- 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<java.lang.Double,java.lang.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.
- AbstractCategorizerOutOfBagStoppingCriteria<InputType,CategoryType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
-
Abstract class for implementing a out-of-bag stopping criteria for a
bagging-based ensemble.
- AbstractCategorizerOutOfBagStoppingCriteria() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
-
Creates a new OutOfBagErrorStoppingCriteria
.
- AbstractCategorizerOutOfBagStoppingCriteria(int) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
-
Creates a new OutOfBagErrorStoppingCriteria
with the given
smoothing window size.
- 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
.
- AbstractClosedFormIntegerDistribution - Class in gov.sandia.cognition.statistics
-
An abstract class for closed-form integer distributions.
- AbstractClosedFormIntegerDistribution() - Constructor for class gov.sandia.cognition.statistics.AbstractClosedFormIntegerDistribution
-
- AbstractClosedFormSmoothUnivariateDistribution - Class in gov.sandia.cognition.statistics
-
Partial implementation of SmoothUnivariateDistribution
- AbstractClosedFormSmoothUnivariateDistribution() - Constructor for class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution
-
- AbstractClosedFormUnivariateDistribution<NumberType extends java.lang.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
- AbstractCombinationsIterator(int, int) - Constructor for class gov.sandia.cognition.math.Combinations.AbstractCombinationsIterator
-
Creates a new instance of AbstractCombinationsIterator
- 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.
- AbstractDeltaCategorizer<CategoryType> - Class in gov.sandia.cognition.learning.algorithm.delta
-
The Burrows Delta algorithm is primarily used for authorship attribution, but
can be used for other applications.
- AbstractDeltaCategorizer(AbstractDeltaCategorizer.AbstractLearner<CategoryType>, ArrayList<Double>) - Constructor for class gov.sandia.cognition.learning.algorithm.delta.AbstractDeltaCategorizer
-
Constructor that takes a learner and featureStddev.
- AbstractDeltaCategorizer.AbstractLearner<CategoryType> - Class in gov.sandia.cognition.learning.algorithm.delta
-
Abstract learner for delta algorithms.
- 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 java.lang.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
.
- AbstractEnvelope() - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.AbstractEnvelope
-
Default constructor
- AbstractEuclideanRing<RingType extends EuclideanRing<RingType>> - Class in gov.sandia.cognition.math
-
- AbstractEuclideanRing() - Constructor for class gov.sandia.cognition.math.AbstractEuclideanRing
-
- AbstractFactorizationMachineLearner - Class in gov.sandia.cognition.learning.algorithm.factor.machine
-
- AbstractFactorizationMachineLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
-
- AbstractFactorizationMachineLearner(int, double, double, double, double, int, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
-
- 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
-
- 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
.
- AbstractHashFunction - Class in gov.sandia.cognition.hash
-
Partial implementation of HashFunction
- AbstractHashFunction() - Constructor for class gov.sandia.cognition.hash.AbstractHashFunction
-
Creates a new instance of AbstractHashFunction
- 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
- AbstractLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.delta.AbstractDeltaCategorizer.AbstractLearner
-
Default constructor.
- 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<java.lang.Double,java.lang.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<java.lang.Double,java.lang.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
.
- AbstractLogisticRegression<InputType,OutputType,FunctionType extends Evaluator<? super InputType,OutputType>> - Class in gov.sandia.cognition.learning.algorithm.regression
-
Abstract partial implementation for logistic regression classes.
- AbstractLogisticRegression(double, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
-
Creates a new instance of AbstractLogisticRegression
- AbstractLogNumberMap<KeyType> - Class in gov.sandia.cognition.collection
-
A partial implementation of a ScalarMap with a LogNumber value
- AbstractLogNumberMap(Map<KeyType, LogNumber>) - Constructor for class gov.sandia.cognition.collection.AbstractLogNumberMap
-
Creates a new instance of AbstractMutableDoubleMap
- AbstractLogNumberMap.SimpleEntry<KeyType> - Class in gov.sandia.cognition.collection
-
Entry for the AbstractScalarMap
- AbstractLogNumberMap.SimpleEntrySet<KeyType> - Class in gov.sandia.cognition.collection
-
Simple Entry Set for DefaultInfiniteVector
- AbstractLogNumberMap.SimpleIterator<KeyType> - Class in gov.sandia.cognition.collection
-
Simple iterator for DefaultInfiniteVector
- 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 java.lang.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
- 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.Entry<KeyType> - Interface in gov.sandia.cognition.collection
-
Interface for entries.
- AbstractMutableDoubleMap.SimpleEntry<KeyType> - Class in gov.sandia.cognition.collection
-
Entry for the AbstractScalarMap
- AbstractMutableDoubleMap.SimpleEntrySet<KeyType> - Class in gov.sandia.cognition.collection
-
Simple Entry Set for DefaultInfiniteVector
- AbstractMutableDoubleMap.SimpleIterator<KeyType> - Class in gov.sandia.cognition.collection
-
Simple iterator for DefaultInfiniteVector
- 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.
- 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,NumberType extends java.lang.Number> - Class in gov.sandia.cognition.collection
-
Partial implementation of ScalarMap
- AbstractScalarMap(Map<KeyType, NumberType>) - Constructor for class gov.sandia.cognition.collection.AbstractScalarMap
-
Creates a new instance of AbstractScalarMap
- 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
- AbstractSoftMargin() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin
-
Creates a new AbstractSoftMargin
with default parameters.
- AbstractSoftMargin(double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin
-
Creates a new AbstractSoftMargin
with the given
aggressiveness.
- AbstractSoftMargin(double, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin
-
Creates a new AbstractSoftMargin
with the given parameters.
- 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 java.lang.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
.
- AbstractVectorThresholdMaximumGainLearner(int, int[]) - 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.
- ActualPredictedPairSummarizer() - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer
-
Creates a new CombineSummarizer
.
- ActualPredictedPairSummarizer() - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.ActualPredictedPairSummarizer
-
Creates a new CombineSummarizer
.
- 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.LineSegment - Class in gov.sandia.cognition.statistics.bayesian
-
A line that has a minimum and maximum support (x-axis) value.
- AdaptiveRejectionSampling.LogEvaluator<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> - Class in gov.sandia.cognition.statistics.bayesian
-
Wraps an Evaluator and takes the natural logarithm of the evaluate method
- AdaptiveRejectionSampling.LowerEnvelope - Class in gov.sandia.cognition.statistics.bayesian
-
Define the lower envelope for Adaptive Rejection Sampling
- AdaptiveRejectionSampling.PDFLogEvaluator - Class in gov.sandia.cognition.statistics.bayesian
-
Wraps a PDF so that it returns the logEvaluate method.
- AdaptiveRejectionSampling.Point - Class in gov.sandia.cognition.statistics.bayesian
-
An InputOutputPair that has a natural ordering according to their
input (x-axis) values.
- AdaptiveRejectionSampling.UpperEnvelope - Class in gov.sandia.cognition.statistics.bayesian
-
Constructs the upper envelope for sampling.
- add(ValueType) - Method in class gov.sandia.cognition.collection.DefaultIndexer
-
- add(double) - Method in class gov.sandia.cognition.collection.DoubleArrayList
-
Adds element to the end of the vector (allocating more space as needed
- 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(int) - Method in class gov.sandia.cognition.collection.IntArrayList
-
Adds element to the end of the vector (allocating more space as needed
- 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(NormalizedCentroidCluster<Vectorizable>, Vectorizable) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.NormalizedCentroidClusterCreator
-
- 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.
- addDocumentTermOccurrences(DocIdType, Set<TermType>) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
-
Adds the input document with all of the input terms in the data.
- addDocumentTermWeights(DocIdType, Map<TermType, Double>) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
-
Adds the input document with all of the input terms with their input
scores (should be greater than 0) to the data.
- addEdge(NodeNameType, NodeNameType) - Method in class gov.sandia.cognition.graph.DenseMemoryGraph
-
- addEdge(NodeNameType, NodeNameType) - Method in interface gov.sandia.cognition.graph.DirectedNodeEdgeGraph
-
Adds a directed edge from left to right.
- addEdge(NodeNameType, NodeNameType) - Method in interface gov.sandia.cognition.graph.DirectedWeightedNodeEdgeGraph
-
Adds a directed edge from left to right.
- addEdge(NodeNameType, NodeNameType, double) - Method in interface gov.sandia.cognition.graph.DirectedWeightedNodeEdgeGraph
-
Adds a directed edge from left to right with the input weight.
- addEdge(NodeNameType, NodeNameType) - Method in class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
-
- addEdge(NodeNameType, NodeNameType, double) - Method in class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
-
- 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.
- addIterativeAlgorithmListener(IterativeAlgorithmListener) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
- AdditiveEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends java.lang.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.
- addNode(NodeNameType) - Method in class gov.sandia.cognition.graph.DenseMemoryGraph
-
- addNode(NodeNameType) - Method in interface gov.sandia.cognition.graph.DirectedNodeEdgeGraph
-
Adds the input node to the graph.
- 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
- addRelationship(int, int, int, int, double) - Method in class gov.sandia.cognition.learning.algorithm.semisupervised.valence.MultipartiteValenceMatrix
-
Adds a relationship between the two indexed elements.
- 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.
- addWeightedDocument(DocIdType, double) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
-
Adds the input documentId with its associated score.
- addWeightedDocument(DocIdType, double, double) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
-
Adds the input documentId with its associated score/trust.
- addWeightedTerm(TermType, double) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
-
Adds the input term with its associated score.
- addWeightedTerm(TermType, double, double) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
-
Adds the input term with its associated score and trust level.
- 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
distance between clusters to allow when merging.
- 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.
- 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.AbstractCategorizerOutOfBagStoppingCriteria
-
- algorithmEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner.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.AbstractCategorizerOutOfBagStoppingCriteria
-
- algorithmStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner.OutOfBagErrorStoppingCriteria
-
- 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
- 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.
- AnytimeBatchLearnerValidationPerformanceReporter<DataType,ObjectType> - Class in gov.sandia.cognition.learning.performance
-
A performance reporter for a validation set.
- AnytimeBatchLearnerValidationPerformanceReporter(PerformanceEvaluator<? super ObjectType, ? super DataType, ?>, DataType) - Constructor for class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
-
Creates a new AnytimeBatchLearnerValidationPerformanceReporter
that
reports to the given print stream using the default format.
- AnytimeBatchLearnerValidationPerformanceReporter(PerformanceEvaluator<? super ObjectType, ? super DataType, ?>, DataType, PrintStream) - Constructor for class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
-
Creates a new AnytimeBatchLearnerValidationPerformanceReporter
that
reports to the given print stream using the default format.
- AnytimeBatchLearnerValidationPerformanceReporter(PerformanceEvaluator<? super ObjectType, ? super DataType, ?>, DataType, String) - Constructor for class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
-
Creates a new AnytimeBatchLearnerValidationPerformanceReporter
that
reports to System.out and the given format.
- AnytimeBatchLearnerValidationPerformanceReporter(PerformanceEvaluator<? super ObjectType, ? super DataType, ?>, DataType, PrintStream, String) - Constructor for class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
-
Creates a new AnytimeBatchLearnerValidationPerformanceReporter
that
reports to the given print stream and format.
- 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
-
- APStat() - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.APStat
-
- 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.
- assertMultiplicationDimensions(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
-
- assertMultiplicationDimensions(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Checks to see if the dimensions are appropriate for:
this.times(postMultiplicationMatrix)
.
- 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
- AssignDataToCluster(Collection<DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer.AssignDataToCluster
-
Creates a new instance of AssignDataToCluster
- 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 Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
-
- 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 java.lang.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