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

P

P - Variable in class gov.sandia.cognition.math.matrix.custom.DenseMatrix.LU

The 0-based list of row swaps used in the factorization.

p - Variable in class gov.sandia.cognition.statistics.distribution.GeometricDistribution

Probability of a positive outcome (Bernoulli probability), [0,1]

p - Variable in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution

Probability of a positive outcome (Bernoulli probability), [0,1]

Pair<FirstType,SecondType> - Interface in gov.sandia.cognition.util

The Pair interface defines the functionality of an object that contains a pair of other objects inside of it.

PairFirstVectorizableIndexComparator(int) - Constructor for class gov.sandia.cognition.math.geometry.KDTree.PairFirstVectorizableIndexComparator

Creates a new instance of PairFirstVectorizableIndexComparator

pairwiseTest - Variable in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison

Confidence test used for pair-wise null-hypothesis tests.

pairwiseTestStatistics - Variable in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic

Results from the pair-wise confidence tests.

ParallelAlgorithm - Interface in gov.sandia.cognition.algorithm

Interface for algorithms that are parallelized using multithreading.

ParallelBaumWelchAlgorithm<ObservationType> - Class in gov.sandia.cognition.learning.algorithm.hmm

A Parallelized implementation of some of the methods of the Baum-Welch Algorithm.

ParallelBaumWelchAlgorithm() - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm

Default constructor

ParallelBaumWelchAlgorithm(HiddenMarkovModel<ObservationType>, BatchLearner<Collection<? extends WeightedValue<? extends ObservationType>>, ? extends ComputableDistribution<ObservationType>>, boolean) - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm

Creates a new instance of ParallelBaumWelchAlgorithm

ParallelBaumWelchAlgorithm.DistributionEstimatorTask<ObservationType> - Class in gov.sandia.cognition.learning.algorithm.hmm

Re-estimates the PDF from the gammas.

ParallelClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.function.cost

A parallel implementation of ClusterDistortionMeasure.

ParallelClusterDistortionMeasure() - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelClusterDistortionMeasure

Creates a new instance of ParallelClusterDistortionMeasure

ParallelClusterDistortionMeasure(ClusterDivergenceFunction<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelClusterDistortionMeasure

Creates a new instance of ClusterDistortionMeasure

ParallelDirichletProcessMixtureModel<ObservationType> - Class in gov.sandia.cognition.statistics.bayesian

A Parallelized version of vanilla Dirichlet Process Mixture Model learning.

ParallelDirichletProcessMixtureModel() - Constructor for class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel

Creates a new instance of ParallelDirichletProcessMixtureModel

ParallelDirichletProcessMixtureModel.ClusterUpdaterTask - Class in gov.sandia.cognition.statistics.bayesian

Tasks that update the values of the clusters for Gibbs sampling

ParallelDirichletProcessMixtureModel.DPMMAssignments - Class in gov.sandia.cognition.statistics.bayesian

Assignments from the DPMM

ParallelDirichletProcessMixtureModel.ObservationAssignmentTask - Class in gov.sandia.cognition.statistics.bayesian

Task that assign observations to cluster indices

ParallelHiddenMarkovModel<ObservationType> - Class in gov.sandia.cognition.learning.algorithm.hmm

A Hidden Markov Model with parallelized processing.

ParallelHiddenMarkovModel() - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel

Creates a new instance of ParallelHiddenMarkovModel

ParallelHiddenMarkovModel(int) - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel

Creates a new instance of ParallelHiddenMarkovModel

ParallelHiddenMarkovModel(Vector, Matrix, Collection<? extends ComputableDistribution<ObservationType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel

Creates a new instance of ParallelHiddenMarkovModel

ParallelHiddenMarkovModel(HiddenMarkovModel<ObservationType>) - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel

\ Creates a new ParallelHiddenMarkovModel from another HiddenMarkovModel.

ParallelHiddenMarkovModel.ComputeTransitionsTask - Class in gov.sandia.cognition.learning.algorithm.hmm

Calls the computeTransitions method.

ParallelHiddenMarkovModel.LogLikelihoodTask - Class in gov.sandia.cognition.learning.algorithm.hmm

Computes the log-likelihood of a particular data sequence

ParallelHiddenMarkovModel.NormalizeTransitionTask - Class in gov.sandia.cognition.learning.algorithm.hmm

Calls the normalizeTransitionMatrix method.

ParallelHiddenMarkovModel.ObservationLikelihoodTask<ObservationType> - Class in gov.sandia.cognition.learning.algorithm.hmm

Calls the computeObservationLikelihoods() method.

ParallelHiddenMarkovModel.StateObservationLikelihoodTask - Class in gov.sandia.cognition.learning.algorithm.hmm

Calls the computeStateObservationLikelihood() method.

ParallelHiddenMarkovModel.ViterbiTask - Class in gov.sandia.cognition.learning.algorithm.hmm

Computes the most-likely "from state" for the given "destination state" and the given deltas.

ParallelizableCostFunction - Interface in gov.sandia.cognition.learning.function.cost

Interface describing a cost function that can (largely) be computed in parallel.

ParallelizedCostFunctionContainer - Class in gov.sandia.cognition.learning.function.cost

A cost function that automatically splits a ParallelizableCostFunction across multiple cores/processors to speed up computation.

ParallelizedCostFunctionContainer() - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer

Default constructor for ParallelizedCostFunctionContainer.

ParallelizedCostFunctionContainer(ParallelizableCostFunction) - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer

Creates a new instance of ParallelizedCostFunctionContainer

ParallelizedCostFunctionContainer(ParallelizableCostFunction, ThreadPoolExecutor) - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer

Creates a new instance of ParallelizedCostFunctionContainer

ParallelizedCostFunctionContainer.SubCostEvaluate - Class in gov.sandia.cognition.learning.function.cost

Callable task for the evaluate() method.

ParallelizedCostFunctionContainer.SubCostGradient - Class in gov.sandia.cognition.learning.function.cost

Callable task for the computeGradient() method

ParallelizedGeneticAlgorithm<CostParametersType,GenomeType> - Class in gov.sandia.cognition.learning.algorithm.genetic

This is a parallel implementation of the genetic algorithm.

ParallelizedGeneticAlgorithm() - Constructor for class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm

Default constructor

ParallelizedGeneticAlgorithm(Collection<GenomeType>, Reproducer<GenomeType>, CostFunction<? super GenomeType, ? super CostParametersType>, ThreadPoolExecutor) - Constructor for class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm

ParallelizedGeneticAlgorithm(Collection<GenomeType>, Reproducer<GenomeType>, CostFunction<? super GenomeType, ? super CostParametersType>, ThreadPoolExecutor, int, int) - Constructor for class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm

ParallelizedGeneticAlgorithm.EvaluateGenome - Class in gov.sandia.cognition.learning.algorithm.genetic

Callable task for the evaluate() method.

ParallelizedKMeansClusterer<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering

This is a parallel implementation of the k-means clustering algorithm.

ParallelizedKMeansClusterer() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer

Default constructor

ParallelizedKMeansClusterer(int, int, ThreadPoolExecutor, FixedClusterInitializer<ClusterType, DataType>, ClusterDivergenceFunction<? super ClusterType, ? super DataType>, ClusterCreator<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer

Creates a new instance of ParallelizedKMeansClusterer2

ParallelizedKMeansClusterer.AssignDataToCluster - Class in gov.sandia.cognition.learning.algorithm.clustering

Callable task for the evaluate() method.

ParallelizedKMeansClusterer.CreateClustersFromAssignments - Class in gov.sandia.cognition.learning.algorithm.clustering

Callable task for that creates clusters from assigned data

ParallelLatentDirichletAllocationVectorGibbsSampler - Class in gov.sandia.cognition.text.topic

A parallel implementation of LatentDirichletAllocationVectorGibbsSampler.

ParallelLatentDirichletAllocationVectorGibbsSampler() - Constructor for class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler

Creates a new ParallelLatentDirichletAllocationVectorGibbsSampler with default parameters.

ParallelLatentDirichletAllocationVectorGibbsSampler(int, double, double, int, int, int, Random) - Constructor for class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler

Creates a new ParallelLatentDirichletAllocationVectorGibbsSampler with the given parameters.

ParallelLatentDirichletAllocationVectorGibbsSampler.DocumentSampleTask - Class in gov.sandia.cognition.text.topic

A document sampling task

ParallelLearnerValidationExperiment<InputDataType,FoldDataType,LearnedType,StatisticType,SummaryType> - Class in gov.sandia.cognition.learning.experiment

Parallel version of the LearnerValidationExperiment class that executes the validations experiments across available cores and hyperthreads.

ParallelLearnerValidationExperiment() - Constructor for class gov.sandia.cognition.learning.experiment.ParallelLearnerValidationExperiment

Default constructor

ParallelLearnerValidationExperiment(ValidationFoldCreator<InputDataType, FoldDataType>, PerformanceEvaluator<? super LearnedType, ? super Collection<? extends FoldDataType>, ? extends StatisticType>, Summarizer<? super StatisticType, ? extends SummaryType>) - Constructor for class gov.sandia.cognition.learning.experiment.ParallelLearnerValidationExperiment

Creates a new instance of ParallelLearnerValidationExperiment.

ParallelNegativeLogLikelihood<DataType> - Class in gov.sandia.cognition.learning.function.cost

Parallel implementation of the NegativeLogLikleihood cost function

ParallelNegativeLogLikelihood() - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelNegativeLogLikelihood

Default constructor

ParallelNegativeLogLikelihood(Collection<? extends DataType>) - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelNegativeLogLikelihood

Creates a new instance of ParallelNegativeLogLikelihood

ParallelNegativeLogLikelihood.NegativeLogLikelihoodTask<DataType> - Class in gov.sandia.cognition.learning.function.cost

Task for computing partial log likelihoods

ParallelSparseMatrix - Class in gov.sandia.cognition.math.matrix.custom

A sparse matrix implementation.

ParallelSparseMatrix(int, int, int) - Constructor for class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix

Creates a new parallel sparse matrix with the specified number of rows and columns.

ParallelSparseMatrix(ParallelSparseMatrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix

Creates a new sparse matrix with the same dimensions and data as m (performs a deep copy).

ParallelSparseMatrix(SparseMatrix, int) - Constructor for class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix

Creates a new sparse matrix with the same dimensions and data as m (performs a deep copy).

ParallelSparseMatrix(DenseMatrix, int) - Constructor for class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix

Creates a new sparse matrix with the same dimensions and data as d (performs a deep copy).

ParallelSparseMatrix(DiagonalMatrix, int) - Constructor for class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix

Creates a new sparse matrix with the same dimensions and data as d (performs a deep copy).

ParallelSparseMatrix() - Constructor for class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix

This should never be called by anything or anyone other than Java's serialization code.

ParallelUtil - Class in gov.sandia.cognition.algorithm

Utility methods for creating parallel algorithms.

ParallelUtil() - Constructor for class gov.sandia.cognition.algorithm.ParallelUtil

Protected constructor since this is a utility class.

parameter - Variable in class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator

Bayesian hyperparameter relationship between the conditional distribution and the conjugate prior distribution.

Parameter(BernoulliDistribution, BetaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator.Parameter

Creates a new instance

Parameter(BinomialDistribution, BetaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator.Parameter

Creates a new instance of Parameter

Parameter(ExponentialDistribution, GammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator.Parameter

Creates a new instance of Parameter

Parameter(GammaDistribution, GammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator.Parameter

Creates a new instance of Parameter

Parameter(MultinomialDistribution, DirichletDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator.Parameter

Creates a new instance

Parameter(MultivariateGaussian, MultivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator.Parameter

Creates a new instance

Parameter(MultivariateGaussian, NormalInverseWishartDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator.Parameter

Creates a new instance

Parameter(PoissonDistribution, GammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator.Parameter

Creates a new instance

Parameter(UniformDistribution, ParetoDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator.Parameter

Creates a new instance

Parameter(UnivariateGaussian, UnivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator.Parameter

Creates a new instance

Parameter(UnivariateGaussian, NormalInverseGammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator.Parameter

Creates a new instance

ParameterAdaptable<ObjectType,DataType> - Interface in gov.sandia.cognition.learning.parameter

Interface for an object that allows parameter adapters to be attached to it.

ParameterAdaptableBatchLearnerWrapper<DataType,ResultType,LearnerType extends BatchLearner<? super DataType,? extends ResultType>> - Class in gov.sandia.cognition.learning.parameter

A wrapper for adding parameter adapters to a batch learner.

ParameterAdaptableBatchLearnerWrapper() - Constructor for class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper

Creates a new ParameterAdaptableBatchLearnerWrapper.

ParameterAdaptableBatchLearnerWrapper(LearnerType) - Constructor for class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper

Creates a new ParameterAdaptableBatchLearnerWrapper.

ParameterAdapter<ObjectType,DataType> - Interface in gov.sandia.cognition.learning.parameter

Interface for an object that can adapt the parameters of another object based on some given data.

parameterAdapters - Variable in class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper

The list of parameter adapters for the learner.

parameterCost - Variable in class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction.Cache

Cost-function value of the parameter set

ParameterCostEvaluatorDerivativeBased(GradientDescendable, DifferentiableCostFunction) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased

Creates a new instance of ParameterCostEvaluatorDerivativeBased

ParameterCostEvaluatorDerivativeFree(VectorizableVectorFunction, SupervisedCostFunction<Vector, Vector>) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree

Creates a new instance of ParameterCostEvaluatorDerivativeFree

ParameterCostMinimizer<ResultType extends VectorizableVectorFunction> - Interface in gov.sandia.cognition.learning.algorithm.regression

A anytime algorithm that is used to estimate the locally minimum-cost parameters of an object.

ParameterDerivativeFreeCostMinimizer - Class in gov.sandia.cognition.learning.algorithm.regression

Implementation of a class of objects that uses a derivative-free minimization algorithm.

ParameterDerivativeFreeCostMinimizer() - Constructor for class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer

Creates a new instance of ParameterDerivativeFreeCostMinimizer

ParameterDerivativeFreeCostMinimizer(FunctionMinimizer<Vector, Double, ? super DifferentiableEvaluator<Vector, Double, Vector>>) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer

Creates a new instance of ParameterDerivativeFreeCostMinimizer

ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree - Class in gov.sandia.cognition.learning.algorithm.regression

Function that maps the parameters of an object to its inputs, so that minimization algorithms can tune the parameters of an object against a cost function.

ParameterDifferentiableCostMinimizer - Class in gov.sandia.cognition.learning.algorithm.regression

This class adapts the unconstrained nonlinear minimization algorithms in the "minimization" package to the task of estimating locally optimal (minimum-cost) parameter sets.

ParameterDifferentiableCostMinimizer() - Constructor for class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer

Creates a new instance of ParameterDifferentiableCostMinimizer

ParameterDifferentiableCostMinimizer(FunctionMinimizer<Vector, Double, ? super DifferentiableEvaluator<Vector, Double, Vector>>) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer

Creates a new instance of ParameterDerivativeFreeCostMinimizer

ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased - Class in gov.sandia.cognition.learning.algorithm.regression

Function that maps the parameters of an object to its inputs, so that minimization algorithms can tune the parameters of an object against a cost function.

parameterGetter - Variable in class gov.sandia.cognition.statistics.DefaultDistributionParameter

Getter for the parameter, the write method.

ParameterGradientEvaluator<InputType,OutputType,GradientType> - Interface in gov.sandia.cognition.learning.algorithm.gradient

Interface for computing the derivative of the output with respect to the parameters for a given input.

parameters - Variable in class gov.sandia.cognition.factory.ConstructorBasedFactory

The parameters to pass to the constructor.

parameters - Variable in class gov.sandia.cognition.statistics.distribution.CategoricalDistribution

Parameters of the multinomial distribution, must be at least 2-dimensional and each element must be nonnegative.

parameters - Variable in class gov.sandia.cognition.statistics.distribution.DirichletDistribution

Parameters of the Dirichlet distribution, must be at least 2-dimensional and each element must be positive.

parameters - Variable in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution

Parameters of the Dirichlet distribution, must be at least 2-dimensional and each element must be positive.

parameterSetter - Variable in class gov.sandia.cognition.statistics.DefaultDistributionParameter

Setter for the parameter, the read method.

parent - Variable in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode

The parent node of this node.

parent - Variable in class gov.sandia.cognition.math.geometry.KDTree

Parent of this node of the subtree.

parent - Variable in class gov.sandia.cognition.math.geometry.Quadtree.Node

The parent of this node in the tree.

ParetoDistribution - Class in gov.sandia.cognition.statistics.distribution

This class describes the Pareto distribution, sometimes called the Bradford Distribution.

ParetoDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution

Creates a new instance of ParetoDistribution

ParetoDistribution(double, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution

Creates a new instance of ParetoDistribution

ParetoDistribution(ParetoDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution

Copy constructor

ParetoDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution

CDF of the Pareto Distribution.

ParetoDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution

PDF of the ParetoDistribution

parse(BufferedReader) - Method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler

The main parsing function.

parseCSVToModelFactory(String, boolean) - Static method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler

Reads a default CognitiveModuleFactory from the given file and puts it in a default CognitiveModelFactory.

parseCSVToModelFactory(BufferedReader, boolean) - Static method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler

Reads a default CognitiveModuleFactory from the given buffered reader and puts it in a default CognitiveModelFactory.

parseCSVToModuleFactory(String, boolean) - Static method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler

Reads a default CognitiveModuleFactory from the given CSV file and returns it.

parseCSVToModuleFactory(BufferedReader, boolean) - Static method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler

Reads a default CognitiveModuleFactory from the given buffered reader and then returns it.

parseHeader(BufferedReader) - Method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler

Parses the header and returns the version number.

parseVector(Collection<String>) - Static method in class gov.sandia.cognition.math.matrix.VectorReader

Parses a Vector from the given list of element tokens.

partialSum - Variable in class gov.sandia.cognition.statistics.TransferEntropy.TransferEntropyPartialSumObject

The partial sum.

ParticleFilter<ObservationType,ParameterType> - Interface in gov.sandia.cognition.statistics.bayesian

A particle filter aims to estimate a sequence of hidden parameters based on observed data using point-mass estimates of the posterior distribution.

ParticleFilter.Updater<ObservationType,ParameterType> - Interface in gov.sandia.cognition.statistics.bayesian

Updates the particles.

particlePctThreadhold - Variable in class gov.sandia.cognition.statistics.bayesian.SamplingImportanceResamplingParticleFilter

Percentage of effective particles, below which we resample.

PartitionalClusterer<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering

The PartitionalClusterer implements a partitional clustering algorithm, which is a type of hierarchical clustering algorithm.

PartitionalClusterer(int, ClusterDivergenceFunction<ClusterType, DataType>, IncrementalClusterCreator<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer

Creates a new partitional clusterer.

PartitionalClusterer(int, WithinClusterDivergence<ClusterType, DataType>, IncrementalClusterCreator<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer

Creates a new partitional clusterer.

PartitionedDataset<DataType> - Interface in gov.sandia.cognition.learning.data

Interface for a dataset partitioned into training and testing sets.

partitioner - Variable in class gov.sandia.cognition.learning.experiment.RandomFoldCreator

The partitioner used for each fold.

PatternRecognizerLite - Interface in gov.sandia.cognition.framework.lite

The PatternRecognizerLite interface defines the functionality needed by a pattern recognizer that is to be used by a SemanticMemoryLite.

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.BetaDistribution.PDF

Default constructor.

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaDistribution.PDF

Creates a new PDF

PDF(BetaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution.PDF

Creates a new instance of CauchyDistribution

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution.PDF

Creates a new instance of CauchyDistribution

PDF(CauchyDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.PDF

Default constructor.

PDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.PDF

Creates a new instance of ChiSquareDistribution

PDF(ChiSquareDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.DirichletDistribution.PDF

Default constructor.

PDF(Vector) - Constructor for class gov.sandia.cognition.statistics.distribution.DirichletDistribution.PDF

Creates a new instance of PDF

PDF(DirichletDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.DirichletDistribution.PDF

Copy Constructor.

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.PDF

Default constructor.

PDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.PDF

Creates a new instance of PDF

PDF(ExponentialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.GammaDistribution.PDF

Default constructor.

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.GammaDistribution.PDF

Creates a new instance of PDF

PDF(GammaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.GammaDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.PDF

Default constructor

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.PDF

Creates a new instance of InverseGammaDistribution

PDF(InverseGammaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution.PDF

Creates a new instance of InverseWishartDistribution

PDF(Matrix, int) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution.PDF

Creates a new instance of InverseWishartDistribution

PDF(InverseWishartDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution.PDF

Copy constructor.

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.PDF

Creates a new instance of LaplaceDistribution.PDF

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.PDF

Creates a new instance of LaplaceDistribution.PDF

PDF(LaplaceDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.PDF

Copy Constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.LogisticDistribution.PDF

Default constructor

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.LogisticDistribution.PDF

Creates a new instance of PDF

PDF(LogisticDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.LogisticDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.PDF

Default constructor.

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.PDF

Creates a new instance of LogNormalDistribution

PDF(LogNormalDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.PDF

Copy Constructor

PDF(MultivariateGaussian...) - Constructor for class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.PDF

Creates a new instance of MixtureOfGaussians

PDF(Collection<? extends MultivariateGaussian>) - Constructor for class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.PDF

Creates a new instance of MixtureOfGaussians

PDF(Collection<? extends MultivariateGaussian>, double[]) - Constructor for class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.PDF

Creates a new instance of LinearMixtureModel

PDF(MixtureOfGaussians.PDF) - Constructor for class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.PDF

Copy Constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.PDF

Default constructor.

PDF(int) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.PDF

Creates a new instance of MultivariateGaussian.

PDF(Vector, Matrix) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.PDF

Creates a new instance of MultivariateGaussian.

PDF(MultivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.PDF

Creates a new instance of MultivariateGaussian.

PDF(Collection<? extends DistributionType>) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel.PDF

Creates a new instance of MultivariateMixtureDensityModel

PDF(Collection<? extends DistributionType>, double[]) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel.PDF

Creates a new instance of MultivariateMixtureDensityModel

PDF(MultivariateMixtureDensityModel<? extends DistributionType>) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel.PDF

Copy Constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution.PDF

Creates a new instance of MultivariateStudentTDistribution

PDF(int) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution.PDF

Creates a distribution with the given dimensionality.

PDF(double, Vector, Matrix) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution.PDF

Creates a distribution with the given dimensionality.

PDF(MultivariateStudentTDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution.PDF

Creates a new instance of NormalInverseGammaDistribution

PDF(double, double, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution.PDF

Creates a new instance of NormalInverseGammaDistribution

PDF(NormalInverseGammaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution.PDF

Default constructor

PDF(int, double) - Constructor for class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution.PDF

Creates a new instance of NormalInverseWishartDistribution

PDF(MultivariateGaussian, InverseWishartDistribution, double) - Constructor for class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution.PDF

Creates a new instance of NormalInverseWishartDistribution

PDF(NormalInverseWishartDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution.PDF

Creates a new instance of PDF

PDF(double, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution.PDF

Creates a new instance of PDF

PDF(ParetoDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.PDF

Creates a new instance of ScalarMixtureDensityModel

PDF(SmoothUnivariateDistribution...) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.PDF

Creates a new instance of ScalarMixtureDensityModel

PDF(Collection<? extends SmoothUnivariateDistribution>) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.PDF

Creates a new instance of ScalarMixtureDensityModel

PDF(Collection<? extends SmoothUnivariateDistribution>, double[]) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.PDF

Creates a new instance of ScalarMixtureDensityModel

PDF(ScalarMixtureDensityModel) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.PDF

Default constructor.

PDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.PDF

Creates a new instance of PDF

PDF(double, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.PDF

Creates a new instance of PDF

PDF(StudentTDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.PDF

Creates a new instance of PDF

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.UniformDistribution.PDF

Creates a new instance of PDF

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformDistribution.PDF

Creates a new instance of PDF

PDF(UniformDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformDistribution.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.PDF

Creates a new instance of UnivariateGaussian with zero mean and unit variance

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.PDF

Creates a new instance of UnivariateGaussian

PDF(UnivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.PDF

Copy constructor

PDF() - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution.PDF

Creates a new instance of WeibullDistribution

PDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution.PDF

Creates a new instance of WeibullDistribution

PDF(WeibullDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution.PDF

Copy constructor

PDFLogEvaluator(ProbabilityFunction<Double>) - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.PDFLogEvaluator

Creates a new instance of PDFLogEvaluator

percentToSample - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner

The percentage of the data to sample with replacement on each iteration.

percentToSample - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner

The percent to sample on each iteration.

percentToSample - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner

The percentage of the data to sample for each ensemble member.

percentToSample - Variable in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner

The percentage of the dimensionality to sample.

Perceptron - Class in gov.sandia.cognition.learning.algorithm.perceptron

The Perceptron class implements the standard Perceptron learning algorithm that learns a binary classifier based on vector input.

Perceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron

Creates a new instance of Perceptron.

Perceptron(int) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron

Creates a new instance of Perceptron with the given maximum number of iterations.

Perceptron(int, double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron

Creates a new instance of Perceptron with the given parameters

Perceptron(int, double, double, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron

Creates a new instance of Perceptron with the given parameters

PERFORMANCE_DESCRIPTION - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering

Description of the performance value returned, "Number of Clusters".

PERFORMANCE_NAME - Static variable in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm

Name of the performance statistic, "Log Likelihood".

PERFORMANCE_NAME - Static variable in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm

The performance name is "Change".

PERFORMANCE_NAME - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization

The performance name is "Change count".

PERFORMANCE_NAME - Static variable in class gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm

Performance statistic name, "Current Log Likelihood".

PERFORMANCE_NAME - Static variable in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner

Name of the performance measurement, "Assignment Change".

PERFORMANCE_NAME - Static variable in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner

Name of the performance measurement, "Assignment Change".

performanceEvaluator - Variable in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment

The evaluator to use to compute the performance of the learned object on each fold.

performanceEvaluator - Variable in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment

The evaluator to use to compute the performance of the learned object on each fold.

performanceEvaluator - Variable in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment

The evaluator to use to compute the performance of the learned object on each fold.

performanceEvaluator - Variable in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment

The evaluator to use to compute the performance of the learned object on each fold.

performanceEvaluator - Variable in class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter

The performance evaluator.

PerformanceEvaluator() - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.PerformanceEvaluator

Creates a new PerformanceEvaluator.

PerformanceEvaluator<ObjectType,DataType,ResultType> - Interface in gov.sandia.cognition.learning.performance

The PerformanceEvaluator class defines the functionality of some object with regards to some data.

Permanence<NodeNameType> - Class in gov.sandia.cognition.graph.community

Permanence(DirectedNodeEdgeGraph<NodeNameType>, int, double) - Constructor for class gov.sandia.cognition.graph.community.Permanence

Initialize the class with the input graph and parameters

permanence() - Method in class gov.sandia.cognition.graph.community.Permanence

Returns the permanence discovered by running solveCommunities.

Permutation - Class in gov.sandia.cognition.math

The Permutation class contains methods for dealing with permutations of object sets.

Permutation() - Constructor for class gov.sandia.cognition.math.Permutation

Creates a new instance of Permutation

PersonalizedPageRank<NodeNameType> - Class in gov.sandia.cognition.graph.community

This class can compute PersonalizedPageRank for the input graph and a specified node, and also can determine a community for any specified node.

PersonalizedPageRank(DirectedNodeEdgeGraph<NodeNameType>) - Constructor for class gov.sandia.cognition.graph.community.PersonalizedPageRank

Initializes all of the internal data-structures for the input graph.

PersonalizedPageRank(DirectedNodeEdgeGraph<NodeNameType>, double) - Constructor for class gov.sandia.cognition.graph.community.PersonalizedPageRank

Initializes all of the internal data-structures for the input graph.

perturb(PerturbedType) - Method in interface gov.sandia.cognition.learning.algorithm.annealing.Perturber

Perturbs the given object and returns the perturbed version.

perturb(Vectorizable) - Method in class gov.sandia.cognition.learning.algorithm.annealing.VectorizablePerturber

Perturbs the given Vectorizable by cloning it and then operating on the clone by side-effect.

Perturber<PerturbedType> - Interface in gov.sandia.cognition.learning.algorithm.annealing

The Perturber interface defines the functionality of an object that can take an object and perturb it, returning the perturbed value.

perturbVector(Vector) - Method in class gov.sandia.cognition.learning.algorithm.annealing.VectorizablePerturber

Perturbs the given vector using the underlying random number generator.

phi - Variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation

Phi is the standard score computed from the confidence.

phi - Variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance

Phi is the standard score computed from the confidence.

PI2 - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian

PI times 2.0, 6.283185307179586

PIDController - Class in gov.sandia.cognition.math.signals

This class defines a Proportional-plus-Integral-plus-Derivative set-point controller.

PIDController() - Constructor for class gov.sandia.cognition.math.signals.PIDController

Creates a new instance of PIDController

PIDController(double, double, double) - Constructor for class gov.sandia.cognition.math.signals.PIDController

Creates a new instance of PIDController.

PIDController(double, double, double, double) - Constructor for class gov.sandia.cognition.math.signals.PIDController

Creates a new instance of PIDController.

PIDController.State - Class in gov.sandia.cognition.math.signals

State of a PIDController

plus(RingType) - Method in class gov.sandia.cognition.math.AbstractRing

plus(LogNumber) - Method in class gov.sandia.cognition.math.LogNumber

plus(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector

plus(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector

plus(MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble

plus(MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger

plus(MutableLong) - Method in class gov.sandia.cognition.math.MutableLong

plus(RingType) - Method in interface gov.sandia.cognition.math.Ring

Arithmetic addition of this and other

plus(UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber

plus(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian

Adds two MultivariateGaussian random variables together and returns the resulting MultivariateGaussian

plus(UnivariateGaussian.SufficientStatistic) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic

Adds this set of sufficient statistics to another and returns the combined sufficient statistics.

plus(Duration) - Method in class gov.sandia.cognition.time.DefaultDuration

plus(Duration) - Method in interface gov.sandia.cognition.time.Duration

Adds this duration to the given duration and returns the sum.

plusEquals(int, double) - Method in class gov.sandia.cognition.collection.DoubleArrayList

Adds val to the element at idx

plusEquals(int, int) - Method in class gov.sandia.cognition.collection.IntArrayList

Adds val to the element at idx

plusEquals(ComplexNumber) - Method in class gov.sandia.cognition.math.ComplexNumber

Inline addition between this and the complex number

plusEquals(LogNumber) - Method in class gov.sandia.cognition.math.LogNumber

plusEquals(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix

plusEquals(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector

plusEquals(SparseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix

plusEquals(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix

plusEquals(DiagonalMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix

plusEquals(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector

plusEquals(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector

plusEquals(SparseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix

Type-specific version of plusEquals for combining whatever type this is with the input sparse matrix.

plusEquals(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix

Type-specific version of plusEquals for combining whatever type this is with the input dense matrix.

plusEquals(DiagonalMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix

plusEquals(SparseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix

Type-specific version of plusEquals for combining whatever type this is with the input sparse matrix.

plusEquals(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix

Type-specific version of plusEquals for combining whatever type this is with the input dense matrix.

plusEquals(DiagonalMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix

Type-specific version of plusEquals for combining whatever type this is with the input diagonal matrix.

plusEquals(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector

Type-specific version of plusEquals for combining whatever type this is with the input dense vector.

plusEquals(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector

plusEquals(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector

plusEquals(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix

plusEquals(AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix

Inline addition of this and matrix, modifies the elements of this

plusEquals(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector

plusEquals(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector

Inline addition of this and the other vector

plusEquals(MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble

plusEquals(MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger

plusEquals(MutableLong) - Method in class gov.sandia.cognition.math.MutableLong

plusEquals(RingType) - Method in interface gov.sandia.cognition.math.Ring

Inline arithmetic addition of this and other

plusEquals(UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber

plusEquals(UnivariateGaussian.SufficientStatistic) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic

Adds another sufficient statistic to this one.

plusEquals(RandomVariable<Number>) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.PMF

Default constructor

PMF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.PMF

Creates a new instance of PMF

PMF(BernoulliDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.PMF

Creates a new instance of BetaBinomialDistribution

PMF(int, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.PMF

Creates a new instance of BetaBinomialDistribution

PMF(BetaBinomialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.BinomialDistribution.PMF

Default constructor.

PMF(int, double) - Constructor for class gov.sandia.cognition.statistics.distribution.BinomialDistribution.PMF

Creates a new instance of PMF

PMF(BinomialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BinomialDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution.PMF

Creates a new instance of CategoricalDistribution

PMF(int) - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution.PMF

Creates a new instance of CategoricalDistribution

PMF(Vector) - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution.PMF

Creates a new instance of CategoricalDistribution

PMF(CategoricalDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess.PMF

Creates a new instance of ChineseRestaurantProcess

PMF(double, int) - Constructor for class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess.PMF

Creates a new instance of ChineseRestaurantProcess

PMF(ChineseRestaurantProcess) - Constructor for class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.PMF

Default constructor

PMF(DataDistribution<KeyType>) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.PMF

Copy constructor

PMF(int) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.PMF

Creates a new instance of DefaultDataDistribution

PMF(Iterable<? extends KeyType>) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.PMF

Creates a new instance of ScalarDataDistribution

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.PMF

Creates a new instance of DeterministicDistribution

PMF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.PMF

Creates a new instance of DeterministicDistribution

PMF(DeterministicDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.PMF

Copy Constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.GeometricDistribution.PMF

Creates a new instance of GeometricDistribution

PMF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.GeometricDistribution.PMF

Creates a new instance of GeometricDistribution

PMF(GeometricDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.GeometricDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.PMF

Creates a new instance of MultinomialDistribution.PMF

PMF(int, int) - Constructor for class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.PMF

Creates a new instance of MultinomialDistribution.PMF

PMF(Vector, int) - Constructor for class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.PMF

Creates a new instance of MultinomialDistribution.PMF

PMF(MultinomialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution.PMF

Creates a new instance of DirichletDistribution

PMF(int, int) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution.PMF

Creates a new instance of MultivariatePolyaDistribution

PMF(Vector, int) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution.PMF

Creates a new instance of MultivariatePolyaDistribution

PMF(MultivariatePolyaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution.PMF

Copy Constructor.

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.PMF

Creates a new instance of PMF

PMF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.PMF

Creates a new instance of PMF

PMF(NegativeBinomialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution.PMF

Default constructor.

PMF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution.PMF

Creates a new PMF

PMF(PoissonDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution.PMF

Copy constructor

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.PMF

Default constructor

PMF(ScalarDataDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.PMF

Copy constructor

PMF(Iterable<? extends Number>) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.PMF

Creates a new instance of PMF

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.PMF

Creates a new UniformIntegerDistribution.PMF with min and max 0.

PMF(int, int) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.PMF

Creates a new UniformIntegerDistribution.PMF with the given min and max.

PMF(UniformIntegerDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.PMF

Creates a new UniformIntegerDistribution.PMF as a copy of the given other uniform distribution.

PMF() - Constructor for class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.PMF

Creates a new instance of YuleSimonDistribution

PMF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.PMF

Creates a new instance of YuleSimonDistribution

PMF(YuleSimonDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.PMF

Copy constructor

Point(double, double) - Constructor for class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.Point

Creates a new instance of Point

PoissonBayesianEstimator - Class in gov.sandia.cognition.statistics.bayesian.conjugate

A Bayesian estimator for the parameter of a PoissonDistribution using the conjugate prior GammaDistribution.

PoissonBayesianEstimator() - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator

Creates a new instance of PoissonBayesianEstimator

PoissonBayesianEstimator(GammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator

Creates a new instance of PoissonBayesianEstimator

PoissonBayesianEstimator(PoissonDistribution, GammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator

Creates a new instance of PoissonBayesianEstimator

PoissonBayesianEstimator(BayesianParameter<Double, PoissonDistribution, GammaDistribution>) - Constructor for class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator

Creates a new instance

PoissonBayesianEstimator.Parameter - Class in gov.sandia.cognition.statistics.bayesian.conjugate

Parameter of this conjugate prior relationship.

PoissonDistribution - Class in gov.sandia.cognition.statistics.distribution

A Poisson distribution is the limits of what happens when a Bernoulli trial with "rare" events are sampled on a continuous basis and then binned into discrete time intervals.

PoissonDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution

Creates a new instance of PoissonDistribution

PoissonDistribution(double) - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution

Creates a new instance of PoissonDistribution

PoissonDistribution(PoissonDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution

Creates a new instance of PoissonDistribution

PoissonDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution

CDF of the PoissonDistribution

PoissonDistribution.MaximumLikelihoodEstimator - Class in gov.sandia.cognition.statistics.distribution

Creates a PoissonDistribution from data

PoissonDistribution.PMF - Class in gov.sandia.cognition.statistics.distribution

PMF of the PoissonDistribution.

PoissonDistribution.WeightedMaximumLikelihoodEstimator - Class in gov.sandia.cognition.statistics.distribution

Creates a PoissonDistribution from weighted data.

PolynomialFunction - Class in gov.sandia.cognition.learning.function.scalar

A single polynomial term specified by a real-valued exponent.

PolynomialFunction(double) - Constructor for class gov.sandia.cognition.learning.function.scalar.PolynomialFunction

Creates a new instance of PolynomialFunction

PolynomialFunction(PolynomialFunction) - Constructor for class gov.sandia.cognition.learning.function.scalar.PolynomialFunction

Copy Constructor

PolynomialFunction.ClosedForm - Interface in gov.sandia.cognition.learning.function.scalar

Describes functionality of a closed-form algebraic polynomial function

PolynomialFunction.Cubic - Class in gov.sandia.cognition.learning.function.scalar

Algebraic treatment for a polynomial of the form y(x) = q0 + q1*x + q2*x^2 + q3*x^3

PolynomialFunction.Linear - Class in gov.sandia.cognition.learning.function.scalar

Utilities for algebraic treatment of a linear polynomial of the form y(x) = q0 + q1*x

PolynomialFunction.Quadratic - Class in gov.sandia.cognition.learning.function.scalar

Utilities for algebraic treatment of a quadratic polynomial of the form y(x) = q0 + q1*x + q2*x^2.

PolynomialFunction.Regression - Class in gov.sandia.cognition.learning.function.scalar

Performs Linear Regression using an arbitrary set of PolynomialFunction basis functions

PolynomialKernel - Class in gov.sandia.cognition.learning.function.kernel

The PolynomialKernel class implements a kernel for two given vectors that is the polynomial function:
(x dot y + c)^d
d is the degree of the polynomial, which must be a positive integer.

PolynomialKernel() - Constructor for class gov.sandia.cognition.learning.function.kernel.PolynomialKernel

Creates a new instance of PolynomialKernel with a degree of 2 and a constant of 1.0.

PolynomialKernel(int) - Constructor for class gov.sandia.cognition.learning.function.kernel.PolynomialKernel

Creates a new instance of PolynomialKernel with the given degree and a constant of 1.0.

PolynomialKernel(int, double) - Constructor for class gov.sandia.cognition.learning.function.kernel.PolynomialKernel

Creates a new instance of PolynomialKernel with the given degree and constant.

PolynomialKernel(PolynomialKernel) - Constructor for class gov.sandia.cognition.learning.function.kernel.PolynomialKernel

Creates a new copy of a PolynomialKernel.

PorterEnglishStemmingFilter - Class in gov.sandia.cognition.text.term.filter.stem

A term filter that uses the Porter Stemming algorithm.

PorterEnglishStemmingFilter() - Constructor for class gov.sandia.cognition.text.term.filter.stem.PorterEnglishStemmingFilter

Creates a new PorterEnglishStemmingFilter.

possibleOneCharacterEdits(String, Collection<String>) - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector

Lists all possible one-character edits for a given word by looking at character deletes, transposes, replaces, and inserts.

possibleTruthsSorted(int) - Static method in class gov.sandia.cognition.statistics.method.ShafferStaticCorrection.Statistic

Returns the sorted-ascending set of the possible set of true hypothesis given the number of treatments being considered.

posterior - Variable in class gov.sandia.cognition.statistics.TransferEntropy.TransferEntropyDistributionObject

The posterior.

power - Variable in class gov.sandia.cognition.learning.function.distance.MinkowskiDistanceMetric

The power that the distance is computed to.

power(double) - Method in class gov.sandia.cognition.math.LogNumber

Returns a new LogNumber representing this log number taken to the given power.

power(double) - Method in class gov.sandia.cognition.math.UnsignedLogNumber

Returns a new LogNumber representing this log number taken to the given power.

powerEquals(double) - Method in class gov.sandia.cognition.math.LogNumber

Transforms this log number by taking it to the given power.

powerEquals(double) - Method in class gov.sandia.cognition.math.UnsignedLogNumber

Transforms this log number by taking it to the given power.

ppnd(double) - Static method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.APStat

ALGORITHM AS 111, APPL.STATIST., VOL.26, 118-121, 1977.

precision - Variable in class gov.sandia.cognition.statistics.distribution.StudentTDistribution

Precision, which is proportionate to the inverseRootFinder of variance, of the distribution, must be greater than zero.

PrecisionRecallPair - Interface in gov.sandia.cognition.text.evaluation

A pair of precision and recall values.

predict(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter

Creates a prediction of the system's next state given the current belief state

predict(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter

predict(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.KalmanFilter

predictionHorizon - Variable in class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner

The prediction horizon, which is the number of samples in the future to try to learn to predict.

PredictiveDistribution(MultivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.PredictiveDistribution

Creates a new instance of PredictiveDistribution

PredictiveDistribution(MultivariateGaussianInverseGammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.PredictiveDistribution

Creates a new instance of PredictiveDistribution

PredictiveDistribution(MultivariateGaussian, ArrayList<InputType>) - Constructor for class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression.PredictiveDistribution

Creates a new instance of PredictiveDistribution

preprocessor - Variable in class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer

The preprocessor for the input data.

preTimes(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix

preTimes(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix

preTimes(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix

preTimes(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix

preTimes(DiagonalMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix

Package-private helper for the diagonal matrix class.

preTimes(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix

Type-specific version of pre-times for combining whatever type this is with the input sparse vector.

preTimes(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix

Type-specific version of pre-times for combining whatever type this is with the input dense vector.

previous() - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer.InternalIterator

previousIndex() - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer.InternalIterator

previousParameter - Variable in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo

The previous parameter in the random walk.

previousSmoothedErrorRate - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria

The smoothed error rate of the previous iteration.

previousStepWeight - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry

The weight of the entry on the previous step.

PrimalEstimatedSubGradient - Class in gov.sandia.cognition.learning.algorithm.svm

An implementation of the Primal Estimated Sub-Gradient Solver (PEGASOS) algorithm for learning a linear support vector machine (SVM).

PrimalEstimatedSubGradient() - Constructor for class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient

Creates a new PrimalEstimatedSubGradient with default parameters.

PrimalEstimatedSubGradient(int, double, int, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient

Creates a new PrimalEstimatedSubGradient with the given parameters.

Prime32Hash - Class in gov.sandia.cognition.hash

Implementation of the prime-hash function using 32-bit (4-byte) precision.

Prime32Hash() - Constructor for class gov.sandia.cognition.hash.Prime32Hash

Creates a new instance of Prime32Hash

Prime64Hash - Class in gov.sandia.cognition.hash

Implementation of the prime-hash function using 64-bit (8-byte) precision.

Prime64Hash() - Constructor for class gov.sandia.cognition.hash.Prime64Hash

Creates a new instance of Prime64Hash

PrincipalComponentsAnalysis - Interface in gov.sandia.cognition.learning.algorithm.pca

Principal Components Analysis is a family of algorithms that map from a high-dimensional input space to a low-dimensional output space.

PrincipalComponentsAnalysisFunction - Class in gov.sandia.cognition.learning.algorithm.pca

This VectorFunction maps a high-dimension input space onto a (hopefully) simple low-dimensional output space by subtracting the mean of the input data, and passing the zero-mean input through a dimension-reducing matrix multiplication function.

PrincipalComponentsAnalysisFunction() - Constructor for class gov.sandia.cognition.learning.algorithm.pca.PrincipalComponentsAnalysisFunction

Default constructor

PrincipalComponentsAnalysisFunction(Vector, MultivariateDiscriminant) - Constructor for class gov.sandia.cognition.learning.algorithm.pca.PrincipalComponentsAnalysisFunction

Creates a new instance of PrincipalComponentAnalysisFunction

printPartitioning(NodePartitioning<NodeNameType>) - Static method in interface gov.sandia.cognition.graph.community.NodePartitioning

A helper pretty print method so that all partitionings can have the same look-and-feel.

priors - Variable in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer

The prior distribution for the categorizer.

priors - Variable in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner

Prior probabilities for the different categories.

PriorWeightedNodeLearner<OutputType> - Interface in gov.sandia.cognition.learning.algorithm.tree

The PriorWeightedNodeLearner interface specifies the ability to configure prior weights on the learning algorithm that searches for a decision function inside a decision tree.

priorWeights - Variable in class gov.sandia.cognition.statistics.distribution.LinearMixtureModel

Weights proportionate by which the distributions are sampled

ProbabilisticLatentSemanticAnalysis - Class in gov.sandia.cognition.text.topic

An implementation of the Probabilistic Latent Semantic Analysis (PLSA) algorithm.

ProbabilisticLatentSemanticAnalysis() - Constructor for class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis

Creates a new ProbabilisticSemanticAnalysis with default parameters.

ProbabilisticLatentSemanticAnalysis(Random) - Constructor for class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis

Creates a new ProbabilisticLatentSemanticAnalysis with default parameters and the given random number generator.

ProbabilisticLatentSemanticAnalysis(int) - Constructor for class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis

Creates a new ProbabilisticLatentSemanticAnalysis with the given rank and otherwise default parameters.

ProbabilisticLatentSemanticAnalysis(int, double, Random) - Constructor for class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis

Creates a new ProbabilisticLatentSemanticAnalysis with the given parameters.

ProbabilisticLatentSemanticAnalysis.LatentData - Class in gov.sandia.cognition.text.topic

The information about each latent variable.

ProbabilisticLatentSemanticAnalysis.Result - Class in gov.sandia.cognition.text.topic

The dimensionality transform created by probabilistic latent semantic analysis.

ProbabilisticLatentSemanticAnalysis.StatusPrinter - Class in gov.sandia.cognition.text.topic

Prints out the status of the probabilistic latent semantic analysis algorithm.

ProbabilityDensityFunction<DataType> - Interface in gov.sandia.cognition.statistics

Defines a probability density function.

probabilityFunction - Variable in class gov.sandia.cognition.learning.function.cost.ParallelNegativeLogLikelihood.NegativeLogLikelihoodTask

Probability function to compute the log likelihood

ProbabilityFunction<DataType> - Interface in gov.sandia.cognition.statistics

A Distribution that has an evaluate method that indicates p(x), such as a probability density function or a probability mass function (but NOT a cumulative distribution function).

ProbabilityMassFunction<DataType> - Interface in gov.sandia.cognition.statistics

The ProbabilityMassFunction interface defines the functionality of a probability mass function.

ProbabilityMassFunctionUtil - Class in gov.sandia.cognition.statistics

Utility methods for helping computations in PMFs.

ProbabilityMassFunctionUtil() - Constructor for class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil

ProbabilityUtil - Class in gov.sandia.cognition.math

Utility methods for dealing with probabilities.

ProbabilityUtil() - Constructor for class gov.sandia.cognition.math.ProbabilityUtil

probablisticSelect(DoubleArrayList, Random) - Static method in class gov.sandia.cognition.graph.GraphWalker

Helper method that returns the index of the probabilistically selected input weight.

ProcessLauncher - Class in gov.sandia.cognition.io

Launches a process as a separate thread and monitors the stdout and stderr, throwing events when they update and exit

ProcessLauncher(String) - Constructor for class gov.sandia.cognition.io.ProcessLauncher

Creates a new instance of ProcessLauncher

ProcessLauncherEvent - Class in gov.sandia.cognition.io

Event that gets fired when the ProcessLauncher is updated (for example, the underlying process writes to stdout or stderr, or terminates)

ProcessLauncherEvent(ProcessLauncherEvent.EventType, String, Process) - Constructor for class gov.sandia.cognition.io.ProcessLauncherEvent

Creates a new instance of ProcessLauncherEvent

processLauncherEvent(ProcessLauncherEvent) - Method in interface gov.sandia.cognition.io.ProcessLauncherListener

Method that gets called when the ProcessLauncher is updated (for example, the underlying process writes to stdout or stderr, or terminates)

ProcessLauncherEvent.EventType - Enum in gov.sandia.cognition.io

Types of events that may be fired

ProcessLauncherListener - Interface in gov.sandia.cognition.io

Interface for receiving ProcessLauncher events

ProductKernel<InputType> - Class in gov.sandia.cognition.learning.function.kernel

The ProductKernel class implements a kernel that takes the product of applying multiple kernels to the same pair of inputs.

ProductKernel() - Constructor for class gov.sandia.cognition.learning.function.kernel.ProductKernel

Creates a new instance of ProductKernel.

ProductKernel(Collection<? extends Kernel<? super InputType>>) - Constructor for class gov.sandia.cognition.learning.function.kernel.ProductKernel

Creates a new instance of ProductKernel with the given collection of kernels.

Projectron<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel

An implementation of the Projectron algorithm, which is an online kernel binary categorizer learner that has a budget parameter tuned by the eta parameter.

Projectron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron

Creates a new Projectron with a null kernel and default parameters.

Projectron(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron

Creates a new Projectron with the given kernel and default parameters.

Projectron(Kernel<? super InputType>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron

Creates a new Projectron with the given parameters.

Projectron.LinearSoftMargin<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel

An implementation of the Projectron++ algorithm, which is an online kernel binary categorizer learner that has a budget parameter tuned by the eta parameter.

ProportionalUpdate() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.ProportionalUpdate

Creates a new OnlineMultiPerceptron.ProportionalUpdate.

ProportionalUpdate(double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.ProportionalUpdate

Creates a new OnlineMultiPerceptron.ProportionalUpdate with the given minimum margin.

ProportionalUpdate(double, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.ProportionalUpdate

Creates a new OnlineMultiPerceptron.ProportionalUpdate with the given minimum margin and backing vector factory.

proportionIncorrectInSample - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner

The proportion of incorrect examples in each sample.

proposals - Variable in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater

Number of proposals suggested

prototype - Variable in class gov.sandia.cognition.factory.PrototypeFactory

The prototype to create clones from.

PrototypeFactory<CreatedType extends CloneableSerializable> - Class in gov.sandia.cognition.factory

The PrototypeFactory class implements a Factory that uses a prototype object to create new objects from by cloning it.

PrototypeFactory() - Constructor for class gov.sandia.cognition.factory.PrototypeFactory

Creates a new PrototypeFactory with no prototype.

PrototypeFactory(CreatedType) - Constructor for class gov.sandia.cognition.factory.PrototypeFactory

Creates a new PrototypeFactory with the given prototype.

PrototypeFactory(PrototypeFactory<? extends CreatedType>) - Constructor for class gov.sandia.cognition.factory.PrototypeFactory

Creates a new copy of a PrototypeFactory.

prototypes - Variable in class gov.sandia.cognition.learning.function.categorization.LinearMultiCategorizer

A map of each category to its prototype categorizer.

prtrng(double, double, double) - Static method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.APStat

Algorithm AS 190 Appl Statist (1983) Vol.32, No.2.

pseudoInverse() - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix

pseudoInverse(double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix

pseudoInverse(double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix

pseudoInverse(double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix

Computes the effective pseudo-inverse of this, using a rather expensive procedure (SVD)

pseudoInverse() - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition

pseudoInverse(double) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition

pseudoInverse() - Method in interface gov.sandia.cognition.math.matrix.decomposition.SingularValueDecomposition

Computes the Least Squares pseudoinverse of the underlying matrix

pseudoInverse(double) - Method in interface gov.sandia.cognition.math.matrix.decomposition.SingularValueDecomposition

Computes the Least Squares pseudoinverse of the underlying matrix, while clipping the singular values at effectiveZero

pseudoInverse() - Method in interface gov.sandia.cognition.math.matrix.DiagonalMatrix

pseudoInverse(double) - Method in interface gov.sandia.cognition.math.matrix.DiagonalMatrix

pseudoInverse() - Method in interface gov.sandia.cognition.math.matrix.Matrix

Computes the effective pseudo-inverse of this, using a rather expensive procedure (SVD)

pseudoInverse(double) - Method in interface gov.sandia.cognition.math.matrix.Matrix

Computes the effective pseudo-inverse of this, using a rather expensive procedure (SVD)

pseudoInverse(double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix

pseudoInverse(double) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix

pseudoInverse() - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ

pseudoInverse(double) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ

psi - Variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation

Psi is the cached value 1 + phi^2 / 2.

PublicationReference - Annotation Type in gov.sandia.cognition.annotation

The PublicationReference annotation describes a reference to a publication from a journal, conference, etc.

PublicationReferences - Annotation Type in gov.sandia.cognition.annotation

The PublicationReferences annotation defines a container for one or more references to a publication.

PublicationType - Enum in gov.sandia.cognition.annotation

The PublicationType enumeration lists off the possible types of publications for a PublicationReference annotation.

put(Integer, ValueType) - Method in class gov.sandia.cognition.collection.DynamicArrayMap

Runs in O(1) if the key is within the range already used, otherwise O(n) to expand the range.

put(int, ValueType) - Method in class gov.sandia.cognition.collection.DynamicArrayMap

Puts a value into the mapping.

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