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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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