class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic
Default constructor
AbstractMultiTextualConverter<InputType,OutputType extends Textual> - Class in gov.sandia.cognition.text.convert
An abstract implementation of the MultiTextualConverter interface.
AbstractMultiTextualConverter() - Constructor for class gov.sandia.cognition.text.convert.AbstractMultiTextualConverter
Creates a new AbstractMultiTextualConverter.
AbstractMutableDoubleMap<KeyType> - Class in gov.sandia.cognition.collection
A partial implementation of a ScalarMap with a MutableDouble value
AbstractMutableDoubleMap(Map<KeyType, MutableDouble>) - Constructor for class gov.sandia.cognition.collection.AbstractMutableDoubleMap
Creates a new instance of AbstractMutableDoubleMap
AbstractMutableDoubleMap.SimpleEntry<KeyType> - Class in gov.sandia.cognition.collection
Entry for the AbstractScalarMap
AbstractMutableDoubleMap.SimpleEntry(KeyType, MutableDouble) - Constructor for class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntry
Creates a new instance of SimpleEntry
AbstractMutableDoubleMap.SimpleEntrySet<KeyType> - Class in gov.sandia.cognition.collection
Simple Entry Set for DefaultInfiniteVector
AbstractMutableDoubleMap.SimpleEntrySet(Map<KeyType, MutableDouble>) - Constructor for class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntrySet
Creates a new instance of SimpleEntrySet
AbstractMutableDoubleMap.SimpleIterator<KeyType> - Class in gov.sandia.cognition.collection
Simple iterator for DefaultInfiniteVector
AbstractMutableDoubleMap.SimpleIterator(Iterator<? extends Map.Entry<KeyType, MutableDouble>>) - Constructor for class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleIterator
Default constructor
AbstractNamed - Class in gov.sandia.cognition.util
The AbstractNamed class implements the Named interface in a standard way by having a name field inside the object.
AbstractNamed() - Constructor for class gov.sandia.cognition.util.AbstractNamed
Creates a new instance of AbstractNamed.
AbstractNamed(String) - Constructor for class gov.sandia.cognition.util.AbstractNamed
Creates a new instance of AbstractNamed with the given name.
AbstractNearestNeighbor<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.nearest
Partial implementation of KNearestNeighbor.
AbstractNearestNeighbor() - Constructor for class gov.sandia.cognition.learning.algorithm.nearest.AbstractNearestNeighbor
Creates a new instance of AbstractNearestNeighbor
AbstractNearestNeighbor(DivergenceFunction<? super InputType, ? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.nearest.AbstractNearestNeighbor
Creates a new instance of AbstractNearestNeighbor
AbstractOccurrenceInText<DataType> - Class in gov.sandia.cognition.text
An abstract implementation of the OccurrenceInText interface.
AbstractOccurrenceInText() - Constructor for class gov.sandia.cognition.text.AbstractOccurrenceInText
Creates a new AbstractOccurrenceInText.
AbstractOccurrenceInText(int, int) - Constructor for class gov.sandia.cognition.text.AbstractOccurrenceInText
Creates a new AbstractOccurrenceInText.
AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
An abstract implementation of the BudgetedKernelBinaryCategorizerLearner for online learners.
AbstractOnlineBudgetedKernelBinaryCategorizerLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineBudgetedKernelBinaryCategorizerLearner
Creates a new AbstractOnlineBudgetedKernelBinaryCategorizerLearner with a null kernel and default budget.
AbstractOnlineBudgetedKernelBinaryCategorizerLearner(Kernel<? super InputType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineBudgetedKernelBinaryCategorizerLearner
Creates a new AbstractOnlineBudgetedKernelBinaryCategorizerLearner with the given parameters.
AbstractOnlineKernelBinaryCategorizerLearner<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
An abstract class for an online kernel binary categorizer learner.
AbstractOnlineKernelBinaryCategorizerLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner
Creates a new AbstractOnlineKernelBinaryCategorizerLearner with a null kernel.
AbstractOnlineKernelBinaryCategorizerLearner(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner
Creates a new AbstractOnlineKernelBinaryCategorizerLearner with the given kernel.
AbstractOnlineLinearBinaryCategorizerLearner - Class in gov.sandia.cognition.learning.algorithm.perceptron
An abstract class for online (incremental) learning algorithms that produce an LinearBinaryCategorizer.
AbstractOnlineLinearBinaryCategorizerLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AbstractOnlineLinearBinaryCategorizerLearner
Creates a new AbstractOnlineLinearBinaryCategorizerLearner with the default vector factory.
AbstractOnlineLinearBinaryCategorizerLearner(VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AbstractOnlineLinearBinaryCategorizerLearner
Creates a new AbstractOnlineLinearBinaryCategorizerLearner with the given vector factory.
AbstractPairwiseMultipleHypothesisComparison<StatisticType extends AbstractPairwiseMultipleHypothesisComparison.Statistic> - Class in gov.sandia.cognition.statistics.method
A multiple-hypothesis comparison algorithm based on making multiple pair-wise null-hypothesis comparisons.
AbstractPairwiseMultipleHypothesisComparison(NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison
Creates a new instance of BonferroniCorrection
AbstractPairwiseMultipleHypothesisComparison.Statistic - Class in gov.sandia.cognition.statistics.method
Result from a pairwise multiple-comparison statistic.
AbstractPairwiseMultipleHypothesisComparison.Statistic(Collection<? extends Collection<? extends Number>>, double, NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic
Creates a new instance of StudentizedMultipleComparisonStatistic
AbstractParallelAlgorithm - Class in gov.sandia.cognition.algorithm
Partial implementation of ParallelAlgorithm.
AbstractParallelAlgorithm() - Constructor for class gov.sandia.cognition.algorithm.AbstractParallelAlgorithm
Creates a new instance of AbstractParallelAlgorithm
AbstractParallelAlgorithm(ThreadPoolExecutor) - Constructor for class gov.sandia.cognition.algorithm.AbstractParallelAlgorithm
Creates a new instance of AbstractParallelAlgorithm
AbstractParallelizableCostFunction - Class in gov.sandia.cognition.learning.function.cost
Partial implementation of the ParallelizableCostFunction
AbstractParallelizableCostFunction(Collection<? extends InputOutputPair<? extends Vector, Vector>>) - Constructor for class gov.sandia.cognition.learning.function.cost.AbstractParallelizableCostFunction
Creates a new instance of AbstractParallelizableCostFunction
AbstractParameterCostMinimizer<ResultType extends VectorizableVectorFunction,CostFunctionType extends SupervisedCostFunction<Vector,Vector>> - Class in gov.sandia.cognition.learning.algorithm.regression
Partial implementation of ParameterCostMinimizer.
AbstractParameterCostMinimizer(CostFunctionType, int, double) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Creates a new instance of AbstractParameterCostMinimizer
AbstractParticleFilter<ObservationType,ParameterType> - Class in gov.sandia.cognition.statistics.bayesian
Partial abstract implementation of ParticleFilter.
AbstractParticleFilter() - Constructor for class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter
Default constructor.
AbstractPrincipalComponentsAnalysis - Class in gov.sandia.cognition.learning.algorithm.pca
Abstract implementation of PCA.
AbstractPrincipalComponentsAnalysis(int, PrincipalComponentsAnalysisFunction) - Constructor for class gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis
Creates a new instance of AbstractPrincipalComponentsAnalysis
AbstractRandomized - Class in gov.sandia.cognition.util
The AbstractRandomized abstract class implements the Randomized interface by containing the random object in a protected field.
AbstractRandomized(Random) - Constructor for class gov.sandia.cognition.util.AbstractRandomized
Creates a new instance of AbstractRandomized with the given Random object.
AbstractRandomVariable<DataType> - Class in gov.sandia.cognition.statistics
Partial implementation of RandomVariable.
AbstractRandomVariable() - Constructor for class gov.sandia.cognition.statistics.AbstractRandomVariable
 
AbstractRegressor<InputType> - Class in gov.sandia.cognition.learning.function.regression
An abstract implementation of the Regressor interface.
AbstractRegressor() - Constructor for class gov.sandia.cognition.learning.function.regression.AbstractRegressor
Creates a new AbstractRegressor.
AbstractRelation<SourceType,TargetType> - Class in gov.sandia.cognition.text.relation
An abstract implementation of a relation between two objects.
AbstractRelation() - Constructor for class gov.sandia.cognition.text.relation.AbstractRelation
Creates a new AbstractRelation with null source and target.
AbstractRelation(SourceType, TargetType) - Constructor for class gov.sandia.cognition.text.relation.AbstractRelation
Creates a new AbstractRelation with the given source and target.
AbstractReverseCachedDataConverter<InputType,OutputType,ReverseConverterType extends DataConverter<? super OutputType,? extends InputType>> - Class in gov.sandia.cognition.data.convert
Abstract implementation of ReversibleDataConverter that caches the reverse converter.
AbstractReverseCachedDataConverter() - Constructor for class gov.sandia.cognition.data.convert.AbstractReverseCachedDataConverter
Creates a new AbstractReverseCachedDataConverter.
AbstractReversibleDataConverter<InputType,OutputType> - Class in gov.sandia.cognition.data.convert
Abstract implementation of sthe ReversibleDataConverter interface.
AbstractReversibleDataConverter() - Constructor for class gov.sandia.cognition.data.convert.AbstractReversibleDataConverter
Creates a new AbstractReversibleDataConverter.
AbstractRing<RingType extends Ring<RingType>> - Class in gov.sandia.cognition.math
Implements the non-inline versions of the various Ring functions.
AbstractRing() - Constructor for class gov.sandia.cognition.math.AbstractRing
 
AbstractRootFinder - Class in gov.sandia.cognition.learning.algorithm.root
Partial implementation of RootFinder.
AbstractRootFinder() - Constructor for class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder
Creates a new instance of AbstractRootFinder
AbstractScalarFunction<InputType> - Class in gov.sandia.cognition.math
An abstract implementation of the ScalarFunction interface.
AbstractScalarFunction() - Constructor for class gov.sandia.cognition.math.AbstractScalarFunction
Creates a new AbstractScalarFunction.
AbstractScalarMap<KeyType> - Class in gov.sandia.cognition.collection
Partial implementation of ScalarMap
AbstractScalarMap() - Constructor for class gov.sandia.cognition.collection.AbstractScalarMap
Default Constructor
AbstractScalarMap.MapWrapper - Class in gov.sandia.cognition.collection
Wrapper when using the asMap method
AbstractScalarMap.MapWrapper() - Constructor for class gov.sandia.cognition.collection.AbstractScalarMap.MapWrapper
Default constructor
AbstractSelector<GenomeType> - Class in gov.sandia.cognition.learning.algorithm.genetic.selector
The AbstractSelector class provides some common functionality for implementations of Selectors.
AbstractSelector() - Constructor for class gov.sandia.cognition.learning.algorithm.genetic.selector.AbstractSelector
Creates a new instance of AbstractSelector.
AbstractSemanticIdentifier - Class in gov.sandia.cognition.framework
The AbstractSemanticIdentifier class implements the basic methods that are needed for a SemanticIdentifier to provide a good speed improvement.
AbstractSemanticIdentifier() - Constructor for class gov.sandia.cognition.framework.AbstractSemanticIdentifier
Creates a new instance of AbstractSemanticIdentifier
AbstractSemanticMemoryLite - Class in gov.sandia.cognition.framework.lite
The AbstractSemanticMemoryLite implements the common functionality among SemanticMemoryLite modules.
AbstractSemanticMemoryLite(SemanticIdentifierMap, PatternRecognizerLite) - Constructor for class gov.sandia.cognition.framework.lite.AbstractSemanticMemoryLite
Creates a new instance of AbstractSemanticMemoryLite.
AbstractSingleDocumentExtractor - Class in gov.sandia.cognition.text.document.extractor
An abstract implementation of the SingleDocumentExtractor interface.
AbstractSingleDocumentExtractor() - Constructor for class gov.sandia.cognition.text.document.extractor.AbstractSingleDocumentExtractor
Creates a new AbstractSingleDocumentExtractor.
AbstractSingleTermFilter - Class in gov.sandia.cognition.text.term.filter
An abstract implementation of the SingleTermFilter interface.
AbstractSingleTermFilter() - Constructor for class gov.sandia.cognition.text.term.filter.AbstractSingleTermFilter
Creates a new AbstractSingleTermFilter.
AbstractSingleTextualConverter<InputType,OutputType extends Textual> - Class in gov.sandia.cognition.text.convert
An abstract implementation of the SingleTextualConverter interface.
AbstractSingleTextualConverter() - Constructor for class gov.sandia.cognition.text.convert.AbstractSingleTextualConverter
Creates a new AbstractSingleTextualConverter.
AbstractSingularValueDecomposition - Class in gov.sandia.cognition.math.matrix.decomposition
Abstract container class that stores the matrices for a Singular Value Decomposition (SVD) and related operations but does not actually perform a singular value decomposition
AbstractSingularValueDecomposition() - Constructor for class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition
Default constructor that nulls out all matrices
AbstractSingularValueDecomposition(Matrix, Matrix, Matrix) - Constructor for class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition
Creates a new instance of AbstractSingularValueDecomposition where U*S*Vtranspose = original_matrix
AbstractSparseMatrix - Class in gov.sandia.cognition.math.matrix.mtj
Implements some generic operations that any sparse-matrix representation must do.
AbstractSparseMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix
Creates a new instance of AbstractSparseMatrix using the given MTJ matrix
AbstractStatefulEvaluator<InputType,OutputType,StateType extends CloneableSerializable> - Class in gov.sandia.cognition.evaluator
The AbstractStatefulEvalutor class is an abstract implementation of the StatefulEvalutor interface.
AbstractStatefulEvaluator() - Constructor for class gov.sandia.cognition.evaluator.AbstractStatefulEvaluator
Creates a new instance of AbstractStatefulEvaluator.
AbstractStatefulEvaluator(StateType) - Constructor for class gov.sandia.cognition.evaluator.AbstractStatefulEvaluator
Creates a new instance of AbstractStatefulEvaluator.
AbstractStreamSerializationHandler<SerializedType> - Class in gov.sandia.cognition.io.serialization
An abstract implementation of StreamSerializationHandler.
AbstractStreamSerializationHandler() - Constructor for class gov.sandia.cognition.io.serialization.AbstractStreamSerializationHandler
Creates a new AbstractStreamSerializationHandler.
AbstractSufficientStatistic<DataType,DistributionType> - Class in gov.sandia.cognition.statistics
Partial implementation of SufficientStatistic
AbstractSufficientStatistic() - Constructor for class gov.sandia.cognition.statistics.AbstractSufficientStatistic
Creates a new instance of AbstractSufficientStatistic
AbstractSupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> - Class in gov.sandia.cognition.learning.algorithm
An abstract implementation of the batch and incremental learning for an incremental supervised learner.
AbstractSupervisedBatchAndIncrementalLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.AbstractSupervisedBatchAndIncrementalLearner
Creates a new AbstractSupervisedBatchAndIncrementalLearner.
AbstractSupervisedCostFunction<InputType,TargetType> - Class in gov.sandia.cognition.learning.function.cost
Partial implementation of SupervisedCostFunction
AbstractSupervisedCostFunction() - Constructor for class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction
Creates a new instance of AbstractSupervisedCostFunction
AbstractSupervisedCostFunction(Collection<? extends InputOutputPair<? extends InputType, TargetType>>) - Constructor for class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction
Creates a new instance of AbstractSupervisedCostFunction
AbstractSupervisedPerformanceEvaluator<InputType,TargetType,EstimateType,ResultType> - Class in gov.sandia.cognition.learning.performance
The AbstractSupervisedPerformanceEvaluator class contains an abstract implementation of the SupervisedPerformanceEvaluator class.
AbstractSupervisedPerformanceEvaluator() - Constructor for class gov.sandia.cognition.learning.performance.AbstractSupervisedPerformanceEvaluator
Creates a new AbstractSupervisedPerformanceEvaluator.
AbstractTargetEstimatePair<TargetType,EstimateType> - Class in gov.sandia.cognition.learning.data
An abstract implementation of the TargetEstimatePair.
AbstractTargetEstimatePair() - Constructor for class gov.sandia.cognition.learning.data.AbstractTargetEstimatePair
Creates a new AbstractTargetEstimatePair.
AbstractTemporal - Class in gov.sandia.cognition.util
Partial implementation of Temporal
AbstractTemporal() - Constructor for class gov.sandia.cognition.util.AbstractTemporal
Creates a new instance of AbstractTemporal
AbstractTemporal(Date) - Constructor for class gov.sandia.cognition.util.AbstractTemporal
Creates a new instance of AbstractTemporal
AbstractTerm - Class in gov.sandia.cognition.text.term
Creates a new AbstractTerm.
AbstractTerm() - Constructor for class gov.sandia.cognition.text.term.AbstractTerm
Creates a new AbstractTerm.
AbstractTermIndex - Class in gov.sandia.cognition.text.term
An abstract implementation of the TermIndex class that handles a lot of the convenience method implementations.
AbstractTermIndex() - Constructor for class gov.sandia.cognition.text.term.AbstractTermIndex
Creates a new AbstractTermIndex.
AbstractTermWeightNormalizer - Class in gov.sandia.cognition.text.term.vector.weighter.normalize
An abstract implementation of the TermWeightNormalizer interface.
AbstractTermWeightNormalizer() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.normalize.AbstractTermWeightNormalizer
Creates a new AbstractTermWeightNormalizer.
AbstractTextSerializationHandler<SerializedType> - Class in gov.sandia.cognition.io.serialization
An abstract implementation of the TextSerializationHandler interface.
AbstractTextSerializationHandler() - Constructor for class gov.sandia.cognition.io.serialization.AbstractTextSerializationHandler
Creates a new AbstractTextSerializationHandler.
AbstractTextual - Class in gov.sandia.cognition.text
A default implementation of the Textual interface.
AbstractTextual() - Constructor for class gov.sandia.cognition.text.AbstractTextual
Creates a new AbstractTextual.
AbstractTextualConverter<InputType,OutputType extends Textual> - Class in gov.sandia.cognition.text.convert
An abstract implementation of the TextualConverter interface.
AbstractTextualConverter() - Constructor for class gov.sandia.cognition.text.convert.AbstractTextualConverter
Creates a new AbstractTextualConverter.
AbstractThresholdBinaryCategorizer<InputType> - Class in gov.sandia.cognition.learning.function.categorization
Categorizer that first maps the input space onto a real value, then uses a threshold to map the result onto lowValue (for strictly less than the threshold) or highValue (for greater than or equal to the threshold).
AbstractThresholdBinaryCategorizer(double) - Constructor for class gov.sandia.cognition.learning.function.categorization.AbstractThresholdBinaryCategorizer
Creates a new AbstractThresholdBinaryCategorizer
AbstractTokenizer - Class in gov.sandia.cognition.text.token
Abstract implementation of the Tokenizer interface.
AbstractTokenizer() - Constructor for class gov.sandia.cognition.text.token.AbstractTokenizer
Creates a new AbstractTokenizer.
AbstractToVectorEncoder<InputType> - Class in gov.sandia.cognition.data.convert.vector
An abstract implementation of the DataToVectorEncoder interface.
AbstractToVectorEncoder() - Constructor for class gov.sandia.cognition.data.convert.vector.AbstractToVectorEncoder
Creates a new AbstractToVectorEncoder.
AbstractToVectorEncoder(VectorFactory<?>) - Constructor for class gov.sandia.cognition.data.convert.vector.AbstractToVectorEncoder
Creates a new AbstractToVectorEncoder with the given vector factory.
AbstractUnivariateScalarFunction - Class in gov.sandia.cognition.math
Abstract implementation of ScalarFunction where the evaluate(Double) method calls back into the evaluate(double) method.
AbstractUnivariateScalarFunction() - Constructor for class gov.sandia.cognition.math.AbstractUnivariateScalarFunction
Creates a new AbstractUnivariateScalarFunction.
AbstractUnweightedEnsemble<MemberType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An abstract implementation of the Ensemble interface for unweighted ensembles.
AbstractUnweightedEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractUnweightedEnsemble
Creates a new AbstractUnweightedEnsemble.
AbstractUnweightedEnsemble(List<MemberType>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractUnweightedEnsemble
Creates a new AbstractUnweightedEnsemble with the given list of members.
AbstractValidationFoldExperiment<InputDataType,FoldDataType> - Class in gov.sandia.cognition.learning.experiment
The AbstractValidationFoldExperiment class implements a common way of structuring an experiment around a ValidationFoldCreator object where the fold creator is used to create each of the individual trials of the experiment.
AbstractValidationFoldExperiment() - Constructor for class gov.sandia.cognition.learning.experiment.AbstractValidationFoldExperiment
Creates a new instance of AbstractValidationFoldExperiment.
AbstractValidationFoldExperiment(ValidationFoldCreator<InputDataType, FoldDataType>) - Constructor for class gov.sandia.cognition.learning.experiment.AbstractValidationFoldExperiment
Creates a new instance of AbstractValidationFoldExperiment.
AbstractValueDiscriminantPair<ValueType,DiscriminantType extends Comparable<? super DiscriminantType>> - Class in gov.sandia.cognition.learning.data
An abstract implementation of the ValueDiscriminantPair interface.
AbstractValueDiscriminantPair() - Constructor for class gov.sandia.cognition.learning.data.AbstractValueDiscriminantPair
Creates a new AbstractValueDiscriminantPair.
AbstractVector - Class in gov.sandia.cognition.math.matrix
Abstract implementation of some of the Vector interface, in a storage-free manner
AbstractVector() - Constructor for class gov.sandia.cognition.math.matrix.AbstractVector
 
AbstractVectorSpace<VectorType extends VectorSpace<VectorType,? extends EntryType>,EntryType extends VectorSpace.Entry> - Class in gov.sandia.cognition.math.matrix
Partial implementation of VectorSpace
AbstractVectorSpace() - Constructor for class gov.sandia.cognition.math.matrix.AbstractVectorSpace
Creates a new instance of AbstractVectorSpace
AbstractVectorSpaceModel - Class in gov.sandia.cognition.text.term.vector
An abstract implementation of the VectorSpaceModel class.
AbstractVectorSpaceModel() - Constructor for class gov.sandia.cognition.text.term.vector.AbstractVectorSpaceModel
Creates a new AbstractVectorSpaceModel.
AbstractVectorThresholdMaximumGainLearner<OutputType> - Class in gov.sandia.cognition.learning.algorithm.tree
An abstract class for decider learners that produce a threshold function on a vector element based on maximizing some gain value.
AbstractVectorThresholdMaximumGainLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
Creates a new AbstractVectorThresholdMaximumGainLearner.
AbstractWeighted - Class in gov.sandia.cognition.util
Container class for a Weighted object
AbstractWeighted() - Constructor for class gov.sandia.cognition.util.AbstractWeighted
Creates a new instance of AbstractWeighted
AbstractWeighted(double) - Constructor for class gov.sandia.cognition.util.AbstractWeighted
Creates a new instance of AbstractWeighted
AbstractWeightedEnsemble<MemberType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An abstract implementation of the Ensemble interface for ensembles that have a weight associated with each member.
AbstractWeightedEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble
Creates a new, empty of AbstractWeightedEnsemble.
AbstractWeightedEnsemble(List<WeightedValue<MemberType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble
Creates a new instance of AbstractWeightedEnsemble.
acceptNullHypothesis(int, int) - Method in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic
 
acceptNullHypothesis(int, int) - Method in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment.Statistic
 
acceptNullHypothesis(int, int) - Method in interface gov.sandia.cognition.statistics.method.MultipleHypothesisComparison.Statistic
Determines if the (i,j) null hypothesis should be accepted (true) or rejected (false) .
acceptNullHypothesis(int, int) - Method in class gov.sandia.cognition.statistics.method.NemenyiConfidence.Statistic
 
acceptNullHypothesis(int, int) - Method in class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic
 
ACCESSED_DATE_FIELD_NAME - Static variable in class gov.sandia.cognition.text.document.AbstractDocument
The name of the last accessed date field is "accessedDate".
accumulate(RingType) - Method in class gov.sandia.cognition.math.RingAccumulator
Adds the given object to the accumulation.
accumulate(Iterable<? extends RingType>) - Method in class gov.sandia.cognition.math.RingAccumulator
Adds all of the given set of objects onto the accumulation.
Activatable - Interface in gov.sandia.cognition.framework
The Activatable interface provides a general definition for objects that can be isActivated.
ActivatableCogxel - Interface in gov.sandia.cognition.framework
ActivatableCogxel is an interface which defines a cogxel which is activatable.
AdaBoost<InputType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
The AdaBoost class implements the Adaptive Boosting (AdaBoost) algorithm formulated by Yoav Freund and Robert Shapire.
AdaBoost() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
Creates a new instance of AdaBoost with no base learner.
AdaBoost(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, Boolean>>, ? extends Evaluator<? super InputType, ? extends Boolean>>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
Creates a new instance of AdaBoost.
AdaBoost(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, Boolean>>, ? extends Evaluator<? super InputType, ? extends Boolean>>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
Creates a new instance of AdaBoost.
adapt(ObjectType, DataType) - Method in interface gov.sandia.cognition.learning.parameter.ParameterAdapter
Adapt the parameter(s) of a given object based on the given data.
AdaptiveRegularizationOfWeights - Class in gov.sandia.cognition.learning.algorithm.confidence
An implementation of the Adaptive Regularization of Weights (AROW) algorithm for online learning of a linear binary categorizer.
AdaptiveRegularizationOfWeights() - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.AdaptiveRegularizationOfWeights
Creates a new AdaptiveRegularizationOfWeights with default parameters.
AdaptiveRegularizationOfWeights(double) - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.AdaptiveRegularizationOfWeights
Creates a new AdaptiveRegularizationOfWeights with the given parameters
AdaptiveRejectionSampling - Class in gov.sandia.cognition.statistics.bayesian
Samples form a univariate distribution using the method of adaptive rejection sampling, which is a very efficient method that iteratively improves the rejection and acceptance envelopes in response to additional points.
AdaptiveRejectionSampling() - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Creates a new instance of AdaptiveRejectionSampling
AdaptiveRejectionSampling.AbstractEnvelope - Class in gov.sandia.cognition.statistics.bayesian
Describes an enveloping function comprised of a sorted sequence of lines
AdaptiveRejectionSampling.AbstractEnvelope() - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.AbstractEnvelope
Default constructor
AdaptiveRejectionSampling.LineSegment - Class in gov.sandia.cognition.statistics.bayesian
A line that has a minimum and maximum support (x-axis) value.
AdaptiveRejectionSampling.LineSegment(PolynomialFunction.Linear, double, double) - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LineSegment
Creates a new instance of LineSegment
AdaptiveRejectionSampling.LogEvaluator<EvaluatorType extends Evaluator<Double,Double>> - Class in gov.sandia.cognition.statistics.bayesian
Wraps an Evaluator and takes the natural logarithm of the evaluate method
AdaptiveRejectionSampling.LogEvaluator(EvaluatorType) - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LogEvaluator
Creates a new instance of LogEvaluator
AdaptiveRejectionSampling.LowerEnvelope - Class in gov.sandia.cognition.statistics.bayesian
Define the lower envelope for Adaptive Rejection Sampling
AdaptiveRejectionSampling.LowerEnvelope() - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LowerEnvelope
Default constructor
AdaptiveRejectionSampling.PDFLogEvaluator - Class in gov.sandia.cognition.statistics.bayesian
Wraps a PDF so that it returns the logEvaluate method.
AdaptiveRejectionSampling.PDFLogEvaluator(ProbabilityFunction<Double>) - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.PDFLogEvaluator
Creates a new instance of PDFLogEvaluator
AdaptiveRejectionSampling.Point - Class in gov.sandia.cognition.statistics.bayesian
An InputOutputPair that has a natural ordering according to their input (x-axis) values.
AdaptiveRejectionSampling.Point(double, double) - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.Point
Creates a new instance of Point
AdaptiveRejectionSampling.UpperEnvelope - Class in gov.sandia.cognition.statistics.bayesian
Constructs the upper envelope for sampling.
AdaptiveRejectionSampling.UpperEnvelope() - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
Default constructor
add(ValueType) - Method in class gov.sandia.cognition.collection.DefaultIndexer
 
add(DataType) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
Appends the element to the end of the buffer, removing excess elements if necessary
add(DataType) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer.InternalIterator
 
add(ValueType) - Method in interface gov.sandia.cognition.collection.Indexer
Adds a value to the indexer and returns the index assigned to the value.
add(MemberType) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractUnweightedEnsemble
Adds a given member to the ensemble.
add(MemberType) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble
Adds the given regression function with a default weight of 1.0.
add(MemberType, double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble
Adds the given regression function with a given weight.
add(MemberType) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.VotingCategorizerEnsemble
Adds a given member to the ensemble.
add(MemberType, double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAveragingEnsemble
 
add(MemberType) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble
Adds the given categorizer with a default weight of 1.0.
add(MemberType, double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble
Adds the given categorizer with a given weight.
add(MemberType) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble
Adds the given categorizer with a default weight of 1.0.
add(MemberType, double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble
Adds the given categorizer with a given weight.
add(InputOutputPair<? extends InputType, OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.AbstractNearestNeighbor
 
add(InputOutputPair<? extends InputType, OutputType>) - Method in interface gov.sandia.cognition.learning.algorithm.nearest.NearestNeighbor
Adds the Pair to the data.
add(InputType, double) - Method in class gov.sandia.cognition.learning.function.categorization.DefaultKernelBinaryCategorizer
Adds a new example of the given value with the given weight.
add(CategoryType, CategoryType) - Method in class gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix
 
add(CategoryType, CategoryType) - Method in interface gov.sandia.cognition.learning.performance.categorization.ConfusionMatrix
Adds a count of one to the matrix entry for the (actual, predicted) pair.
add(CategoryType, CategoryType, double) - Method in interface gov.sandia.cognition.learning.performance.categorization.ConfusionMatrix
Adds a given value to the matrix entry for the (actual, predicted) pair.
add(Boolean, Boolean, double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
 
add(CategoryType, CategoryType, double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
 
add(PairType) - Method in class gov.sandia.cognition.math.geometry.KDTree
 
add(PairType, double) - Method in class gov.sandia.cognition.math.geometry.KDTree.Neighborhood
Adds the neighbor to the priority queue.
add(DataType) - Method in class gov.sandia.cognition.math.geometry.Quadtree
Adds an item to the tree.
add(double, double) - Static method in class gov.sandia.cognition.math.LogMath
Adds two log-domain values.
add(String) - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Adds a word to the dictionary of counts for the spelling corrector.
add(String, int) - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Adds a given number of counts for a word to the dictionary of counts for the spelling corrector.
add(Termable) - Method in class gov.sandia.cognition.text.term.AbstractTermIndex
 
add(Termable) - Method in class gov.sandia.cognition.text.term.DefaultTermCounts
Increments the count for a given term.
add(Term, int) - Method in class gov.sandia.cognition.text.term.DefaultTermCounts
Adds the given amount for the given term.
add(Term) - Method in class gov.sandia.cognition.text.term.DefaultTermIndex
 
add(String) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
Adds a word to the stop list.
add(Termable) - Method in interface gov.sandia.cognition.text.term.TermIndex
Adds the given term to the index.
add(Term) - Method in interface gov.sandia.cognition.text.term.TermIndex
Adds the given term to the index.
add(Vectorizable) - Method in class gov.sandia.cognition.text.term.vector.AbstractVectorSpaceModel
 
add(Vectorizable) - Method in interface gov.sandia.cognition.text.term.vector.VectorSpaceModel
Adds a document to the model.
add(Vector) - Method in interface gov.sandia.cognition.text.term.vector.VectorSpaceModel
Adds a document to the model.
add(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractEntropyBasedGlobalTermWeighter
 
add(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
 
add(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.DominanceGlobalTermWeighter
 
add(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.EntropyGlobalTermWeighter
 
add(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.InverseDocumentFrequencyGlobalTermWeighter
 
addAll(Iterable<? extends ValueType>) - Method in class gov.sandia.cognition.collection.DefaultIndexer
 
addAll(Iterable<? extends ValueType>) - Method in interface gov.sandia.cognition.collection.Indexer
Adds all of the given values to the index.
addAll(ConfusionMatrix<OtherType>) - Method in class gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix
 
addAll(ConfusionMatrix<OtherType>) - Method in interface gov.sandia.cognition.learning.performance.categorization.ConfusionMatrix
Adds all of the values in the given confusion matrix to this confusion matrix.
addAll(Collection<? extends DataType>) - Method in class gov.sandia.cognition.math.geometry.Quadtree
Adds all the items to the
addAll(Iterable<? extends Termable>) - Method in class gov.sandia.cognition.text.term.AbstractTermIndex
 
addAll(Iterable<? extends Termable>) - Method in class gov.sandia.cognition.text.term.DefaultTermCounts
Adds all of the given terms to the counters; one for each term occurrence.
addAll(Iterable<String>) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
Adds all of the given words to the stop list.
addAll(Iterable<? extends Termable>) - Method in interface gov.sandia.cognition.text.term.TermIndex
Adds all of the given terms to the index, if they are not already part of it.
addAll(Iterable<? extends Vectorizable>) - Method in class gov.sandia.cognition.text.term.vector.AbstractVectorSpaceModel
 
addAll(Iterable<? extends Vectorizable>) - Method in interface gov.sandia.cognition.text.term.vector.VectorSpaceModel
Adds all of the given documents to the model.
addCategory(CategoryType, double, ProbabilityFunction<ObservationType>) - Method in class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer
Adds the given category with the given mass (which is divided by the masses of all categories to determine the prior probability weight) and the distribution function
addChild(InteriorType, DecisionTreeNode<InputType, OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
Adds a child for a given interior type.
addClusterMember(DefaultCluster<DataType>, DataType) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultIncrementalClusterCreator
 
addClusterMember(ClusterType, DataType) - Method in interface gov.sandia.cognition.learning.algorithm.clustering.cluster.IncrementalClusterCreator
Adds a member to the given cluster.
addClusterMember(CentroidCluster<Vector>, Vector) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanCentroidClusterCreator
 
addCognitiveModelListener(CognitiveModelListener) - Method in class gov.sandia.cognition.framework.AbstractCognitiveModel
Adds a CognitiveModelListener to this model.
addCognitiveModelListener(CognitiveModelListener) - Method in interface gov.sandia.cognition.framework.CognitiveModel
Adds a CognitiveModelListener to this model.
addCogxel(Cogxel) - Method in interface gov.sandia.cognition.framework.CogxelState
Adds a Cogxel to the state, overriding the existing Cogxel, if it exists.
addCogxel(Cogxel) - Method in class gov.sandia.cognition.framework.lite.CogxelStateLite
Adds a Cogxel to the state, overriding the existing Cogxel, if it exists.
addEnsembleMember(MemberType) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Adds a new member to the ensemble.
addEnsembleMember(Evaluator<? super InputType, ? extends CategoryType>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner
 
addEnsembleMember(Evaluator<? super InputType, ? extends Number>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingRegressionLearner
 
addEnsembleMember(Evaluator<? super InputType, ? extends Boolean>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BinaryBaggingLearner
 
addField(Field) - Method in class gov.sandia.cognition.text.document.AbstractDocument
Adds a field to the document.
addField(Field) - Method in class gov.sandia.cognition.text.document.DefaultDocument
 
addFirst(DataType) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
Prepend the element to the beginning of the buffer, removing excess elements if necessary
addIterativeAlgorithmListener(IterativeAlgorithmListener) - Method in class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
 
addIterativeAlgorithmListener(IterativeAlgorithmListener) - Method in interface gov.sandia.cognition.algorithm.IterativeAlgorithm
Adds a listener for the iterations of the algorithm.
AdditiveEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends Number>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An ensemble of regression functions that determine the result by adding their outputs together.
AdditiveEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AdditiveEnsemble
Creates a new, empty AdditiveEnsemble.
AdditiveEnsemble(List<MemberType>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AdditiveEnsemble
Creates a new AdditiveEnsemble with the given members and a bias of 0.
AdditiveEnsemble(List<MemberType>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AdditiveEnsemble
Creates a new AdditiveEnsemble with the given members.
addLabel(SemanticLabel) - Method in class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap
Adds a SemanticLabel to the map, or returns an existing SemanticIdentifier if already in the map
addLabel(SemanticLabel) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Adds the given SemanticLabel to the list of labels used by the converter.
addLabel(SemanticLabel) - Method in interface gov.sandia.cognition.framework.SemanticIdentifierMap
Adds a SemanticLabel to the map, or returns an existing SemanticIdentifier if already in the map
addLabels(Collection<SemanticLabel>) - Method in class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap
Adds a list of SemanticLabels to the map, returning the list of the corresponding SemanticIdentifiers for the given SemanticLabels.
addLabels(Iterable<SemanticLabel>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Adds all of the given labels to the converter.
addLabels(SemanticLabel[]) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Adds all of the given labels to the converter.
addLabels(Collection<SemanticLabel>) - Method in interface gov.sandia.cognition.framework.SemanticIdentifierMap
Adds a list of SemanticLabels to the map, returning the list of the corresponding SemanticIdentifiers for the given SemanticLabels.
addLabelToIdentifierCache(SemanticLabel) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Adds the given label to the cache of SemanticIdentifiers.
addLast(DataType) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
Appends the element to the end of the buffer, removing excess elements if necessary
addLink(String, String, double) - Method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Called when the "link" directive is seen.
addListener(ProcessLauncherListener) - Method in class gov.sandia.cognition.io.ProcessLauncher
Adds the listener to the event queue
addListener(LearningExperimentListener) - Method in class gov.sandia.cognition.learning.experiment.AbstractLearningExperiment
 
addListener(LearningExperimentListener) - Method in interface gov.sandia.cognition.learning.experiment.LearningExperiment
Adds the given listener to this object.
addModuleFactory(CognitiveModuleFactory) - Method in class gov.sandia.cognition.framework.AbstractCognitiveModelFactory
Adds a CognitiveModuleFactory to be used by this factory when creating a new CognitiveModel.
addNode(SemanticLabel) - Method in class gov.sandia.cognition.framework.DefaultSemanticNetwork
Adds a node to the semantic network.
addNode(String) - Method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Called when the "node" directive is seen.
addNode(SemanticLabel) - Method in interface gov.sandia.cognition.framework.lite.MutablePatternRecognizerLite
Adds a node to the pattern recognizer.
addNode(SemanticLabel) - Method in class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLite
Adds a node to the semantic memory.
addNode(SemanticLabel) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Adds a node to the pattern recognizer.
addParameterAdapter(ParameterAdapter<? super ObjectType, ? super DataType>) - Method in interface gov.sandia.cognition.learning.parameter.ParameterAdaptable
Adds the given parameter adapter to this object.
addParameterAdapter(ParameterAdapter<? super LearnerType, ? super DataType>) - Method in class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper
 
addPoint(double, double) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Adds a point to the set, which will adject the upper and lower envelopes
addSemanticIdentifierMapListener(SemanticIdentifierMapListener) - Method in class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap
Adds a listener to this semantic identifier map.
addSemanticIdentifierMapListener(SemanticIdentifierMapListener) - Method in interface gov.sandia.cognition.framework.SemanticIdentifierMap
Adds a listener to this semantic identifier map.
adjust(double, int) - Static method in class gov.sandia.cognition.statistics.method.BonferroniCorrection
Computes the Bonferroni multiple-comparison correction
adjust(double, int) - Static method in class gov.sandia.cognition.statistics.method.SidakCorrection
Computes the Sidak multiple-comparison correction
adjustedAlpha - Variable in class gov.sandia.cognition.statistics.method.AdjustedPValueStatistic
Adjusted alpha term to account for multiple comparisons
adjustedAlphas - Variable in class gov.sandia.cognition.statistics.method.HolmCorrection.Statistic
Matrix of adjusted alphas (p-value thresholds) for each comparison
adjustedAlphas - Variable in class gov.sandia.cognition.statistics.method.ShafferStaticCorrection.Statistic
Matrix of adjusted alphas (p-value thresholds) for each comparison
AdjustedPValueStatistic - Class in gov.sandia.cognition.statistics.method
A multiple-comparison statistic derived from a single adjusted p-value.
AdjustedPValueStatistic(Collection<? extends Collection<? extends Number>>, double, double, NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.AdjustedPValueStatistic
Creates a new instance of StudentizedMultipleComparisonStatistic
advanceInternalIterators() - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
Internal routine for advancing the internal iterators
advanceInternalIterators() - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
Internal method for advancing the internal Iterators
AffinityPropagation<DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering
The AffinityPropagation algorithm requires three parameters: a divergence function, a value to use for self-divergence, and a damping factor (called lambda in the paper; 0.5 is the default).
AffinityPropagation() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Creates a new instance of AffinityPropagation.
AffinityPropagation(DivergenceFunction<? super DataType, ? super DataType>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Creates a new instance of AffinityPropagation.
AffinityPropagation(DivergenceFunction<? super DataType, ? super DataType>, double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Creates a new instance of AffinityPropagation.
AffinityPropagation(DivergenceFunction<? super DataType, ? super DataType>, double, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Creates a new instance of AffinityPropagation.
AgglomerativeClusterer<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering
The AgglomerativeClusterer implements an agglomerative clustering algorithm, which is a type of hierarchical clustering algorithm.
AgglomerativeClusterer() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Creates a new instance of AgglomerativeClusterer.
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType, ? super DataType>, ClusterCreator<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Initializes the clustering to use the given metric between clusters, and the given cluster creator.
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType, ? super DataType>, ClusterCreator<ClusterType, DataType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Initializes the clustering to use the given metric between clusters, the given cluster creator, and the minimum number of clusters to allow.
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType, ? super DataType>, ClusterCreator<ClusterType, DataType>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Initializes the clustering to use the given metric between clusters, the given cluster merger, and the maximum minimum distance between clusters to allow.
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType, ? super DataType>, ClusterCreator<ClusterType, DataType>, int, double) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Initializes the clustering to use the given metric between clusters, the given cluster merger, the minimum number of clusters to allow, and the maximum minimum distance between clusters to allow.
AgglomerativeClusterer.HierarchyNode<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering
Holds the hierarchy information for the agglomerative clusterer.
AgglomerativeClusterer.HierarchyNode() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer.HierarchyNode
Creates a new HierarchyNode.
AgglomerativeClusterer.HierarchyNode(ClusterType) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer.HierarchyNode
Creates a new HierarchyNode.
AgglomerativeClusterer.HierarchyNode(ClusterType, AgglomerativeClusterer.HierarchyNode<DataType, ClusterType>, AgglomerativeClusterer.HierarchyNode<DataType, ClusterType>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer.HierarchyNode
Creates a new HierarchyNode.
aggressiveness - Variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin
The aggressiveness parameter (C), which is the trade-off between aggressive updating to meet an incorrect example and keeping history around.
AggressiveRelaxedOnlineMaximumMarginAlgorithm - Class in gov.sandia.cognition.learning.algorithm.perceptron
An implementation of the Aggressive Relaxed Online Maximum Margin Algorithm (AROMMA).
AggressiveRelaxedOnlineMaximumMarginAlgorithm() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AggressiveRelaxedOnlineMaximumMarginAlgorithm
Creates a new AggressiveRelaxedOnlineMaximumMarginAlgorithm.
AggressiveRelaxedOnlineMaximumMarginAlgorithm(VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.AggressiveRelaxedOnlineMaximumMarginAlgorithm
Creates a new AggressiveRelaxedOnlineMaximumMarginAlgorithm with the given vector factory.
algorithmEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
 
algorithmEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener
 
algorithmEnded(IterativeAlgorithm) - Method in interface gov.sandia.cognition.algorithm.IterativeAlgorithmListener
This method is called when the algorithm has ended, after the last step of the algorithm.
algorithmEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria
 
algorithmStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
 
algorithmStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener
 
algorithmStarted(IterativeAlgorithm) - Method in interface gov.sandia.cognition.algorithm.IterativeAlgorithmListener
This method is called when a algorithm has started, before the first step of the algorithm.
algorithmStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria
 
allowedTerms - Variable in class gov.sandia.cognition.text.term.filter.DictionaryFilter
The set of terms allowed by the filter.
alnorm(double, boolean) - Static method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.APStat
Algorithm AS66 Applied Statistics (1973) vol22 no.3.
alpha - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.StateObservationLikelihoodTask
Alpha at time n.
alpha - Variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
Scaling parameter which defines the strength of the base distribution, must be greater than zero.
alpha - Variable in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
CRP concentration parameter, must be greater than zero.
alpha - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The alpha parameter controlling the Dirichlet distribution for the document-topic probabilities.
alphabet - Variable in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
The alphabet of lower case characters.
alphabet - Variable in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector.Learner
The alphabet of lower case characters.
alphaInverseSampler - Variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Samples a new alpha-inverse.
AnalysisOfVarianceOneWay - Class in gov.sandia.cognition.statistics.method
Analysis of Variance single-factor null-hypothesis testing procedure, usually called "1-way ANOVA".
AnalysisOfVarianceOneWay() - Constructor for class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay
Creates a new instance of AnalysisOfVarianceOneWay
AnalysisOfVarianceOneWay.Statistic - Class in gov.sandia.cognition.statistics.method
Returns the confidence statistic for an ANOVA test
AnalysisOfVarianceOneWay.Statistic(double, double, double) - Constructor for class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay.Statistic
Creates a new instance of Statistic
angle(VectorType) - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
 
angle(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
angle(VectorType) - Method in interface gov.sandia.cognition.math.matrix.VectorSpace
Computes the angle between two Vectors.
AnytimeAlgorithm<ResultType> - Interface in gov.sandia.cognition.algorithm
The AnytimeAlgorithm interface defines the functionality of an iterative algorithm that is stoppable and can return intermediate results.
AnytimeAlgorithmWrapper<ResultType,InternalAlgorithm extends AnytimeAlgorithm<?>> - Class in gov.sandia.cognition.algorithm
Wraps an AnytimeAlgorithm.
AnytimeAlgorithmWrapper() - Constructor for class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
Creates a new instance of AnytimeAlgorithmWrapper
AnytimeAlgorithmWrapper(InternalAlgorithm) - Constructor for class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
Creates a new instance of AnytimeAlgorithmWrapper
AnytimeBatchLearner<DataType,ResultType> - Interface in gov.sandia.cognition.learning.algorithm
A batch learner that is also and Anytime algorithm.
appendBias(Collection<? extends Vector>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Appends a bias (constant 1.0) to the end of each Vector in the dataset, the original dataset is unmodified.
appendBias(Collection<? extends Vector>, double) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Appends "biasValue" to the end of each Vector in the dataset, the original dataset is unmodified.
applyUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, double, double, double, double, Vector) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron
Apply the update for the Projectron.
applyUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, double, double, double, double, Vector) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron.LinearSoftMargin
 
areAllOutputsEqual(Collection<? extends InputOutputPair<? extends InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner
Determines if all of the output values in the collection are equal.
areLocalItemsSame() - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Returns true if this is a leaf and all the local items are the same.
ArgumentChecker - Class in gov.sandia.cognition.util
A utility class for checking arguments to a function.
ArgumentChecker() - Constructor for class gov.sandia.cognition.util.ArgumentChecker
 
ArrayBasedCognitiveModelInput - Class in gov.sandia.cognition.framework.lite
The ArrayBasedCognitiveModelInput class implements a CognitiveModelInput that is used by the ArrayBasedPerceptionModule.
ArrayBasedCognitiveModelInput(SemanticIdentifier[], double[]) - Constructor for class gov.sandia.cognition.framework.lite.ArrayBasedCognitiveModelInput
Creates a new instance of ArrayBasedCognitiveModelInput using the two given arrays underneath by copying them.
ArrayBasedCognitiveModelInput(SemanticIdentifier[], double[], boolean) - Constructor for class gov.sandia.cognition.framework.lite.ArrayBasedCognitiveModelInput
Creates a new instance of ArrayBasedCognitiveModelInput using the two given arrays underneath.
ArrayBasedPerceptionModule - Class in gov.sandia.cognition.framework.lite
The ArrayBasedPerceptionModule class implements a simple CognitiveModule that sets the state of Cogxels based on a given input of SemanticIdentifiers and their associated activation values.
ArrayBasedPerceptionModule(SemanticIdentifierMap, CogxelFactory) - Constructor for class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModule
Creates a new instance of ArrayBasedPerceptionModule.
ArrayBasedPerceptionModuleFactory - Class in gov.sandia.cognition.framework.lite
The ArrayBasedPerceptionModuleFactory class implements a CognitiveModuleFactory for ArrayBasedPerceptionModules.
ArrayBasedPerceptionModuleFactory() - Constructor for class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModuleFactory
Creates a new instance of ArrayBasedPerceptionModuleFactory.
ArrayBasedPerceptionModuleFactory(CogxelFactory) - Constructor for class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModuleFactory
Creates a new instance of ArrayBasedPerceptionModuleFactory.
ArrayIndexSorter - Class in gov.sandia.cognition.util
Returns the indices of the array sorted in ascending or descending order
ArrayIndexSorter() - Constructor for class gov.sandia.cognition.util.ArrayIndexSorter
 
ArrayUtil - Class in gov.sandia.cognition.collection
Utility class for handling arrays.
ArrayUtil() - Constructor for class gov.sandia.cognition.collection.ArrayUtil
 
asArrayList(Iterable<DataType>) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Returns the Collection as an ArrayList.
asDivergence() - Method in interface gov.sandia.cognition.text.relation.SimilarityFunction
Converts the similarity function into a divergence function.
asDivergence() - Method in class gov.sandia.cognition.text.term.vector.CosineSimilarityFunction
 
asMap() - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap
 
asMap() - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
asMap() - Method in class gov.sandia.cognition.collection.DefaultIndexer
 
asMap() - Method in interface gov.sandia.cognition.collection.Indexer
Gets mapping of values to indices.
asMap() - Method in interface gov.sandia.cognition.collection.ScalarMap
Gets a java.util.Map that contains the same data as in this scalar map.
asMultiCollection(Collection<EntryType>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Takes a collection and returns a multi-collection version of that collection.
assertArgumentIsNode(SemanticLabel) - Method in class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLite
Asserts that the given argument is a node, throwing an IllegalArgumentException if it is not a node.
assertDimensionalitiesAllEqual(Iterable<? extends Vectorizable>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Asserts that all of the dimensionalities of the vectors in the given set of data are the same.
assertDimensionalitiesAllEqual(Iterable<? extends Vectorizable>, int) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
Asserts that all of the dimensionalities of the vectors in the given set of data equal the given dimensionality.
assertDimensionalityEquals(int) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
assertDimensionalityEquals(int) - Method in interface gov.sandia.cognition.math.matrix.Vector
Asserts that the dimensionality of this vector equals the given dimensionality.
assertEqualDimensionality(Vector, Vector) - Static method in class gov.sandia.cognition.math.matrix.AbstractVector
Throws a DimensionalityMismatchException if first.getDimensionality() != second.getDimensionality(), otherwise this function has no effect
assertInputDimensionalitiesAllEqual(Iterable<? extends InputOutputPair<? extends Vectorizable, ?>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Asserts that all of the dimensionalities of the input vectors in the given set of input-output pairs are the same.
assertInputDimensionalitiesAllEqual(Iterable<? extends InputOutputPair<? extends Vectorizable, ?>>, int) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Asserts that all of the dimensionalities of the input vectors in the given set of input-output pairs equal the given dimensionality.
assertIsInRangeExclusive(String, double, double, double) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts that the given argument is in the given range, exclusive.
assertIsInRangeInclusive(String, double, double, double) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts that the given argument is in the given range, inclusive.
assertIsNonNegative(String, int) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts that the given argument is non-negative (>=0.0).
assertIsNonNegative(String, long) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts that the given argument is non-negative (>=0.0).
assertIsNonNegative(String, double) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts that the given argument is non-negative (>=0.0).
assertIsNotNull(String, Object) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts that the given value is not null.
assertIsPositive(String, int) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts the given value is positive (> 0).
assertIsPositive(String, long) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts the given value is positive (> 0).
assertIsPositive(String, double) - Static method in class gov.sandia.cognition.util.ArgumentChecker
Asserts the given value is positive (> 0.0).
assertIsProbability(double) - Static method in class gov.sandia.cognition.math.ProbabilityUtil
Checks to make sure that probability is between 0.0 and 1.0.
assertSameDimensionality(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
assertSameDimensionality(Vector) - Method in interface gov.sandia.cognition.math.matrix.Vector
Asserts that this vector has the same dimensionality as the given vector.
assertSameDimensions(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
assertSameDimensions(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Throws a DimensionalityMismatchException if dimensions between this and otherMatrix aren't the same
assignCluster(int, int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Assigns example "i" to the new cluster index.
assignDataFromIndices() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Puts the data into a list of lists for each cluster to then estimate
assignDataToClusters(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Creates the cluster assignments given the current locations of clusters
assignDataToClusters(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer
 
assignments - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The assignments of each example to an exemplar (cluster).
assignments - Variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
The current assignments of elements to clusters.
assignments - Variable in class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.DPMMAssignments
List of assignment indices
assignmentTasks - Variable in class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel
Tasks that assign observations to clusters
assignObservationsToClusters(int, DirichletProcessMixtureModel.DPMMLogConditional) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Assigns observations to each of the K clusters, plus the as-yet-uncreated new cluster
assignObservationsToClusters(int, DirichletProcessMixtureModel.DPMMLogConditional) - Method in class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel
 
assignObservationToCluster(ObservationType, double[], DirichletProcessMixtureModel.DPMMLogConditional) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Probabilistically assigns an observation to a cluster
assignParameterMethods(Distribution<?>, String) - Method in class gov.sandia.cognition.statistics.DefaultDistributionParameter
Assigns the getter and setter from the given conditionalDistribution and parameter name.
asTerm() - Method in class gov.sandia.cognition.text.term.AbstractTerm
 
asTerm() - Method in class gov.sandia.cognition.text.term.DefaultIndexedTerm
 
asTerm() - Method in class gov.sandia.cognition.text.term.DefaultTermOccurrence
 
asTerm() - Method in interface gov.sandia.cognition.text.term.Termable
Get the term for the object.
asTerm() - Method in class gov.sandia.cognition.text.token.DefaultToken
 
asTerm() - Method in interface gov.sandia.cognition.text.token.Token
Tokens always are treated as DefaultTerm objects that contain the text of the Token.
asVectorCollection(Collection<? extends Vectorizable>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Takes a collection of Vectorizable objects and returns a collection of Vector objects of the same size.
AtanFunction - Class in gov.sandia.cognition.learning.function.scalar
Returns the element-wise arctangent of the input vector, compressed between -maxMagnitude and maxMagnitude (instead of just -PI/2 and PI/2)
AtanFunction() - Constructor for class gov.sandia.cognition.learning.function.scalar.AtanFunction
Creates a new instance of AtanFunction with the standard unit magnitude of -PI / 2 to PI / 2.
AtanFunction(double) - Constructor for class gov.sandia.cognition.learning.function.scalar.AtanFunction
Creates a new instance of AtanFunction.
AUTHOR_FIELD_NAME - Static variable in class gov.sandia.cognition.text.document.AbstractDocument
The name of the author field is "author".
AutoRegressiveMovingAverageFilter - Class in gov.sandia.cognition.math.signals
A type of filter using a moving-average calculation.
AutoRegressiveMovingAverageFilter(int, int) - Constructor for class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
Creates a new instance of AutoRegressiveMovingAverageFilter
AutoRegressiveMovingAverageFilter(double[], double[]) - Constructor for class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
Creates a new instance of AutoRegressiveMovingAverageFilter
AutoRegressiveMovingAverageFilter(Vector, Vector) - Constructor for class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
Creates a new instance of AutoRegressiveMovingAverageFilter
availabilities - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The array of example-example availabilities.
AveragingEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends Number>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An ensemble for regression functions that averages together the output value of each ensemble member to get the final output.
AveragingEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AveragingEnsemble
Creates a new, empty AdditiveEnsemble.
AveragingEnsemble(List<MemberType>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AveragingEnsemble
Creates a new AdditiveEnsemble with the given

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