Skip navigation links
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 

C

Cache(Matrix, Matrix, Vector, double) - Constructor for class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction.Cache
Creates a new instance of Cache
call() - Method in class gov.sandia.cognition.framework.concurrent.MultithreadedCognitiveModel.ModuleEvaluator
 
call() - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer.AssignDataToCluster
 
call() - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer.CreateClustersFromAssignments
 
call() - Method in class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm.EvaluateGenome
 
call() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask
 
call() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ComputeTransitionsTask
 
call() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.LogLikelihoodTask
 
call() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.NormalizeTransitionTask
 
call() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ObservationLikelihoodTask
 
call() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.StateObservationLikelihoodTask
 
call() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ViterbiTask
 
call() - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer.SubCostEvaluate
 
call() - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer.SubCostGradient
 
call() - Method in class gov.sandia.cognition.learning.function.cost.ParallelNegativeLogLikelihood.NegativeLogLikelihoodTask
 
call() - Method in class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ClusterUpdaterTask
 
call() - Method in class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ObservationAssignmentTask
 
call() - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.SampleRange
 
call() - Method in class gov.sandia.cognition.statistics.method.MaximumLikelihoodDistributionEstimator.DistributionEstimationTask
 
call() - Method in class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler.DocumentSampleTask
 
canExtract(File) - Method in class gov.sandia.cognition.text.document.extractor.AbstractDocumentExtractor
 
canExtract(File) - Method in interface gov.sandia.cognition.text.document.extractor.DocumentExtractor
Determines if the given file can be extracted by this extractor.
canExtract(URI) - Method in interface gov.sandia.cognition.text.document.extractor.DocumentExtractor
Determines if the given file can be extracted by this extractor.
canExtract(URLConnection) - Method in interface gov.sandia.cognition.text.document.extractor.DocumentExtractor
Determines if the given file can be extracted by this extractor.
canExtract(URI) - Method in class gov.sandia.cognition.text.document.extractor.TextDocumentExtractor
 
canExtract(URLConnection) - Method in class gov.sandia.cognition.text.document.extractor.TextDocumentExtractor
 
capitalizeFirstCharacter(String) - Static method in class gov.sandia.cognition.util.StringUtil
Capitalizes the first character of the given string.
castOrCreateModel(Object) - Static method in class gov.sandia.cognition.framework.io.ModelFileHandler
Attempts to cast the given Object to a CognitiveModel.
CategoricalDistribution - Class in gov.sandia.cognition.statistics.distribution
The Categorical Distribution is the multivariate generalization of the Bernoulli distribution, where the outcome of an experiment is a one-of-N output, where the output is a selector Vector.
CategoricalDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
Creates a new instance of CategoricalDistribution
CategoricalDistribution(int) - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
Creates a new instance of CategoricalDistribution
CategoricalDistribution(Vector) - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
Creates a new instance of CategoricalDistribution
CategoricalDistribution(CategoricalDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
Copy constructor
CategoricalDistribution.PMF - Class in gov.sandia.cognition.statistics.distribution
PMF of the Categorical Distribution
categories - Variable in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTree
The list of possible output categories.
categories - Variable in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner
The categories for the prior.
categories - Variable in class gov.sandia.cognition.learning.function.categorization.AbstractCategorizer
The set of categories that are the possible output values of the categorizer.
CategorizationTree<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.tree
The CategorizationTree class extends the DecisionTree class to implement a decision tree that does categorization.
CategorizationTree() - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTree
Creates a new instance of CategorizationTree.
CategorizationTree(DecisionTreeNode<InputType, OutputType>, Set<OutputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTree
Creates a new instance of CategorizationTree.
CategorizationTreeLearner<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.tree
The CategorizationTreeLearner class implements a supervised learning algorithm for learning a categorization tree.
CategorizationTreeLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
Creates a new instance of CategorizationTreeLearner.
CategorizationTreeLearner(DeciderLearner<? super InputType, OutputType, ?, ?>) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
Creates a new instance of CategorizationTreeLearner.
CategorizationTreeLearner(DeciderLearner<? super InputType, OutputType, ?, ?>, int, int) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
Creates a new instance of CategorizationTreeLearner.
CategorizationTreeLearner(DeciderLearner<? super InputType, OutputType, ?, ?>, int, int, Map<OutputType, Double>) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
Creates a new instance of CategorizationTreeLearner.
CategorizationTreeNode<InputType,OutputType,InteriorType> - Class in gov.sandia.cognition.learning.algorithm.tree
The CategorizationTreeNode implements a DecisionTreeNode for a tree that does categorization.
CategorizationTreeNode() - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode
Creates a new instance of CategorizationTreeNode.
CategorizationTreeNode(DecisionTreeNode<InputType, OutputType>, OutputType) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode
Creates a new instance of CategorizationTreeNode.
CategorizationTreeNode(DecisionTreeNode<InputType, OutputType>, OutputType, Object) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode
Creates a new instance of CategorizationTreeNode.
CategorizationTreeNode(DecisionTreeNode<InputType, OutputType>, Categorizer<? super InputType, ? extends InteriorType>, OutputType, Object) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode
Creates a new instance of CategorizationTreeNode.
Categorizer<InputType,CategoryType> - Interface in gov.sandia.cognition.learning.function.categorization
The Categorizer interface defines the functionality of an object that can take an input and evaluate what category out of a fixed set of categories it belongs to.
categorizer - Variable in class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer
The categorizer.
categorizers - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.BinaryCategorizerSelector
The collection of categorizers to evaluate and select from.
CategoryBalancedBaggingLearner<InputType,CategoryType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An extension of the basic bagging learner that attempts to sample bags that have equal numbers of examples from every category.
CategoryBalancedBaggingLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner
Creates a new instance of CategoryBalancedBaggingLearner.
CategoryBalancedBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner
Creates a new instance of CategoryBalancedBaggingLearner.
CategoryBalancedBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>, int, double, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner
Creates a new instance of CategoryBalancedBaggingLearner.
CategoryBalancedIVotingLearner<InputType,CategoryType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An extension of IVoting for dealing with skew problems that makes sure that there are an equal number of examples from each category in each sample that an ensemble member is trained on.
CategoryBalancedIVotingLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedIVotingLearner
Creates a new CategoryBalancedIVotingLearner.
CategoryBalancedIVotingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>, int, double, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedIVotingLearner
Creates a new CategoryBalancedIVotingLearner.
CategoryBalancedIVotingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>, int, double, double, boolean, Factory<? extends DataDistribution<CategoryType>>, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedIVotingLearner
Creates a new CategoryBalancedIVotingLearner.
categoryCounts - Variable in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner
The counts for each category.
categoryList - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner
The list of categories.
categoryPairsToEvaluatorMap - Variable in class gov.sandia.cognition.learning.function.categorization.BinaryVersusCategorizer
Maps false-true category pairs .
categoryPriors - Variable in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner
The priors for each category.
categoryProbabilities - Variable in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner
Following is scratch space used when computing weighted entropy.
CauchyDistribution - Class in gov.sandia.cognition.statistics.distribution
A Cauchy Distribution is the ratio of two Gaussian Distributions, sometimes known as the Lorentz distribution.
CauchyDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Creates a new instance of CauchyDistribution
CauchyDistribution(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Creates a new instance of CauchyDistribution
CauchyDistribution(CauchyDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Copy constructor
CauchyDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
CDF of the CauchyDistribution.
CauchyDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution
PDF of the CauchyDistribution.
cdf - Variable in class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
The cumulative distribution function to base the evaluator on.
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.CDF
Default constructor
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.CDF
Creates a new instance of PMF
CDF(BernoulliDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.CDF
Creates a new instance of BetaBinomialDistribution
CDF(int, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.CDF
Creates a new instance of BetaBinomialDistribution
CDF(BetaBinomialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.BetaDistribution.CDF
Default constructor.
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaDistribution.CDF
Creates a new CDF
CDF(BetaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BetaDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.BinomialDistribution.CDF
Default constructor.
CDF(int, double) - Constructor for class gov.sandia.cognition.statistics.distribution.BinomialDistribution.CDF
Creates a new instance of BinomialDistribution
CDF(BinomialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.BinomialDistribution.CDF
Creates a new instance of CDF
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution.CDF
Creates a new instance of CauchyDistribution
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution.CDF
Creates a new instance of CauchyDistribution
CDF(CauchyDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.CauchyDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.CDF
Default constructor.
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.CDF
Creates a new instance of ChiSquareDistribution
CDF(ChiSquareDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.CDF
Creates a new instance of DeterministicDistribution
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.CDF
Creates a new instance of DeterministicDistribution
CDF(DeterministicDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.CDF
Copy Constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.CDF
Default constructor.
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.CDF
Creates a new instance of CDF
CDF(ExponentialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.GammaDistribution.CDF
Default constructor.
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.GammaDistribution.CDF
Creates a new instance of CDF
CDF(GammaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.GammaDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.GeometricDistribution.CDF
Creates a new instance of GeometricDistribution
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.GeometricDistribution.CDF
Creates a new instance of GeometricDistribution
CDF(GeometricDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.GeometricDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.CDF
Default constructor
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.CDF
Creates a new instance of InverseGammaDistribution
CDF(InverseGammaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution.CDF
Creates a new instance of CDF
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.CDF
Creates a new instance of LaplaceDistribution.CDF
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.CDF
Creates a new instance of LaplaceDistribution.CDF
CDF(LaplaceDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.CDF
Copy Constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.LogisticDistribution.CDF
Default constructor
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.LogisticDistribution.CDF
Creates a new instance of CDF
CDF(LogisticDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.LogisticDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.CDF
Default constructor.
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.CDF
Creates a new instance of LogNormalDistribution
CDF(LogNormalDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.CDF
Copy Constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.CDF
Creates a new instance of CDF
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.CDF
Creates a new instance of CDF
CDF(NegativeBinomialDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution.CDF
Creates a new instance of CDF
CDF(double, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution.CDF
Creates a new instance of CDF
CDF(ParetoDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ParetoDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution.CDF
Default constructor.
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution.CDF
Creates a new CDF
CDF(PoissonDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.CDF
Default constructor
CDF(ScalarDataDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.CDF
Copy constructor
CDF(Iterable<? extends Number>) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.CDF
Creates a new instance of PMF
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.CDF
Creates a new instance of ScalarMixtureDensityModel
CDF(SmoothUnivariateDistribution...) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.CDF
Creates a new instance of ScalarMixtureDensityModel
CDF(Collection<? extends SmoothUnivariateDistribution>) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.CDF
Creates a new instance of ScalarMixtureDensityModel
CDF(Collection<? extends SmoothUnivariateDistribution>, double[]) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.CDF
Creates a new instance of ScalarMixtureDensityModel
CDF(ScalarMixtureDensityModel) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution.CDF
Default constructor
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution.CDF
Creates a new instance of CumulativeDistribution
CDF(SnedecorFDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution.CDF
Copy Constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.CDF
Default constructor
CDF(int, double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.CDF
Creates a new instance of StudentizedRangeDistribution
CDF(StudentizedRangeDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.CDF
Default constructor.
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.CDF
Creates a new instance of CDF
CDF(double, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.CDF
Creates a new instance of PDF
CDF(StudentTDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.CDF
Creates a new instance of CDF
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF
Creates a new instance of CDF
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF
Creates a new instance of CDF
CDF(UniformDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.CDF
Creates a new UniformIntegerDistribution.PMF with min and max 0.
CDF(int, int) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.CDF
Creates a new UniformIntegerDistribution.CDF with the given min and max.
CDF(UniformIntegerDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.CDF
Creates a new UniformIntegerDistribution.CDF as a copy of the given other uniform distribution.
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF
Creates a new instance of UnivariateGaussian with zero mean and unit variance
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF
Creates a new instance of UnivariateGaussian
CDF(UnivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution.CDF
Creates a new instance of WeibullDistribution
CDF(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution.CDF
Creates a new instance of WeibullDistribution
CDF(WeibullDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution.CDF
Copy constructor
CDF() - Constructor for class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.CDF
Creates a new instance of YuleSimonDistribution
CDF(double) - Constructor for class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.CDF
Creates a new instance of YuleSimonDistribution
CDF(YuleSimonDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.CDF
Copy constructor
centerData - Variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
Whether or not the data should be centered before doing KPCA.
centerData - Variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
A flag indicating if the incoming data needs to be centered or not.
centerWeightsRange() - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
This algorithm only works when there are some negative scores and some positive scores.
centroid - Variable in class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster
The center of the cluster.
CentroidCluster<ClusterType> - Class in gov.sandia.cognition.learning.algorithm.clustering.cluster
The CentroidCluster class extends the default cluster to contain a central element.
CentroidCluster() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster
Creates a new instance of CentroidCluster.
CentroidCluster(ClusterType) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster
Creates a new instance of CentroidCluster.
CentroidCluster(int, ClusterType) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster
Creates a new instance of CentroidCluster.
CentroidCluster(ClusterType, Collection<? extends ClusterType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster
Creates a new instance of CentroidCluster.
CentroidCluster(int, ClusterType, Collection<? extends ClusterType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster
Creates a new instance of CentroidCluster.
CentroidClusterDivergenceFunction<DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
The CentroidClusterDivergenceFunction class implements a divergence function between a cluster and an object by computing the divergence between the center of the cluster and the object.
CentroidClusterDivergenceFunction(DivergenceFunction<? super DataType, ? super DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.CentroidClusterDivergenceFunction
Creates a new instance of CentroidClusterDivergenceFunction.
changedCount - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The number of examples that have changed assignments in the last iteration.
changeOfLogLikelihood - Variable in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
The change in log-likelihood of the algorithm from the current iteration.
ChebyshevDistanceMetric - Class in gov.sandia.cognition.learning.function.distance
An implementation of the Chebyshev distance, which is the absolute value of the largest difference between two vectors in a single dimension.
ChebyshevDistanceMetric() - Constructor for class gov.sandia.cognition.learning.function.distance.ChebyshevDistanceMetric
Creates a new ChebyshevDistanceMetric.
ChebyshevInequality - Class in gov.sandia.cognition.statistics.method
Computes the Chebyshev Inequality for the given level of confidence.
ChebyshevInequality() - Constructor for class gov.sandia.cognition.statistics.method.ChebyshevInequality
Creates a new instance of ChebyshevInequality
checkConfidence(double) - Static method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Checks to make sure that confidence is between 0.0 and 1.0.
checkedAdd(int, int) - Static method in class gov.sandia.cognition.math.MathUtil
Safely checks for underflow/overflow before adding two integers.
checkedMultiply(int, int) - Static method in class gov.sandia.cognition.math.MathUtil
Safely checks for overflow before multiplying two integers.
checkMultiplicationDimensions(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
checkMultiplicationDimensions(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Checks to see if the dimensions are appropriate for: this.times( postMultiplicationMatrix )
checkNumFolds(int) - Static method in class gov.sandia.cognition.learning.experiment.CrossFoldCreator
Checks the given number of folds to make sure that it is greater than 1.
checkSameDimensionality(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
checkSameDimensionality(Vector) - Method in interface gov.sandia.cognition.math.matrix.Vector
Determines if this and other have the same number of dimensions (size)
checkSameDimensions(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
checkSameDimensions(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Checks to see if the dimensions are the same between this and otherMatrix
checkTrainingPercent(double) - Static method in class gov.sandia.cognition.learning.data.RandomDataPartitioner
Checks to make sure the training percent greater than 0.0 and less than 1.0.
child - Variable in class gov.sandia.cognition.math.Combinations.AbstractCombinationsIterator
Child iterator for recursion
childMap - Variable in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
The mapping of decider decision values to child nodes.
children - Variable in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode
The list of children.
children - Variable in class gov.sandia.cognition.math.geometry.Quadtree.Node
The list of children for this node.
childrenDivergence - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer.HierarchyNode
The divergence between the two children, if they exist.
ChineseRestaurantProcess - Class in gov.sandia.cognition.statistics.distribution
A Chinese Restaurant Process is a discrete stochastic processes that partitions data points to clusters.
ChineseRestaurantProcess() - Constructor for class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Creates a new instance of ChineseRestaurantProcess
ChineseRestaurantProcess(double, int) - Constructor for class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Creates a new instance of ChineseRestaurantProcess
ChineseRestaurantProcess(ChineseRestaurantProcess) - Constructor for class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Default constructor
ChineseRestaurantProcess.PMF - Class in gov.sandia.cognition.statistics.distribution
PMF of the Chinese Restaurant Process
ChiSquareConfidence - Class in gov.sandia.cognition.statistics.method
This is the chi-square goodness-of-fit test.
ChiSquareConfidence() - Constructor for class gov.sandia.cognition.statistics.method.ChiSquareConfidence
Creates a new instance of ChiSquareConfidence
ChiSquareConfidence.Statistic - Class in gov.sandia.cognition.statistics.method
Confidence Statistic for a chi-square test
ChiSquareDistribution - Class in gov.sandia.cognition.statistics.distribution
Describes a Chi-Square Distribution.
ChiSquareDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Default constructor.
ChiSquareDistribution(double) - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Creates a new instance of ChiSquareDistribution
ChiSquareDistribution(ChiSquareDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Copy constructor
ChiSquareDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
Cumulative Distribution Function (CDF) of a Chi-Square Distribution
ChiSquareDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution
PDF of the Chi-Square distribution
ChiSquaredSimilarity - Class in gov.sandia.cognition.statistics
A class for computing the chi-squared similarity between two vectors.
ChiSquaredSimilarity(Vector, Vector) - Constructor for class gov.sandia.cognition.statistics.ChiSquaredSimilarity
Basic constructor.
CholeskyDecompositionMTJ - Class in gov.sandia.cognition.math.matrix.mtj.decomposition
Computes the Cholesky decomposition of the symmetric positive definite matrix.
chooseChild(InputType) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
 
chooseChild(InputType) - Method in interface gov.sandia.cognition.learning.algorithm.tree.DecisionTreeNode
Chooses the child node corresponding to the given input.
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
Called to clean up the learning algorithm's state after learning has finished.
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineStochasticGradient
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Called to clean up the learning algorithm's state after learning has finished.
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderNewtonsMethod
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler
 
cleanupAlgorithm() - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
 
clear() - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
clear() - Method in class gov.sandia.cognition.collection.DefaultIndexer
 
clear() - Method in class gov.sandia.cognition.collection.DynamicArrayMap
Runs in O(n).
clear() - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
 
clear() - Method in interface gov.sandia.cognition.collection.Indexer
Clears the contents of this index.
clear() - Method in interface gov.sandia.cognition.collection.NumericMap
Removes all elements from the map.
clear() - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Clears this CognitiveModelLite state, resetting it to being uninitialized.
clear() - Method in class gov.sandia.cognition.framework.lite.CogxelStateLite
Clears all of the Cogxels in this CogxelState.
clear() - Method in class gov.sandia.cognition.graph.DenseMemoryGraph
 
clear() - Method in interface gov.sandia.cognition.graph.DirectedNodeEdgeGraph
Clears the graph back to the original, empty state
clear() - Method in class gov.sandia.cognition.graph.GraphMetrics
Clears all cached metrics for the originally input graph.
clear() - Method in class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
 
clear() - Method in interface gov.sandia.cognition.learning.performance.categorization.ConfusionMatrix
Empties out all the data in this confusion matrix.
clear() - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
 
clear() - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
 
clear() - Method in class gov.sandia.cognition.math.RingAccumulator
Clears the accumulator.
clear() - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
 
clear() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
Resets this set of sufficient statistics to its empty state.
clear() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
Resets this set of sufficient statistics to its empty state.
clear() - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic
Resets this set of sufficient statistics to its empty state.
clearLabels() - Method in class gov.sandia.cognition.graph.inference.GraphWrappingEnergyFunction
Clears labels previously set.
clearStoredCosts() - Method in class gov.sandia.cognition.graph.inference.CostSpeedupEnergyFunction
Clears the pre-computed costs that were stored to keep from calling log and potential each time.
clone() - Method in class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
 
clone() - Method in class gov.sandia.cognition.algorithm.AbstractParallelAlgorithm
 
clone() - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
 
clone() - Method in class gov.sandia.cognition.collection.AbstractLogNumberMap
 
clone() - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap
 
clone() - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
clone() - Method in class gov.sandia.cognition.collection.DefaultIndexer
 
clone() - Method in class gov.sandia.cognition.collection.DynamicArrayMap
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
 
clone() - Method in class gov.sandia.cognition.collection.IntegerSpan
 
clone() - Method in class gov.sandia.cognition.data.convert.IdentityDataConverter
 
clone() - Method in class gov.sandia.cognition.evaluator.AbstractStatefulEvaluator
 
clone() - Method in class gov.sandia.cognition.evaluator.CompositeEvaluatorList
 
clone() - Method in class gov.sandia.cognition.evaluator.IdentityEvaluator
 
clone() - Method in class gov.sandia.cognition.evaluator.ValueClamper
 
clone() - Method in class gov.sandia.cognition.evaluator.ValueMapper
 
clone() - Method in class gov.sandia.cognition.factory.ConstructorBasedFactory
 
clone() - Method in class gov.sandia.cognition.factory.PrototypeFactory
Clones this PrototypeFactory.
clone() - Method in interface gov.sandia.cognition.framework.CognitiveModelState
A deep copy clone of this state.
clone() - Method in interface gov.sandia.cognition.framework.CognitiveModuleState
Performs a deep copy of the state.
clone() - Method in interface gov.sandia.cognition.framework.Cogxel
Clones the Cogxel.
clone() - Method in interface gov.sandia.cognition.framework.CogxelState
Clones this Cogxel state, returning a deep copy of the Cogxels.
clone() - Method in class gov.sandia.cognition.framework.DefaultCogxel
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap
 
clone() - Method in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelConverter
 
clone() - Method in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
 
clone() - Method in class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
 
clone() - Method in interface gov.sandia.cognition.framework.learning.converter.CogxelConverter
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactory
Creates a clone of this EvaluatorBasedCognitiveModuleFactory.
clone() - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner
Creates a copy of this EvaluatorBasedCognitiveModuleFactoryLearner.
clone() - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleSettings
Creates a clone of this EvaluatorBasedCognitiveModuleSettings.
clone() - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.lite.CognitiveModuleStateWrapper
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.lite.CogxelStateLite
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in interface gov.sandia.cognition.framework.lite.PatternRecognizerLite
Creates a deep copy of the pattern recognizer.
clone() - Method in class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteFactory
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteSettings
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.framework.lite.VectorBasedCognitiveModelInput
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.hash.AbstractHashFunction
 
clone() - Method in class gov.sandia.cognition.hash.Eva32Hash
 
clone() - Method in class gov.sandia.cognition.hash.Eva64Hash
 
clone() - Method in class gov.sandia.cognition.hash.FNV1a32Hash
 
clone() - Method in class gov.sandia.cognition.hash.FNV1a64Hash
 
clone() - Method in class gov.sandia.cognition.hash.Murmur32Hash
 
clone() - Method in class gov.sandia.cognition.hash.Prime32Hash
 
clone() - Method in class gov.sandia.cognition.hash.Prime64Hash
 
clone() - Method in class gov.sandia.cognition.hash.SHA256Hash
 
clone() - Method in class gov.sandia.cognition.hash.SHA512Hash
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.AbstractBatchLearnerContainer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.annealing.VectorizablePerturber
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.baseline.IdentityLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.divergence.CentroidClusterDivergenceFunction
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.divergence.WithinClusterDivergenceWrapper
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.divergence.WithinNormalizedCentroidClusterCosineDivergence
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.DistanceSamplingClusterInitializer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.GreedyClusterInitializer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.RandomClusterInitializer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractUnweightedEnsemble
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
 
clone() - Method in interface gov.sandia.cognition.learning.algorithm.gradient.GradientDescendable
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToDifferentiableScalarFunction
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.InputOutputSlopeTriplet
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineBracket
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborExhaustive
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.pca.PrincipalComponentsAnalysisFunction
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearBasisRegression
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression.Function
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.MultivariateLinearRegression
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderNewtonsMethod
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTree
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.DecisionTree
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTree
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeNode
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdGiniImpurityLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdHellingerDistanceLearner
 
clone() - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner
 
clone() - Method in class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
 
clone() - Method in class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair
 
clone() - Method in class gov.sandia.cognition.learning.data.feature.DelayFunction
 
clone() - Method in class gov.sandia.cognition.learning.data.feature.LinearRegressionCoefficientExtractor
 
clone() - Method in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator
Creates a new copy of this MultivariateDecorrelator.
clone() - Method in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
Creates a new copy of this StandardDistributionNormalizer.
clone() - Method in class gov.sandia.cognition.learning.function.categorization.AbstractCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.BinaryVersusCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter.Learner
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.FisherLinearDiscriminantBinaryCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.LinearMultiCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer.Learner
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.ScalarFunctionToBinaryCategorizerAdapter
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.categorization.VectorElementThresholdCategorizer
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.AbstractCostFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.ClusterDistortionMeasure
 
clone() - Method in interface gov.sandia.cognition.learning.function.cost.CostFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.EuclideanDistanceCostFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.MeanL1CostFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.MeanSquaredErrorCostFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer
 
clone() - Method in class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer
 
clone() - Method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
 
clone() - Method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator.Learner
 
clone() - Method in class gov.sandia.cognition.learning.function.distance.WeightedEuclideanDistanceMetric
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.ExponentialKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.KernelDistanceMetric
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.LinearKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.NormalizedKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.PolynomialKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.ProductKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.RadialBasisKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.ScalarFunctionKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.SumKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.VectorFunctionKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.kernel.WeightedKernel
Creates a copy of this kernel.
clone() - Method in class gov.sandia.cognition.learning.function.kernel.ZeroKernel
 
clone() - Method in class gov.sandia.cognition.learning.function.LinearCombinationFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.AtanFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.CosineFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.HardSigmoidFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.HardTanHFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.IdentityScalarFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.LeakyRectifiedLinearFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.LinearCombinationScalarFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminant
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminantWithBias
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.LinearFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.LinearVectorScalarFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Quadratic
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.RectifiedLinearFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.SigmoidFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.SoftPlusFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.TanHFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionLinearDiscriminant
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction.Learner
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.ElementWiseVectorFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.FeedforwardNeuralNetwork
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.GaussianContextRecognizer
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.GeneralizedLinearModel
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.LinearCombinationVectorFunction
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminantWithBias
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.VectorizableVectorConverter
 
clone() - Method in class gov.sandia.cognition.learning.function.vector.VectorizableVectorConverterWithBias
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper
 
clone() - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
 
clone() - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
 
clone() - Method in class gov.sandia.cognition.math.AbstractRing
 
clone() - Method in class gov.sandia.cognition.math.Combinations
 
clone() - Method in class gov.sandia.cognition.math.ComplexNumber
Returns a deep copy of this
clone() - Method in class gov.sandia.cognition.math.geometry.KDTree
 
clone() - Method in class gov.sandia.cognition.math.LogNumber
 
clone() - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Returns a deep copy of this.
clone() - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
clone() - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
clone() - Method in class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
clone() - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
clone() - Method in interface gov.sandia.cognition.math.matrix.Matrix
 
clone() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
clone() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
 
clone() - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
 
clone() - Method in class gov.sandia.cognition.math.matrix.mtj.Vector1
 
clone() - Method in class gov.sandia.cognition.math.matrix.mtj.Vector2
 
clone() - Method in class gov.sandia.cognition.math.matrix.mtj.Vector3
 
clone() - Method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator
 
clone() - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Clones this object.
clone() - Method in interface gov.sandia.cognition.math.matrix.Vector
 
clone() - Method in interface gov.sandia.cognition.math.matrix.Vectorizable
 
clone() - Method in class gov.sandia.cognition.math.matrix.VectorizableIndexComparator
 
clone() - Method in interface gov.sandia.cognition.math.matrix.VectorizableVectorFunction
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.math.MutableDouble
 
clone() - Method in class gov.sandia.cognition.math.MutableInteger
 
clone() - Method in class gov.sandia.cognition.math.MutableLong
 
clone() - Method in interface gov.sandia.cognition.math.Ring
Returns a smart copy of this, such that changing the values of the return class will not effect this
clone() - Method in class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
 
clone() - Method in class gov.sandia.cognition.math.signals.LinearDynamicalSystem
 
clone() - Method in class gov.sandia.cognition.math.signals.MovingAverageFilter
 
clone() - Method in class gov.sandia.cognition.math.UnivariateSummaryStatistics
 
clone() - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
clone() - Method in class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.AbstractDataDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.AbstractIncrementalEstimator
 
clone() - Method in class gov.sandia.cognition.statistics.AbstractSufficientStatistic
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.AbstractEnvelope
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LogEvaluator
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.DefaultBayesianParameter
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMCluster
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanCovarianceUpdater
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanUpdater
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.KalmanFilter
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm
 
clone() - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling
 
clone() - Method in interface gov.sandia.cognition.statistics.DataDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.DefaultDistributionParameter
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.DirichletDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.GeometricDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.LinearMixtureModel
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.PDF
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.CDF
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
 
clone() - Method in class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic
 
clone() - Method in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison
 
clone() - Method in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic
 
clone() - Method in class gov.sandia.cognition.statistics.method.AdjustedPValueStatistic
 
clone() - Method in class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay.Statistic
 
clone() - Method in class gov.sandia.cognition.statistics.method.BonferroniCorrection
 
clone() - Method in class gov.sandia.cognition.statistics.method.ConvexReceiverOperatingCharacteristic
 
clone() - Method in class gov.sandia.cognition.statistics.method.DistributionParameterEstimator
 
clone() - Method in class gov.sandia.cognition.statistics.method.DistributionParameterEstimator.DistributionWrapper
 
clone() - Method in class gov.sandia.cognition.statistics.method.FriedmanConfidence.Statistic
 
clone() - Method in class gov.sandia.cognition.statistics.method.HolmCorrection
 
clone() - Method in class gov.sandia.cognition.statistics.method.MaximumLikelihoodDistributionEstimator
 
clone() - Method in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment
 
clone() - Method in class gov.sandia.cognition.statistics.method.NemenyiConfidence.Statistic
 
clone() - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic
 
clone() - Method in class gov.sandia.cognition.statistics.method.ShafferStaticCorrection
 
clone() - Method in class gov.sandia.cognition.statistics.method.SidakCorrection
 
clone() - Method in class gov.sandia.cognition.statistics.method.StudentTConfidence.Statistic
 
clone() - Method in class gov.sandia.cognition.statistics.method.TukeyKramerConfidence
 
clone() - Method in class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic
 
clone() - Method in class gov.sandia.cognition.statistics.montecarlo.ImportanceSampler
 
clone() - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
clone() - Method in class gov.sandia.cognition.text.DefaultTextual
 
clone() - Method in class gov.sandia.cognition.text.term.DefaultIndexedTerm
 
clone() - Method in class gov.sandia.cognition.text.term.DefaultTerm
 
clone() - Method in class gov.sandia.cognition.text.term.DefaultTermIndex
 
clone() - Method in class gov.sandia.cognition.text.term.DefaultTermNGram
 
clone() - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
 
clone() - Method in class gov.sandia.cognition.text.term.filter.NGramFilter
 
clone() - Method in class gov.sandia.cognition.text.term.vector.weighter.CompositeLocalGlobalTermWeighter
 
clone() - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractEntropyBasedGlobalTermWeighter
 
clone() - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
 
clone() - Method in class gov.sandia.cognition.text.term.vector.weighter.global.DominanceGlobalTermWeighter
 
clone() - Method in class gov.sandia.cognition.text.term.vector.weighter.global.EntropyGlobalTermWeighter
 
clone() - Method in class gov.sandia.cognition.text.term.vector.weighter.global.InverseDocumentFrequencyGlobalTermWeighter
 
clone() - Method in class gov.sandia.cognition.util.AbstractCloneableSerializable
This makes public the clone method on the Object class and removes the exception that it throws.
clone() - Method in class gov.sandia.cognition.util.AbstractNamed
 
clone() - Method in class gov.sandia.cognition.util.AbstractRandomized
 
clone() - Method in class gov.sandia.cognition.util.AbstractTemporal
 
clone() - Method in interface gov.sandia.cognition.util.CloneableSerializable
Creates a new clone (shallow copy) of this object.
clone() - Method in class gov.sandia.cognition.util.DefaultNamedValue
 
clone() - Method in class gov.sandia.cognition.util.DefaultPair
 
clone() - Method in class gov.sandia.cognition.util.DefaultTriple
 
clone() - Method in class gov.sandia.cognition.util.DefaultWeightedValue
Creates a shallow copy of the WeightedValue.
CloneableSerializable - Interface in gov.sandia.cognition.util
An object that is both cloneable and serializable, because Java's Cloneable interface mistakenly doesn't have a clone() method (search on the Web, it's funny "lost in the mists of time..." )
cloneSafe(T) - Static method in class gov.sandia.cognition.util.ObjectUtil
Calls the Clone method on the given object of some type that extends CloneableSerializable.
cloneSmart(T) - Static method in class gov.sandia.cognition.util.ObjectUtil
Attempts to clone a given object.
cloneSmartArrayAndElements(T[]) - Static method in class gov.sandia.cognition.util.ObjectUtil
Clones an array and its elements.
cloneSmartElementsAsArrayList(Collection<T>) - Static method in class gov.sandia.cognition.util.ObjectUtil
Creates a new ArrayList and attempts to copy all of the elements from the given collection into it by calling the cloneSmart method on each of them.
cloneSmartElementsAsLinkedList(Iterable<T>) - Static method in class gov.sandia.cognition.util.ObjectUtil
Creates a new LinkedList and attempts to copy all of the elements from the given collection into it by calling the cloneSmart method on each of them.
ClosedFormComputableDiscreteDistribution<DataType> - Interface in gov.sandia.cognition.statistics
A discrete, closed-form Distribution with a PMF.
ClosedFormComputableDistribution<DataType> - Interface in gov.sandia.cognition.statistics
A closed-form Distribution that also has an associated distribution function.
ClosedFormCumulativeDistributionFunction<DomainType extends java.lang.Number> - Interface in gov.sandia.cognition.statistics
Functionality of a cumulative distribution function that's defined with closed-form parameters.
ClosedFormDifferentiableEvaluator<InputType,OutputType,DerivativeType> - Interface in gov.sandia.cognition.math
A differentiable function that has a closed-form derivative.
ClosedFormDiscreteUnivariateDistribution<DomainType extends java.lang.Number> - Interface in gov.sandia.cognition.statistics
A ClosedFormUnivariateDistribution that is also a DiscreteDistribution
ClosedFormDistribution<DataType> - Interface in gov.sandia.cognition.statistics
Defines a distribution that is described a parameterized mathematical equation.
ClosedFormSolver() - Constructor for class gov.sandia.cognition.learning.function.categorization.FisherLinearDiscriminantBinaryCategorizer.ClosedFormSolver
Default constructor.
ClosedFormSolver(double) - Constructor for class gov.sandia.cognition.learning.function.categorization.FisherLinearDiscriminantBinaryCategorizer.ClosedFormSolver
Creates a new ClosedFormSolver.
ClosedFormUnivariateDistribution<NumberType extends java.lang.Number> - Interface in gov.sandia.cognition.statistics
Defines the functionality associated with a closed-form scalar distribution.
Cluster<ClusterType> - Interface in gov.sandia.cognition.learning.algorithm.clustering.cluster
The Cluster interface defines the general functionality of a cluster, which is just the ability to get the members of the cluster.
cluster - Variable in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.AbstractClusterHierarchyNode
The cluster associated with the node.
ClusterCentroidDivergenceFunction<DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
The ClusterCentroidDivergenceFunction class implements the distance between two clusters by computing the distance between the cluster's centroid.
ClusterCentroidDivergenceFunction() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCentroidDivergenceFunction
Creates a new instance of ClusterCompleteLinkDivergenceFunction.
ClusterCentroidDivergenceFunction(DivergenceFunction<? super DataType, ? super DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCentroidDivergenceFunction
Creates a new instance of ClusterCompleteLinkDivergenceFunction using the given divergence function for elements.
ClusterCompleteLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
The ClusterCompleteLinkDivergenceFunction class implements the complete linkage distance metric between two clusters.
ClusterCompleteLinkDivergenceFunction() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCompleteLinkDivergenceFunction
Creates a new instance of ClusterCompleteLinkDivergenceFunction.
ClusterCompleteLinkDivergenceFunction(DivergenceFunction<? super DataType, ? super DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCompleteLinkDivergenceFunction
Creates a new instance of ClusterCompleteLinkDivergenceFunction using the given divergence function for elements.
clusterCounts - Variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
The current number of elements assigned to each cluster.
ClusterCreator<ClusterType extends Cluster<DataType>,DataType> - Interface in gov.sandia.cognition.learning.algorithm.clustering.cluster
The ClusterCreator defines the functionality of a class that can create a new cluster from a given collection of members of that cluster.
clusterDistances - Variable in class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer
The distances between clusters.
ClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.function.cost
Computes the objective measure for a clustering algorithm, based on the internal "distortion" of each cluster.
ClusterDistortionMeasure() - Constructor for class gov.sandia.cognition.learning.function.cost.ClusterDistortionMeasure
Creates a new instance of ClusterDistortionMeasure
ClusterDistortionMeasure(ClusterDivergenceFunction<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.function.cost.ClusterDistortionMeasure
Creates a new instance of ClusterDistortionMeasure
ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> - Interface in gov.sandia.cognition.learning.algorithm.clustering.divergence
The ClusterDivergenceFunction interface defines a function that computes the divergence between a cluster and some other object.
clusterDivergenceFunction - Variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The divergence function used to find the distance between two clusters.
clusterHierarchically(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
 
clusterHierarchically(Collection<? extends DataType>) - Method in interface gov.sandia.cognition.learning.algorithm.clustering.hierarchy.BatchHierarchicalClusterer
Performs hierarchical clustering on the given elements.
clusterHierarchically(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
 
ClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> - Interface in gov.sandia.cognition.learning.algorithm.clustering.hierarchy
Defines a node in a hierarchy of clusters.
ClusterMeanLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
The ClusterMeanLinkDivergenceFunction class implements the mean linkage distance metric between two clusters.
ClusterMeanLinkDivergenceFunction() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterMeanLinkDivergenceFunction
Creates a new instance of ClusterMeanLinkDivergenceFunction.
ClusterMeanLinkDivergenceFunction(DivergenceFunction<? super DataType, ? super DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterMeanLinkDivergenceFunction
Creates a new instance of ClusterMeanLinkDivergenceFunction using the given divergence function for elements.
clusters - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The clusters that have been found so far.
clusters - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The current set of clusters.
clusters - Variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
The current set of clusters.
clusters - Variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The current set of clusters all clusters created.
clusters - Variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
Point mass realizations from the base distribution.
clustersHierarchy - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The current set of hierarchical clusters.
clustersHierarchy - Variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The current set of hierarchical clusters created.
ClusterSingleLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
The ClusterSingleLinkDivergenceFunction class implements the complete linkage distance metric between two clusters.
ClusterSingleLinkDivergenceFunction() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterSingleLinkDivergenceFunction
Creates a new instance of ClusterSingleLinkDivergenceFunction.
ClusterSingleLinkDivergenceFunction(DivergenceFunction<? super DataType, ? super DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterSingleLinkDivergenceFunction
Creates a new instance of ClusterSingleLinkDivergenceFunction using the given divergence function for elements.
ClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> - Interface in gov.sandia.cognition.learning.algorithm.clustering.divergence
The ClusterToClusterDivergenceFunction defines a DivergenceFunction between two clusters of the same data type.
ClusterUpdaterTask() - Constructor for class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ClusterUpdaterTask
Creates a new instance of ClusterUpdaterTask
clusterUpdaterTasks - Variable in class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel
Tasks that update the values of the clusters for Gibbs sampling
clusterWeights - Variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Holds the cluster weights so that we don't have to re-allocate them each mcmcUpdate step.
CodeReview - Annotation Type in gov.sandia.cognition.annotation
The CodeReview annotation describes information about the last code review for a piece of code.
CodeReviewResponse - Annotation Type in gov.sandia.cognition.annotation
The CodeReviewResponse annotation contains information regarding a response to a CodeReview annotation.
CodeReviews - Annotation Type in gov.sandia.cognition.annotation
The CodeReviews annotation defines a container for one or more CodeReview annotations.
CognitiveModel - Interface in gov.sandia.cognition.framework
The CognitiveModel interface defines the basic functionality of a cognitive model.
CognitiveModelFactory - Interface in gov.sandia.cognition.framework
The CognitiveModelFactory interface defines an interface for creating a new CognitiveModel using a predefined set of CognitiveModules, as created by CognitiveModuleFactories.
CognitiveModelInput - Interface in gov.sandia.cognition.framework
The CognitiveModelInput defines the inteface for an input to a CognitiveModel.
CognitiveModelListener - Interface in gov.sandia.cognition.framework
The CognitiveModelListener interface is an event listener that listens for events on a CognitiveModel.
CognitiveModelLite - Class in gov.sandia.cognition.framework.lite
This class provides a lite implementation of the CognitiveModel interface.
CognitiveModelLite(CognitiveModuleFactory...) - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModelLite
Creates a new instance of CognitiveModelLite.
CognitiveModelLite(Iterable<? extends CognitiveModuleFactory>) - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModelLite
Creates a new instance of CognitiveModelLite.
CognitiveModelLiteFactory - Class in gov.sandia.cognition.framework.lite
The CognitiveModelLiteFactory defines a CognitiveModelFactory for creating CognitiveModelLite objects.
CognitiveModelLiteFactory() - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModelLiteFactory
Creates a new instance of CognitiveModelLiteFactory.
CognitiveModelLiteFactory(Collection<CognitiveModuleFactory>) - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModelLiteFactory
Creates a new instance of CognitiveModelLiteFactory.
CognitiveModelLiteState - Class in gov.sandia.cognition.framework.lite
The CognitiveModelLiteState class implements a CognitiveModelState object for the CognitiveModelLite.
CognitiveModelLiteState(int) - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Creates a new instance of CognitiveModelState.
CognitiveModelLiteState(int, int) - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Creates a new instance of CognitiveModelState.
CognitiveModelLiteState(CognitiveModelLiteState) - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Creates a new copy of a CognitiveModelLiteState.
CognitiveModelState - Interface in gov.sandia.cognition.framework
The CognitiveModelState interface defines the general functionality required of an object that represents the state of a CognitiveModel.
CognitiveModelStateChangeEvent - Class in gov.sandia.cognition.framework
The CognitiveModelStateChangeEvent class is an EventObject that contains the data pertaining to a change in the state of a CognitiveModel.
CognitiveModelStateChangeEvent(CognitiveModel, CognitiveModelState) - Constructor for class gov.sandia.cognition.framework.CognitiveModelStateChangeEvent
Creates a new instance of CognitiveModelStateChangeEvent.
CognitiveModule - Interface in gov.sandia.cognition.framework
The CognitiveModule interface defines the functionality of a general module that can be used in a CognitiveModel.
CognitiveModuleFactory - Interface in gov.sandia.cognition.framework
The CognitiveModuleFactory interface defines the functionality required by something that creates new CognitiveModules for a CognitiveModel.
CognitiveModuleFactoryLearner - Interface in gov.sandia.cognition.framework.learning
The CognitiveModuleFactoryLearner is an interface defining the functionality of an Object that can learn a CognitiveModuleFactory from a collection of input data.
CognitiveModuleSettings - Interface in gov.sandia.cognition.framework
The CogntiviteModuleSettings class defines the functionality required for the settings of a CognitiveModule.
CognitiveModuleState - Interface in gov.sandia.cognition.framework
The CognitiveModuleState defines the interface for the state of a CognitiveModule.
CognitiveModuleStateWrapper - Class in gov.sandia.cognition.framework.lite
The CognitiveModuleStateWrapper wraps some other object as a CognitiveModuleState object.
CognitiveModuleStateWrapper() - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModuleStateWrapper
Creates a new instance of CognitiveModuleStateWrapper.
CognitiveModuleStateWrapper(CloneableSerializable) - Constructor for class gov.sandia.cognition.framework.lite.CognitiveModuleStateWrapper
Creates a new instance of CognitiveModuleStateWrapper.
Cogxel - Interface in gov.sandia.cognition.framework
The interface for the fundamental unit of operation inside a CognitiveModel.
CogxelBooleanConverter - Class in gov.sandia.cognition.framework.learning.converter
Implements a CogxelConverter that encodes booleans as positive and negative values (+1/-1).
CogxelBooleanConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
Creates a new instance of CogxelBooleanConverter.
CogxelBooleanConverter(SemanticLabel) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
Creates a new instance of CogxelDoubleConverter.
CogxelBooleanConverter(SemanticLabel, SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
Creates a new instance of CogxelBooleanConverter.
CogxelBooleanConverter(SemanticLabel, SemanticIdentifierMap, CogxelFactory) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
Creates a new instance of CogxelBooleanConverter.
CogxelConverter<DataType> - Interface in gov.sandia.cognition.framework.learning.converter
The CogxelConverter interface defines the functionality required for an object to act as a converter from some DataType to and from a CogxelState object.
CogxelDoubleConverter - Class in gov.sandia.cognition.framework.learning.converter
The CogxelDoubleConverter class converts a Cogxel to and from a double value by using its activation.
CogxelDoubleConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Creates a new instance of CogxelDoubleConverter.
CogxelDoubleConverter(SemanticLabel) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Creates a new instance of CogxelDoubleConverter.
CogxelDoubleConverter(SemanticLabel, SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Creates a new instance of CogxelDoubleConverter.
CogxelDoubleConverter(SemanticLabel, SemanticIdentifierMap, CogxelFactory) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Creates a new instance of CogxelDoubleConverter.
CogxelDoubleConverter(CogxelDoubleConverter) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Creates a new instance of CogxelDoubleConverter.
CogxelFactory - Interface in gov.sandia.cognition.framework
The CogxelFactory interface defines the functionality required for an object to be used to create a Cogxel for a CognitiveModel.
CogxelInputOutputPairConverter<InputType,OutputType> - Class in gov.sandia.cognition.framework.learning.converter
The InputOutputPairCogxelConverter class implements a converter to and from Cogxels to InputOutputPair objects.
CogxelInputOutputPairConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter
Default constructor
CogxelInputOutputPairConverter(CogxelConverter<InputType>, CogxelConverter<OutputType>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter
Creates a new instance of InputOutputCogxelConverter.
CogxelInputOutputPairConverter(CogxelConverter<InputType>, CogxelConverter<OutputType>, SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter
Creates a new instance of InputOutputCogxelConverter.
CogxelMatrixConverter - Class in gov.sandia.cognition.framework.learning.converter
The CogxelVectorConverter implements a converter to convert Cogxels to and from Matrix objects.
CogxelMatrixConverter(Collection<? extends Iterable<SemanticLabel>>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter
Creates a new instance of CogxelMatrixConverter
CogxelMatrixConverter(ArrayList<CogxelVectorConverter>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter
Creates a new instance of CogxelMatrixConverter
CogxelMatrixConverter(ArrayList<CogxelVectorConverter>, SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter
Creates a new instance of CogxelMatrixConverter
CogxelMatrixConverter(CogxelMatrixConverter) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter
Copy constructor
CogxelState - Interface in gov.sandia.cognition.framework
Keeps a collection of Cogxels and some accessor methods.
CogxelStateLite - Class in gov.sandia.cognition.framework.lite
The CogxelStateLite class implements a CogxelState to be used with the CognitiveModelLite.
CogxelStateLite() - Constructor for class gov.sandia.cognition.framework.lite.CogxelStateLite
Creates a new instance of CogxelStateLite
CogxelStateLite(int) - Constructor for class gov.sandia.cognition.framework.lite.CogxelStateLite
Creates a new instance of CogxelStateLite with an expected initial capacity for the number of cogxels contained in it.
CogxelStateLite(CogxelState) - Constructor for class gov.sandia.cognition.framework.lite.CogxelStateLite
Creates a copy of a CogxelStateLite
CogxelTargetEstimatePairConverter<TargetType,EstimateType> - Class in gov.sandia.cognition.framework.learning.converter
CogxelConverter based on a TargetEstimatePair.
CogxelTargetEstimatePairConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter
Creates a new CogxelTargetEstimatePairConverter.
CogxelTargetEstimatePairConverter(CogxelConverter<TargetType>, CogxelConverter<EstimateType>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter
Creates a new CogxelTargetEstimatePairConverter with the given converters for each element of the pair.
CogxelTargetEstimatePairConverter(CogxelConverter<TargetType>, CogxelConverter<EstimateType>, SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter
Creates a new CogxelTargetEstimatePairConverter with the given converters for each element of the pair.
CogxelVectorCollectionConverter - Class in gov.sandia.cognition.framework.learning.converter
Converts a Collection of Vectors to and from a CogxelState
CogxelVectorCollectionConverter(Collection<CogxelVectorConverter>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter
Creates a new instance of CogxelVectorCollectionConverter
CogxelVectorCollectionConverter(CogxelVectorConverter...) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter
Creates a new instance of CogxelVectorCollectionConverter
CogxelVectorCollectionConverter(CogxelVectorCollectionConverter) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter
Copy Constructor
CogxelVectorConverter - Class in gov.sandia.cognition.framework.learning.converter
The CogxelVectorConverter implements a converter to convert Cogxels to and from Vector objects.
CogxelVectorConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new, empty instance of VectorCogxelMap.
CogxelVectorConverter(SemanticLabel...) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new CogxelVectorConverter from the given labels.
CogxelVectorConverter(Iterable<SemanticLabel>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new CogxelVectorConverter from the given labels.
CogxelVectorConverter(SemanticLabel[], SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new CogxelVectorConverter from the given SemanticIdentifierMap and SemanticLabels.
CogxelVectorConverter(Iterable<SemanticLabel>, SemanticIdentifierMap) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new CogxelVectorConverter from the given SemanticIdentifierMap and SemanticLabels.
CogxelVectorConverter(SemanticLabel[], SemanticIdentifierMap, VectorFactory<?>, CogxelFactory) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new CogxelVectorConverter
CogxelVectorConverter(Iterable<SemanticLabel>, SemanticIdentifierMap, VectorFactory<?>, CogxelFactory) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new CogxelVectorConverter.
CogxelVectorConverter(CogxelVectorConverter) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates a new copy of the given CogxelVectorConverter.
CogxelWeightedInputOutputPairConverter<InputType,OutputType> - Class in gov.sandia.cognition.framework.learning.converter
A CogxelConverter for creating WeightedInputOutputPairs
CogxelWeightedInputOutputPairConverter() - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter
Creates a new instance of CogxelWeightedInputOutputPairConverter
CogxelWeightedInputOutputPairConverter(CogxelConverter<InputType>, CogxelConverter<OutputType>, CogxelConverter<Double>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter
Creates a new instance of CogxelWeightedInputOutputPairConverter
CogxelWeightedInputOutputPairConverter(CogxelWeightedInputOutputPairConverter<InputType, OutputType>) - Constructor for class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter
Copy constructor
CollectionUtil - Class in gov.sandia.cognition.collection
The CollectionUtil class implements static methods for dealing with Collection and Iterable objects.
CollectionUtil() - Constructor for class gov.sandia.cognition.collection.CollectionUtil
 
COLLINEAR_TOLERANCE - Static variable in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear
Tolerance below which to consider something zero, 0.0
columnIndices - Variable in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Part of the compressed Yale format.
Combinations - Class in gov.sandia.cognition.math
Enumerates all the combinations on a given number of items sampled from a larger set without considering order, that is, (1,2) is the same as (2,1).
Combinations(int, int) - Constructor for class gov.sandia.cognition.math.Combinations
Creates a new instance of Combinations
Combinations.AbstractCombinationsIterator<IteratorType extends Combinations.AbstractCombinationsIterator<IteratorType,ClassType>,ClassType> - Class in gov.sandia.cognition.math
Partial implementation of a CombinationsIterator.
Combinations.IndexIterator - Class in gov.sandia.cognition.math
Iterator that returns the index into a set: 0, 1, 2, ...
Combinations.SubsetIterator<ClassType> - Class in gov.sandia.cognition.math
Creates a new instance of SubsetIterator, one that returns the elements from a given set
combineHash(HashFunction, boolean, byte[]...) - Static method in class gov.sandia.cognition.hash.HashFunctionUtil
Cascades the hash codes
CombineSummarizer() - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.CombineSummarizer
Creates a new CombineSummarizer.
CombineSummarizer() - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.CombineSummarizer
Creates a new CombineSummarizer.
COMMENT_LINE_PREFIX - Static variable in class gov.sandia.cognition.math.matrix.VectorReader
The start of a comment line has the "#" string at the beginning.
CommonDocumentTextualConverterFactory - Class in gov.sandia.cognition.text.convert
A utility class for creating common document-text converters.
CommonDocumentTextualConverterFactory() - Constructor for class gov.sandia.cognition.text.convert.CommonDocumentTextualConverterFactory
 
CommonTermWeighterFactory - Class in gov.sandia.cognition.text.term.vector.weighter
A factory for well-known weighting schemes.
CommunityComparisons<NodeNameType> - Class in gov.sandia.cognition.graph.community
This class implements various comparisons of partitionings of a graph (or the resulting communities)
CommunityComparisons(NodePartitioning<NodeNameType>, NodePartitioning<NodeNameType>) - Constructor for class gov.sandia.cognition.graph.community.CommunityComparisons
Initializes this with the input partitionings of the same underlying set
CommunityMetrics - Class in gov.sandia.cognition.graph.community
This class stores several static methods for computing metrics specific to a graph and a set of communities.
CommunityMetrics() - Constructor for class gov.sandia.cognition.graph.community.CommunityMetrics
 
compact() - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap
Removes entries from the map with value of 0.0
compact() - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
compact() - Method in interface gov.sandia.cognition.math.matrix.InfiniteVector
Removes the zero elements from the vector.
compact() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix
Compact the memory used by the matrix, getting rid of any zero elements
compact() - Method in class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix
 
compact() - Method in class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix
 
compact() - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
Compacts the SparseVector, getting rid of any zero'ed elements.
comparator - Variable in class gov.sandia.cognition.math.geometry.KDTree
Comparator of this node to determine less than, greater than, or equality.
comparator - Variable in class gov.sandia.cognition.math.geometry.KDTree.PairFirstVectorizableIndexComparator
Embedded comparator for the Vectorizable argument.
compare(T, T) - Method in class gov.sandia.cognition.collection.DefaultComparator
 
compare(Number, Number) - Method in class gov.sandia.cognition.collection.NumberComparator
 
compare(Pair<? extends Vectorizable, ?>, Pair<? extends Vectorizable, ?>) - Method in class gov.sandia.cognition.math.geometry.KDTree.PairFirstVectorizableIndexComparator
 
compare(Vectorizable, Vectorizable) - Method in class gov.sandia.cognition.math.matrix.VectorizableIndexComparator
 
compare(ReceiverOperatingCharacteristic.DataPoint, ReceiverOperatingCharacteristic.DataPoint) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.DataPoint.Sorter
Sorts ROCDataPoints in ascending order according to their falsePositiveRate (x-axis), used in Arrays.sort() method
compare(WeightedValue<?>, WeightedValue<?>) - Method in class gov.sandia.cognition.util.DefaultWeightedValue.WeightComparator
 
compareTimes(Collection<? extends Callable<ResultType>>) - Static method in class gov.sandia.cognition.algorithm.ParallelUtil
Compares the times needed by running the tasks sequentially versus parallel.
compareTimes(Collection<? extends Callable<ResultType>>, ThreadPoolExecutor) - Static method in class gov.sandia.cognition.algorithm.ParallelUtil
Compares the times needed by running the tasks sequentially versus parallel.
compareTo(SemanticIdentifier) - Method in class gov.sandia.cognition.framework.AbstractSemanticIdentifier
compareTo(DefaultSemanticLabel) - Method in class gov.sandia.cognition.framework.DefaultSemanticLabel
Takes a label and compares that label to this one.
compareTo(SemanticIdentifier) - Method in interface gov.sandia.cognition.framework.SemanticIdentifier
compareTo(KNearestNeighborExhaustive<InputType, OutputType>.Neighbor) - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive.Neighbor
 
compareTo(SuccessiveOverrelaxation<InputType>.Entry) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry
Compares this entry to another one by comparing the weights.
compareTo(KDTree.Neighborhood<VectorType, DataType, PairType>.Neighbor<VectorType, DataType, PairType>) - Method in class gov.sandia.cognition.math.geometry.KDTree.Neighborhood.Neighbor
 
compareTo(LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
 
compareTo(MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
compareTo(MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
compareTo(MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
compareTo(UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
compareTo(Double) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LineSegment
 
compareTo(AdaptiveRejectionSampling.Point) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.Point
 
compareTo(Duration) - Method in class gov.sandia.cognition.time.DefaultDuration
 
compareTo(Temporal) - Method in class gov.sandia.cognition.util.AbstractTemporal
 
completeSolver() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver
 
completeSolver() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver
 
completeSolver() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
Called after the final iteration.
completeSolver() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer
 
completeSolver() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver
 
ComplexNumber - Class in gov.sandia.cognition.math
Represents a complex number in a rectangular manner, explicitly storing the real and imaginary portions: real + j*imaginary
ComplexNumber() - Constructor for class gov.sandia.cognition.math.ComplexNumber
Creates a new instance of ComplexNumber with zero magnitude.
ComplexNumber(double, double) - Constructor for class gov.sandia.cognition.math.ComplexNumber
Creates a new instance of ComplexNumber using the specified complex parts
ComplexNumber(ComplexNumber) - Constructor for class gov.sandia.cognition.math.ComplexNumber
Copy constructor
componentCount - Variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
The number of components to create from the analysis.
components - Variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
The matrix of components for the function.
compose(Quaternion) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Multiplies this * other and returns the result.
composeEquals(Quaternion) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Multiplies this = this * other, thus modifying this object.
CompositeBatchLearnerPair<InputType,IntermediateType,OutputType> - Class in gov.sandia.cognition.learning.algorithm
Composes together a pair of batch (typically unsupervised) learners.
CompositeBatchLearnerPair() - Constructor for class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
Creates a new, empty CompositeBatchLearnerPair.
CompositeBatchLearnerPair(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends IntermediateType>>, BatchLearner<? super Collection<? extends IntermediateType>, ? extends Evaluator<? super IntermediateType, ? extends OutputType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
Creates a new CompositeBatchLearnerPair with the given two learner.
CompositeCategorizer<InputType,IntermediateType,CategoryType> - Class in gov.sandia.cognition.learning.function.categorization
Composes a preprocessor function with a categorizer.
CompositeCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer
Creates a new CompositeCategorizer with the preprocessor and categorizer set to null.
CompositeCategorizer(Evaluator<? super InputType, ? extends IntermediateType>, Categorizer<? super IntermediateType, ? extends CategoryType>) - Constructor for class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer
Creates a new CompositeCategorizer.
CompositeEvaluatorList<InputType,OutputType> - Class in gov.sandia.cognition.evaluator
Implements the composition of a list of evaluators.
CompositeEvaluatorList() - Constructor for class gov.sandia.cognition.evaluator.CompositeEvaluatorList
Creates a new CompositeEvaluatorList with an empty list of evaluators.
CompositeEvaluatorList(Evaluator<?, ?>...) - Constructor for class gov.sandia.cognition.evaluator.CompositeEvaluatorList
Creates a new CompositeEvaluatorList from the given array of evaluators.
CompositeEvaluatorList(Collection<? extends Evaluator<?, ?>>) - Constructor for class gov.sandia.cognition.evaluator.CompositeEvaluatorList
Creates a new CompositeEvaluatorList from the given collection of evaluators.
CompositeEvaluatorPair<InputType,IntermediateType,OutputType> - Class in gov.sandia.cognition.evaluator
Implements a composition of two evaluators.
CompositeEvaluatorPair() - Constructor for class gov.sandia.cognition.evaluator.CompositeEvaluatorPair
Creates a new CompositeEvalutor.
CompositeEvaluatorPair(Evaluator<? super InputType, ? extends IntermediateType>, Evaluator<? super IntermediateType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.evaluator.CompositeEvaluatorPair
Creates a new CompositeEvaluatorPair from the two given evaluators.
CompositeEvaluatorTriple<InputType,FirstIntermediateType,SecondIntermediateType,OutputType> - Class in gov.sandia.cognition.evaluator
Implements a composition of three evaluators.
CompositeEvaluatorTriple() - Constructor for class gov.sandia.cognition.evaluator.CompositeEvaluatorTriple
Creates a new CompositeEvalutorTriple.
CompositeEvaluatorTriple(Evaluator<? super InputType, ? extends FirstIntermediateType>, Evaluator<? super FirstIntermediateType, ? extends SecondIntermediateType>, Evaluator<? super SecondIntermediateType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.evaluator.CompositeEvaluatorTriple
Creates a new CompositeEvaluatorTriple from the three given evaluators.
CompositeLocalGlobalTermWeighter - Class in gov.sandia.cognition.text.term.vector.weighter
Composes together local and global term weighters along with a normalizer.
CompositeLocalGlobalTermWeighter() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.CompositeLocalGlobalTermWeighter
Creates a new CompositeLocalGlobalTermWeighter.
CompositeLocalGlobalTermWeighter(LocalTermWeighter, GlobalTermWeighter, TermWeightNormalizer) - Constructor for class gov.sandia.cognition.text.term.vector.weighter.CompositeLocalGlobalTermWeighter
Creates a new CompositeLocalGlobalTermWeighter with the given weighting schemes.
compress() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
This method is provided so that the calling programmer can explicitly declare when a matrix should be compressed to the compressed Yale format.
compress() - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
The compressed representation should allow for quicker mathematical operations, but does not permit editing the values in the vector.
ComputableDistribution<DomainType> - Interface in gov.sandia.cognition.statistics
A type of Distribution that has an associated distribution function, either a PDF or PMF.
compute(GradientDescendable, Collection<? extends InputOutputPair<? extends Vector, Vector>>) - Static method in class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction.Cache
Computes often-used parameters of a sum-squared error term
compute(Collection<? extends DefaultBinaryConfusionMatrix>, double) - Static method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Computes the ConfidenceIntervals for the given Collection of ConfusionMatrices
compute(Collection<? extends TargetEstimatePair<? extends Double, ? extends Double>>) - Static method in class gov.sandia.cognition.learning.performance.MeanAbsoluteErrorEvaluator
Computes the mean absolute error for the given pairs of values.
compute(Collection<? extends TargetEstimatePair<? extends Double, ? extends Double>>) - Static method in class gov.sandia.cognition.learning.performance.MeanSquaredErrorEvaluator
Computes the mean squared error for the given pairs of values.
compute(Collection<? extends TargetEstimatePair<? extends DataType, ? extends DataType>>) - Static method in class gov.sandia.cognition.learning.performance.MeanZeroOneErrorEvaluator
Computes the mean zero-one loss for the given pairs of values.
compute(Collection<? extends TargetEstimatePair<? extends Double, ? extends Double>>) - Static method in class gov.sandia.cognition.learning.performance.RootMeanSquaredErrorEvaluator
Computes the mean squared error for the given pairs of values.
compute(UnivariateDistribution<NumberType>, double) - Static method in class gov.sandia.cognition.statistics.bayesian.BayesianCredibleInterval
Creates a Bayesian credible interval by inverting the given CDF.
compute() - Method in class gov.sandia.cognition.statistics.ChiSquaredSimilarity
Computes the chi-squared statistic of the two vectors.
compute() - Method in class gov.sandia.cognition.statistics.KullbackLeiblerDivergence
Computes the Kullback--Leibler Divergence.
compute(Vector, Distribution<Vector>, Random, double) - Static method in class gov.sandia.cognition.statistics.montecarlo.MultivariateCumulativeDistributionFunction
Computes a multi-variate cumulative distribution for a given input according to the given distribution.
compute() - Method in class gov.sandia.cognition.statistics.TransferEntropy
Computes the transfer entropy value.
computeAcceptanceProbability(ParameterType, Iterable<? extends ObservationType>) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
 
computeAcceptanceProbability(ParameterType, Iterable<? extends ObservationType>) - Method in interface gov.sandia.cognition.statistics.bayesian.RejectionSampling.Updater
Computes the probability of accepting the parameter for the given data.
computeAllDistancesForNode(int) - Method in class gov.sandia.cognition.graph.GraphMetrics
Helper which computes Dijkstra's Algorithm for the input node and returns all of the distances to all other nodes from this node.
computeAreaUnderConvexHull() - Method in class gov.sandia.cognition.statistics.method.ConvexReceiverOperatingCharacteristic
Computes the area under the convex hull
computeAreaUnderCurve(ReceiverOperatingCharacteristic) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Computes the "pessimistic" area under the ROC curve using the top-left rectangle method for numerical integration.
computeAreaUnderCurveTopLeft(Collection<ReceiverOperatingCharacteristic.DataPoint>) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Computes the Area Under Curve for an x-axis sorted Collection of ROC points using the top-left rectangle method for numerical integration.
computeAreaUnderCurveTrapezoid(Collection<ReceiverOperatingCharacteristic.DataPoint>) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Computes the Area Under Curve for an x-axis sorted Collection of ROC points using the top-left rectangle method for numerical integration.
computeAscendingArray(Collection<? extends Number>) - Static method in class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence
Returns an array of ascending sorted values from the given Collection
computeBackwardProbabilities(Vector, Vector, double) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the backward probability recursion.
computeBackwardProbabilities(ArrayList<Vector>, ArrayList<WeightedValue<Vector>>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the backward-probabilities for the given observation likelihoods and the weights from the alphas.
computeBestGainAndThreshold(Collection<? extends InputOutputPair<? extends Vectorizable, OutputType>>, int, DefaultDataDistribution<OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
Computes the best gain and threshold for a given dimension using the computeSplitGain method for each potential split point of values for the given dimension.
computeBestGainAndThreshold(Collection<? extends InputOutputPair<? extends Vectorizable, OutputType>>, int, DefaultDataDistribution<OutputType>, ArrayList<DefaultWeightedValue<OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
Computes the best gain and threshold for a given dimension using the computeSplitGain method for each potential split point of values for the given dimension.
computeBestGainThreshold(Collection<? extends InputOutputPair<? extends Vectorizable, Double>>, int, double) - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdVarianceLearner
Computes the best information gain-threshold pair for the given dimension on the given data.
computeBounds(Collection<? extends DataType>) - Method in class gov.sandia.cognition.math.geometry.Quadtree
Computes the bounding rectangle of a given collection of points.
computeCentralMoment(Iterable<? extends Number>, double, int) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the desired biased estimate central moment of the given dataset.
computeChiSquare(int, int, ArrayList<Double>) - Static method in class gov.sandia.cognition.statistics.method.FriedmanConfidence.Statistic
Computes the chi-square error for the rank means
computeClusterDistances() - Method in class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer
Computes the distances between the clusters.
computeConditionalProbability(Collection<InputType>, CategoryType) - Method in class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Computes the class conditional for the given inputs at the given category assuming that each input feature is conditionally independent of all other features.
computeConditionalProbability(Collection<DataType>, DataType, ComputableDistribution<Collection<DataType>>, ComputableDistribution<Collection<DataType>>) - Method in class gov.sandia.cognition.statistics.bayesian.ConditionalProbability
Computes the conditional probability between a collection of objects and a new object.
computeConditionalProbability(DataType, DataType, ComputableDistribution<DataType>, ComputableDistribution<Collection<DataType>>) - Method in class gov.sandia.cognition.statistics.bayesian.ConditionalProbability
Computes the conditional probability between two objects.
computeConditionalProbabilityWhenDataTypeHasHistoricalData(DataType, DataType, ComputableDistribution<DataType>, ComputableDistribution<DataType>) - Method in class gov.sandia.cognition.statistics.bayesian.ConditionalProbability
Computes the conditional probability between two objects.
computeConductance(DirectedNodeEdgeGraph<NodeNameType>, Set<NodeNameType>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
 
computeConfidenceInterval(Collection<Boolean>, double) - Method in class gov.sandia.cognition.statistics.method.BernoulliConfidence
Computes the ConfidenceInterval for the Bernoulli parameter based on the given data and the desired level of confidence.
computeConfidenceInterval(double, int, double) - Static method in class gov.sandia.cognition.statistics.method.BernoulliConfidence
Computes the ConfidenceInterval for the Bernoulli parameter based on the given data and the desired level of confidence.
computeConfidenceInterval(double, double, int, double) - Method in class gov.sandia.cognition.statistics.method.BernoulliConfidence
 
computeConfidenceInterval(Collection<Double>, double) - Method in class gov.sandia.cognition.statistics.method.ChebyshevInequality
Computes the Chebyshev Inequality for the given level of confidence.
computeConfidenceInterval(double, double, int, double) - Method in class gov.sandia.cognition.statistics.method.ChebyshevInequality
Computes the Chebyshev Inequality for the given level of confidence.
computeConfidenceInterval(DataType, double) - Method in interface gov.sandia.cognition.statistics.method.ConfidenceIntervalEvaluator
Computes a confidence interval for a given dataset and confidence (power) level
computeConfidenceInterval(double, double, int, double) - Method in interface gov.sandia.cognition.statistics.method.ConfidenceIntervalEvaluator
Computes the confidence interval given the mean and variance of the samples, number of samples, and corresponding confidence interval
computeConfidenceInterval(Collection<DataType>, ConfidenceIntervalEvaluator<Collection<? extends Number>>, double) - Static method in class gov.sandia.cognition.statistics.method.FieldConfidenceInterval
Computes a FieldConfidenceInterval for each Double/double Field in the given data.
computeConfidenceInterval(Collection<DataType>, ArrayList<Field>, ConfidenceIntervalEvaluator<Collection<? extends Number>>, double) - Static method in class gov.sandia.cognition.statistics.method.FieldConfidenceInterval
Computes a FieldConfidenceInterval for the given Fields in the given data
computeConfidenceInterval(Collection<? extends Number>, double) - Method in class gov.sandia.cognition.statistics.method.GaussianConfidence
 
computeConfidenceInterval(UnivariateDistribution<?>, int, double) - Static method in class gov.sandia.cognition.statistics.method.GaussianConfidence
Computes the Gaussian confidence interval given a distribution of data, number of samples, and corresponding confidence interval
computeConfidenceInterval(double, double, int, double) - Method in class gov.sandia.cognition.statistics.method.GaussianConfidence
 
computeConfidenceInterval(Collection<Double>, double) - Method in class gov.sandia.cognition.statistics.method.MarkovInequality
Computes the Markov Inequality Bound for the given data at the given confidence level.
computeConfidenceInterval(double, int, double) - Static method in class gov.sandia.cognition.statistics.method.MarkovInequality
Computes the Markov Inequality Bound for the given data at the given confidence level.
computeConfidenceInterval(double, double, int, double) - Method in class gov.sandia.cognition.statistics.method.MarkovInequality
 
computeConfidenceInterval(Collection<? extends Number>, double) - Method in class gov.sandia.cognition.statistics.method.StudentTConfidence
 
computeConfidenceInterval(double, double, int, double) - Method in class gov.sandia.cognition.statistics.method.StudentTConfidence
 
computeConjuctiveProbability(Collection<InputType>, CategoryType) - Method in class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Computes the conjunctive probability of the inputs and the category.
computeConvexNull(ReceiverOperatingCharacteristic) - Static method in class gov.sandia.cognition.statistics.method.ConvexReceiverOperatingCharacteristic
Computes the convex hull of a ROC curve
computeCorrelation(Collection<? extends Number>, Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the correlation coefficient in a single pass.
computeCumulativeProbabilityValue() - Method in class gov.sandia.cognition.statistics.ChiSquaredSimilarity
Computes the chi-squared similarity statistic, then uses that to compute a cumulative probability.
computeCumulativeValue(int, ClosedFormDiscreteUnivariateDistribution<? super Integer>) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Computes the CDF value for the given PMF for the input.
computeDecay(LinearBinaryCategorizer, Vector, boolean, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Computes the decay scalar for the existing weight vector.
computeDecay(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Computes the decay scalar for the existing weights.
computeDecay(LinearBinaryCategorizer, Vector, boolean, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
 
computeDecay(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
 
computeDPrime(ReceiverOperatingCharacteristic.DataPoint) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Computes the value of d-prime given a datapoint
computeEffectiveParticles(DataDistribution<ParameterType>) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter
 
computeEffectiveParticles(DataDistribution<ParameterType>) - Method in interface gov.sandia.cognition.statistics.bayesian.ParticleFilter
Computes the effective number of particles.
computeEntropy(Iterable<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the information-theoretic entropy of the PMF in bits (base 2).
computeEquivalentSampleSize(BetaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator
 
computeEquivalentSampleSize(BetaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator
 
computeEquivalentSampleSize(BeliefType) - Method in interface gov.sandia.cognition.statistics.bayesian.conjugate.ConjugatePriorBayesianEstimator
Computes the equivalent sample size of using the given prior.
computeEquivalentSampleSize(GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator
 
computeEquivalentSampleSize(GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator
 
computeEquivalentSampleSize(DirichletDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator
 
computeEquivalentSampleSize(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator
 
computeEquivalentSampleSize(NormalInverseWishartDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator
 
computeEquivalentSampleSize(GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator
 
computeEquivalentSampleSize(ParetoDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator
 
computeEquivalentSampleSize(UnivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator
 
computeEquivalentSampleSize(NormalInverseGammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator
 
computeEvidenceProbabilty(Collection<InputType>) - Method in class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Computes the probability of the given inputs.
computeExponent() - Method in class gov.sandia.cognition.math.ComplexNumber
Computes the natural-base exponent of the complex number, such that this = log(exp(this)) = exp(log(this))
computeForwardProbabilities(Vector, Vector, boolean) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the recursive solution to the forward probabilities of the HMM.
computeForwardProbabilities(ArrayList<Vector>, boolean) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the forward probabilities for the given observation likelihood sequence.
computeGaussianSampler(Iterable<? extends ObservationType>, Random, int) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Computes a Gaussian sample for the parameter, assuming it has is a Double, using importance sampling.
computeGraphPermanance(DirectedNodeEdgeGraph<NodeNameType>, GraphMetrics<NodeNameType>, NodePartitioning<NodeNameType>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
Computes the average permanence for the partitioning of the entire graph
computeKurtosis(Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the biased excess kurtosis of the given dataset.
computeLines() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.AbstractEnvelope
Computes the line segments comprising this Envelope
computeLines() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LowerEnvelope
Recomputes the line segments that comprise the upper envelope
computeLines() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
Recomputes the line segments that comprise the upper envelope
computeLocalWeights(Vectorizable) - Method in class gov.sandia.cognition.text.term.vector.weighter.local.AbstractLocalTermWeighter
 
computeLocalWeights(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.local.BinaryLocalTermWeighter
 
computeLocalWeights(Vectorizable) - Method in interface gov.sandia.cognition.text.term.vector.weighter.local.LocalTermWeighter
Computes the new local weights for a given document.
computeLocalWeights(Vector) - Method in interface gov.sandia.cognition.text.term.vector.weighter.local.LocalTermWeighter
Computes the new local weights for a given document.
computeLocalWeights(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.local.LogLocalTermWeighter
 
computeLocalWeights(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.local.NormalizedLogLocalTermWeighter
 
computeLocalWeights(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.local.TermFrequencyLocalTermWeighter
 
computeLogImportanceValue(ParameterType) - Method in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater
 
computeLogImportanceValue(ParameterType) - Method in interface gov.sandia.cognition.statistics.bayesian.ImportanceSampling.Updater
Computes the parameter's importance weight.
computeLogLikelihood(ParameterType, Iterable<? extends ObservationType>) - Method in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater
 
computeLogLikelihood(ParameterType, Iterable<? extends ObservationType>) - Method in interface gov.sandia.cognition.statistics.bayesian.ImportanceSampling.Updater
Computes the log likelihood of the data given the parameter
computeLogLikelihood(ParameterType, Iterable<? extends ObservationType>) - Method in interface gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm.Updater
Computes the log likelihood of the data given the parameter
computeLogLikelihood(ParameterType, ObservationType) - Method in interface gov.sandia.cognition.statistics.bayesian.ParticleFilter.Updater
Computes the log likelihood of the parameter and the observation.
computeLogPosterior(Vector, CategoryType) - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer
Computes the log-posterior probability that the input belongs to the given category.
computeMaximum(Iterable<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Finds the maximum value of a data set.
computeMean(Iterable<? extends RingType>) - Static method in class gov.sandia.cognition.math.MultivariateStatisticsUtil
Computes the arithmetic mean (average, expectation, first central moment) of a dataset
computeMean(Iterable<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the arithmetic mean (average, expectation, first central moment) of a dataset
computeMeanAndCovariance(Iterable<? extends Vectorizable>) - Static method in class gov.sandia.cognition.math.MultivariateStatisticsUtil
Computes the mean and unbiased covariance Matrix of a multivariate data set.
computeMeanAndVariance(Iterable<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the mean and unbiased variance of a Collection of data using the one-pass approach.
computeMeasurementBelief(MultivariateGaussian, Vector, Matrix) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
Updates the measurement belief by computing the Kalman gain and incorporating the innovation into the estimate
computeMedian(Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the median of the given data.
computeMinAndMax(Iterable<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the minimum and maximum of a set of data in a single pass.
computeMinimum(Iterable<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Finds the minimum value of a data set.
computeMinimumDifference(VectorType) - Method in class gov.sandia.cognition.math.geometry.KDTree
Computes the minimum absolute difference between the given key and the "first" value stored in this subtree for the index given by the embedded comparator.
computeModularity(DirectedNodeEdgeGraph<NodeNameType>, Set<Set<NodeNameType>>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
Computes the modularity of the input graph into the input set of communities.
computeModularity(Set<Set<NodeNameType>>, GraphMetrics<NodeNameType>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
Computes the modularity of the graph (whose metrics were passed in) into the input set of communities.
computeModularity(DirectedNodeEdgeGraph<NodeNameType>, NodePartitioning<NodeNameType>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
Computes the modularity of the input graph into the input set of communities.
computeModularity(NodePartitioning<NodeNameType>, GraphMetrics<NodeNameType>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
 
computeMultipleObservationLogLikelihood(Collection<? extends Collection<? extends ObservationType>>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the log-likelihood of the observation sequences, given the current HMM's parameterization.
computeMultipleObservationLogLikelihood(Collection<? extends Collection<? extends ObservationType>>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
 
computeNaturalLogarithm() - Method in class gov.sandia.cognition.math.ComplexNumber
Computes the natural-base logarithm of the complex number, such that this = log(exp(this)) = exp(log(this))
computeNeighborhood(InputType) - Method in class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor
Computes the neighbors to the input key.
computeNeighborhood(InputType) - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive
 
computeNeighborhood(InputType) - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree
 
computeNullHypothesisProbabilities(int, Matrix) - Method in class gov.sandia.cognition.statistics.method.NemenyiConfidence.Statistic
Computes null-hypothesis probability for the (i,j) treatment comparison
computeNullHypothesisProbabilities(ArrayList<Integer>, Matrix) - Method in class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic
Computes null-hypothesis probability for the (i,j) treatment comparison
computeNullHypothesisProbability(double) - Static method in class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Computes the p-value for the test, given the z-value
computeNullHypothesisProbability(double) - Static method in class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence.Statistic
Computes the p-value given the z-value
computeObjective() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
Gets the total objective, which is the squared error plus the regularization terms.
computeObservationLikelihoods(ObservationType) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the conditionally independent likelihoods for each state given the observation.
computeObservationLikelihoods(ObservationType, Vector) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the conditionally independent likelihoods for each state given the observation.
computeObservationLikelihoods(Collection<? extends ObservationType>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the conditionally independent likelihoods for each state given the observation sequence.
computeObservationLogLikelihood(Collection<? extends ObservationType>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the log-likelihood of the observation sequence, given the current HMM's parameterization.
computeObservationLogLikelihood(Collection<? extends ObservationType>, Collection<Integer>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the log-likelihood that the given observation sequence was generated by the given sequence of state indices.
computeOneNodePermanence(GraphMetrics<NodeNameType>, NodePartitioning<NodeNameType>, NodeNameType, DirectedNodeEdgeGraph<NodeNameType>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
 
computeOneNodePermanenceById(GraphMetrics<NodeNameType>, NodePartitioning<NodeNameType>, int, DirectedNodeEdgeGraph<NodeNameType>) - Static method in class gov.sandia.cognition.graph.community.CommunityMetrics
Computes the permanence for one node in the graph.
computeOptimalScale(Iterable<? extends ObservationType>) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Computes the optimal scale factor for enveloping the conjunctive distribution with the sampler function given the data
computeOptimalThreshold(ReceiverOperatingCharacteristic) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Determines the DataPoint, and associated threshold, that simultaneously maximizes the value of Area=TruePositiveRate+TrueNegativeRate, usually the upper-left "knee" on the ROC curve.
computeOptimalThreshold(ReceiverOperatingCharacteristic, double, double) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Determines the DataPoint, and associated threshold, that simultaneously maximizes the value of Area=TruePositiveRate+TrueNegativeRate, usually the upper-left "knee" on the ROC curve.
computeOuterProductDataMatrix(ArrayList<? extends Vector>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Computes the outer-product Matrix of the given set of data: XXt = [ x1 x2 ...
computeOutputMean(Collection<? extends InputOutputPair<?, ? extends Number>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Computes the mean of the output data.
computeOutputVariance(Collection<? extends InputOutputPair<?, ? extends Number>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Computes the variance of the output of a given set of input-output pairs.
computePairwiseTestResults(Collection<? extends Collection<? extends Number>>, NullHypothesisEvaluator<Collection<? extends Number>>) - Method in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic
Computes the pair-wise confidence test results
computeParameterGradient(Vector) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
 
computeParameterGradient(Vector) - Method in interface gov.sandia.cognition.learning.algorithm.gradient.GradientDescendable
Computes the derivative of the function about the input with respect to the parameters of the function.
computeParameterGradient(VectorizableVectorFunction, Vector, double) - Static method in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
Computes a forward-differences approximation to the parameter Jacobian
computeParameterGradient(Vector) - Method in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
Computes a forward-differences approximation to the parameter Jacobian
computeParameterGradient(InputType) - Method in interface gov.sandia.cognition.learning.algorithm.gradient.ParameterGradientEvaluator
Computes the derivative of the output with respect to the parameters for a particular input.
computeParameterGradient(GradientDescendable) - Method in class gov.sandia.cognition.learning.function.cost.AbstractParallelizableCostFunction
 
computeParameterGradient(GradientDescendable) - Method in interface gov.sandia.cognition.learning.function.cost.DifferentiableCostFunction
Differentiates function with respect to its parameters.
computeParameterGradient(GradientDescendable) - Method in class gov.sandia.cognition.learning.function.cost.MeanSquaredErrorCostFunction
 
computeParameterGradient(GradientDescendable) - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer
 
computeParameterGradient(Double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction
 
computeParameterGradient(Vector) - Method in class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork
 
computeParameterGradient(Vector) - Method in class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
 
computeParameterGradient(Vector) - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant
 
computeParameterGradient(Matrix, Vector) - Static method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant
Computes the parameter gradient of the given matrix post-multiplied by the input Vector
computeParameterGradient(Vector) - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminantWithBias
 
computeParameterGradient(Vector) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
 
computeParameterGradientAmalgamate(Collection<Object>) - Method in interface gov.sandia.cognition.learning.function.cost.ParallelizableCostFunction
Amalgamates the linear components of the cost gradient function into a single Vector.
computeParameterGradientAmalgamate(Collection<Object>) - Method in class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction
 
computeParameterGradientPartial(GradientDescendable) - Method in interface gov.sandia.cognition.learning.function.cost.ParallelizableCostFunction
Computes the partial (linear) component of the cost function gradient.
computeParameterGradientPartial(GradientDescendable) - Method in class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction
 
computePercentile(Collection<? extends Number>, double) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the percentile value of the given data.
computePercentiles(Collection<? extends Number>, double...) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the given percentiles of the given data.
computePolynomial(LineBracket, EvaluatorType) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolatorPolynomial
Fits the interpolating polynomial to the given LineBracket
computePolynomial(LineBracket, DifferentiableUnivariateScalarFunction) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorHermiteCubic
 
computePolynomial(LineBracket, DifferentiableUnivariateScalarFunction) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorHermiteParabola
 
computePolynomial(LineBracket, Evaluator<Double, Double>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorLinear
 
computePolynomial(LineBracket, Evaluator<Double, Double>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorParabola
 
computePosterior(Collection<InputType>, CategoryType) - Method in class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Computes the posterior probability of the inputs for the given category.
computePosterior(Vector, CategoryType) - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer
Computes the posterior probability that the input belongs to the given category.
computePosterior(ObservationType, CategoryType) - Method in class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer
Computes the posterior of the observation given the category.
computePosteriorLogLikelihood(Iterable<? extends ObservationType>) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
Computes the posterior log likelihood of the data given the clusters and the prior probability of the clustering from a Chinese Restaurant Process
computePosteriorLogLikelihood(int, double) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
Computes the posterior log likelihood of the Sample
computePredictionCovariance(Matrix, Matrix) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
Computes the prediction covariance from the Jacobian and believe covariance
computeRandomVariableLikelihoods(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel.PDF
Computes the likelihoods of the underlying distributions
computeRandomVariableProbabilities(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel.PDF
Computes the probability distribution that the input was generated by the underlying distributions
computeRescaling(LinearBinaryCategorizer, Vector, boolean, double, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Computes the rescaling for the new weight vector.
computeRescaling(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Computes the rescaling for the new weights.
computeRootMeanSquaredError(Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the Root mean-squared (RMS) error between the data and its mean.
computeRootMeanSquaredError(Collection<? extends Number>, double) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the Root mean-squared (RMS) error between the data and its mean
computeSampleSize(double, double) - Static method in class gov.sandia.cognition.statistics.method.BernoulliConfidence
Computes the number of samples needed to estimate the Bernoulli parameter "p" (mean) within "accuracy" with probability at least "confidence".
computeScaleFactor(Vector, Vector) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
Computes the conjugate gradient parameter for the particular update scheme.
computeScaleFactor(Vector, Vector) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerFletcherReeves
 
computeScaleFactor(Vector, Vector) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerLiuStorey
 
computeScaleFactor(Vector, Vector) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerPolakRibiere
 
computeSequenceParameters() - Method in class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm
Computes the gammas and A matrices for each sequence.
computeSimplexInputSum() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead
Computes the sum of input values in the simplex
computeSkewness(Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the unbiased skewness of the dataset.
computeSplitGain(DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
Computes the gain of a given split.
computeSplitGain(DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdGiniImpurityLearner
Computes the split gain by computing the Gini impurity for the given split.
computeSplitGain(DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdHellingerDistanceLearner
Computes the split gain by computing the mean Hellinger distance for the given split.
computeSplitGain(DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>, DefaultDataDistribution<OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner
 
computeStandardDeviation(Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the standard deviation of a dataset, which is the square root of the unbiased variance.
computeStandardDeviation(Collection<? extends Number>, double) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the standard deviation of a dataset, which is the square root of the unbiased variance.
computeStateObservationLikelihood(Vector, Vector, double) - Static method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the probability of the various states at a time instance given the observation sequence.
computeStateObservationLikelihood(ArrayList<WeightedValue<Vector>>, ArrayList<WeightedValue<Vector>>, double) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the probabilities of the various states over time given the observation sequence.
computeStateObservationLikelihood(ArrayList<WeightedValue<Vector>>, ArrayList<WeightedValue<Vector>>, double) - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
 
computeStatistics() - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic
Computes useful statistical information associated with the ROC curve
computeSum(Iterable<? extends RingType>) - Static method in class gov.sandia.cognition.math.MultivariateStatisticsUtil
Computes the arithmetic sum of the dataset
computeSum(Iterable<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the arithmetic sum of the dataset
computeSumSquaredDifference(Iterable<? extends Number>, double) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the sum-squared difference between the data and a target
computeTemporaryMessage(int) - Method in class gov.sandia.cognition.graph.inference.SumProductBeliefPropagation
 
computeTemporaryMessage(int) - Method in class gov.sandia.cognition.graph.inference.SumProductDirectedPropagation
Private helper that computes the temporary message for the specified edge for the current iteration going in the specified direction
computeTemporaryMessage(int) - Method in class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
Private helper that computes the temporary message for the specified edge for the current iteration going in the specified direction (a different message for each direction)
computeTestStatistics(int, ArrayList<Double>, double) - Method in class gov.sandia.cognition.statistics.method.NemenyiConfidence.Statistic
Computes the test statistic for all treatments
computeTestStatistics(ArrayList<Integer>, ArrayList<Double>, double) - Method in class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic
Computes the test statistic for all treatments
computeTransitions(Vector, Vector, Vector) - Static method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the stochastic transition-probability matrix from the given probabilities.
computeTransitions(ArrayList<WeightedValue<Vector>>, ArrayList<WeightedValue<Vector>>, ArrayList<Vector>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the stochastic transition-probability matrix from the given probabilities.
computeTransitions(ArrayList<WeightedValue<Vector>>, ArrayList<WeightedValue<Vector>>, ArrayList<Vector>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
 
ComputeTransitionsTask() - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ComputeTransitionsTask
Default constructor.
computeTransitionTasks - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
ComputeTransitionsTasks.
computeTreatmentRankMeans(Collection<? extends Collection<? extends Number>>) - Static method in class gov.sandia.cognition.statistics.method.FriedmanConfidence
Computes the mean rank of the treatments
computeU(double, int, double, int) - Static method in class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Computes the U-statistic, the minimum rank sum above "chance"
computeUpdate(LinearBinaryCategorizer, Vector, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Compute the update weight in the linear case.
computeUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Compute the update weight in the linear case.
computeUpdate(LinearBinaryCategorizer, Vector, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
 
computeUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
 
computeUpdate(double, double, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron
Compute the update value (tau) for the algorithm.
computeUpdate(LinearBinaryCategorizer, Vector, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron
 
computeUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron
 
computeUpdate(double, double, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.LinearSoftMargin
 
computeUpdate(double, double, double, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.QuadraticSoftMargin
 
computeUpdate(LinearBinaryCategorizer, Vector, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron
 
computeUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron
 
computeUpdate(boolean, double) - Static method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron
Computes the update weight for the given actual category and predicted value according to the Perceptron update rule.
computeUpdate(LinearBinaryCategorizer, Vector, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineRampPassiveAggressivePerceptron
 
computeUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineRampPassiveAggressivePerceptron
 
computeUpdate(LinearBinaryCategorizer, Vector, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
 
computeUpdate(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean, double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
 
computeVariance(Collection<? extends Vector>) - Static method in class gov.sandia.cognition.math.MultivariateStatisticsUtil
Computes the variance (second central moment, squared standard deviation) of a dataset.
computeVariance(Collection<? extends Vector>, Vector) - Static method in class gov.sandia.cognition.math.MultivariateStatisticsUtil
Computes the variance (second central moment, squared standard deviation) of a dataset
computeVariance(Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the unbiased variance (second central moment, squared standard deviation) of a dataset.
computeVariance(Collection<? extends Number>, double) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the unbiased variance (second central moment, squared standard deviation) of a dataset
computeVector(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
Transforms the scaleFactor into a multidimensional Vector using the direction
computeViterbiRecursion(Vector, Vector) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the Viterbi recursion for a given "delta" and "b"
computeViterbiRecursion(Vector, Vector) - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
 
computeWeightedCentralMoment(Iterable<? extends WeightedValue<? extends Number>>, double, int) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the desired biased estimate central moment of the given dataset.
computeWeightedKurtosis(Collection<? extends WeightedValue<? extends Number>>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the biased excess kurtosis of the given dataset.
computeWeightedMean(Iterable<? extends WeightedValue<? extends Number>>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the arithmetic mean (average, expectation, first central moment) of a dataset.
computeWeightedMeanAndCovariance(Iterable<? extends WeightedValue<? extends Vectorizable>>) - Static method in class gov.sandia.cognition.math.MultivariateStatisticsUtil
Computes the mean and biased covariance Matrix of a multivariate weighted data set.
computeWeightedMeanAndVariance(Iterable<? extends WeightedValue<? extends Number>>) - Static method in class gov.sandia.cognition.math.UnivariateStatisticsUtil
Computes the mean and unbiased variance of a Collection of data using the one-pass approach.
computeWeightedOutputMean(Collection<? extends InputOutputPair<?, ? extends Number>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Computes the mean of the output data.
computeWeightedZSquared(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.PDF
Computes the weighted z-value (deviate) of the given input.
computeWithPartialSums() - Method in class gov.sandia.cognition.statistics.TransferEntropy
Computes the transfer entropy value and returns a map of the states with their corresponding partial sums.
computeZ(double, int, int) - Static method in class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Computes the z-value, used in the UnivariateGaussian CDF
computeZ(double, int) - Static method in class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence.Statistic
Computes the z-value from the T-statistic and numNonZero value
computeZSquared(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Computes the z value squared, such that p(x) = coefficient * exp{-0.5*z^2}
ConcurrentCognitiveModule - Interface in gov.sandia.cognition.framework.concurrent
The ConcurrentCognitiveModule interface extends the functionality of CognitiveModule to support concurrent module evaluation within a CognitiveModel.
conditionalDistribution - Variable in class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter
Distribution from which to pull the parameters.
conditionalDistribution - Variable in class gov.sandia.cognition.statistics.DefaultDistributionParameter
Distribution from which to pull the parameters.
conditionalPriorPredictive - Variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Base predictive distribution that determines the value of the new cluster weighting during the Gibbs sampling.
ConditionalProbability<DataType> - Class in gov.sandia.cognition.statistics.bayesian
A class for finding the conditional probability of two elements, or one element and a collection of other elements.
ConditionalProbability() - Constructor for class gov.sandia.cognition.statistics.bayesian.ConditionalProbability
Constructor for new Conditional Probability object.
conditionals - Variable in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer
The mapping of category to the conditional distribution for the category with one probability density function for each dimension.
conditionNumber() - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition
 
conditionNumber() - Method in interface gov.sandia.cognition.math.matrix.decomposition.SingularValueDecomposition
Returns the condition number of the underlying matrix, which is simply the ratio of the largest to smallest singular value
confidence - Variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
The confidence to use for updating.
confidence - Variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
The confidence to use for updating.
confidence - Variable in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
The confidence statistic generated from the underlying performance statistics.
CONFIDENCE_REGION - Static variable in class gov.sandia.cognition.math.UnivariateSummaryStatistics
Region of the confidence interval, 0.95.
ConfidenceInterval - Class in gov.sandia.cognition.statistics.method
Contains a specification for a confidence interval, that is, the solution of Pr{ lowerBound <= x(centralValue) <= upperBound } >= confidence
ConfidenceInterval(double, double, double, double, int) - Constructor for class gov.sandia.cognition.statistics.method.ConfidenceInterval
Creates a new instance of ConfidenceInterval
ConfidenceInterval(ConfidenceInterval) - Constructor for class gov.sandia.cognition.statistics.method.ConfidenceInterval
Copy constructor
ConfidenceIntervalEvaluator<DataType> - Interface in gov.sandia.cognition.statistics.method
Computes a confidence interval for a given dataset and confidence (power) level
ConfidenceStatistic - Interface in gov.sandia.cognition.statistics.method
An interface that describes the result of a statistical confidence test.
ConfidenceTestAssumptions - Annotation Type in gov.sandia.cognition.statistics.method
Describes the assumptions and other information of a statistical confidence test.
ConfidenceWeightedBinaryCategorizer - Interface in gov.sandia.cognition.learning.function.categorization
Interface for a confidence-weighted binary categorizer, which defines a distribution over linear binary categorizers.
ConfidenceWeightedDiagonalDeviation - Class in gov.sandia.cognition.learning.algorithm.confidence
An implementation of the Standard Deviation (Stdev) algorithm for learning a confidence-weighted categorizer.
ConfidenceWeightedDiagonalDeviation() - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
Creates a new ConfidenceWeightedDiagonalVariance with default parameters.
ConfidenceWeightedDiagonalDeviation(double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
Creates a new ConfidenceWeightedDiagonalVariance with the given parameters.
ConfidenceWeightedDiagonalDeviationProject - Class in gov.sandia.cognition.learning.algorithm.confidence
An implementation of the Standard Deviation (Stdev) algorithm for learning a confidence-weighted categorizer.
ConfidenceWeightedDiagonalDeviationProject() - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviationProject
Creates a new ConfidenceWeightedDiagonalDeviationProject with default parameters.
ConfidenceWeightedDiagonalDeviationProject(double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviationProject
Creates a new ConfidenceWeightedDiagonalDeviationProject with the given parameters.
ConfidenceWeightedDiagonalVariance - Class in gov.sandia.cognition.learning.algorithm.confidence
An implementation of the Variance algorithm for learning a confidence-weighted linear categorizer.
ConfidenceWeightedDiagonalVariance() - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
Creates a new ConfidenceWeightedDiagonalVariance with default parameters.
ConfidenceWeightedDiagonalVariance(double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
Creates a new ConfidenceWeightedDiagonalVariance with the given parameters.
ConfidenceWeightedDiagonalVarianceProject - Class in gov.sandia.cognition.learning.algorithm.confidence
An implementation of the Variance algorithm for learning a confidence-weighted linear categorizer.
ConfidenceWeightedDiagonalVarianceProject() - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVarianceProject
Creates a new ConfidenceWeightedDiagonalVarianceProject with default parameters.
ConfidenceWeightedDiagonalVarianceProject(double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVarianceProject
Creates a new ConfidenceWeightedDiagonalVarianceProject with the given parameters.
configure(Map<OutputType, Double>, Map<OutputType, Integer>) - Method in interface gov.sandia.cognition.learning.algorithm.tree.PriorWeightedNodeLearner
Configure the node learner with prior weights and training counts.
configure(Map<OutputType, Double>, Map<OutputType, Integer>) - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner
 
ConfusionMatrix<CategoryType> - Interface in gov.sandia.cognition.learning.performance.categorization
An interface for a general confusion matrix, which is used to tabulate a set of actual category values against the values predicted for those categories.
ConfusionMatrixPerformanceEvaluator<InputType,CategoryType> - Class in gov.sandia.cognition.learning.performance.categorization
A performance evaluator that builds a confusion matrix.
ConfusionMatrixPerformanceEvaluator() - Constructor for class gov.sandia.cognition.learning.performance.categorization.ConfusionMatrixPerformanceEvaluator
Creates a new ConfusionMatrixPerformanceEvaluator with a default factory behind it.
ConfusionMatrixPerformanceEvaluator(Factory<? extends ConfusionMatrix<CategoryType>>) - Constructor for class gov.sandia.cognition.learning.performance.categorization.ConfusionMatrixPerformanceEvaluator
Creates a new ConfusionMatrixPerformanceEvaluator using the given factory.
confusions - Variable in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
The backing map of confusion matrix entries.
conjuctive - Variable in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater
Defines the parameter that connects the conditional and prior distributions.
conjuctive - Variable in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Defines the parameter that connects the conditional and prior distributions.
conjugate() - Method in class gov.sandia.cognition.math.ComplexNumber
Switches the sign of the imaginary part of this complex number.
conjugateEquals() - Method in class gov.sandia.cognition.math.ComplexNumber
Switches the sign of the imaginary part of this complex number.
ConjugateGradientMatrixSolver - Class in gov.sandia.cognition.learning.algorithm.minimization.matrix
Implements a matrix solver using Conjugate Gradient.
ConjugateGradientMatrixSolver(Vector, Vector) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver
Initializes a conjugate gradient solver with the minimum values
ConjugateGradientMatrixSolver(Vector, Vector, double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver
Initializes a conjugate gradient solver with some additional parameters
ConjugateGradientMatrixSolver(Vector, Vector, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver
Initializes a conjugate gradient solver with all user-definable parameters
ConjugateGradientWithPreconditionerMatrixSolver - Class in gov.sandia.cognition.learning.algorithm.minimization.matrix
Implements a matrix solver using Conjugate Gradient with a preconditioner.
ConjugateGradientWithPreconditionerMatrixSolver(Vector, Vector) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver
Initializes a steepest-descent solver with the minimum values
ConjugateGradientWithPreconditionerMatrixSolver(Vector, Vector, double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver
Initializes a steepest-descent solver with some additional parameters
ConjugateGradientWithPreconditionerMatrixSolver(Vector, Vector, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver
Initializes a steepest-descent solver with all user-definable parameters
ConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> - Interface in gov.sandia.cognition.statistics.bayesian.conjugate
A Bayesian Estimator that makes use of conjugate priors, which is a mathematical trick when the conditional and the prior result a posterior that is the same type as the prior.
ConjugatePriorBayesianEstimatorPredictor<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> - Interface in gov.sandia.cognition.statistics.bayesian.conjugate
A conjugate prior estimator that also has a closed-form predictive posterior.
constant - Variable in class gov.sandia.cognition.learning.function.kernel.PolynomialKernel
The constant for the polynomial.
constant - Variable in class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
The constant used in the sigmoid.
ConstantEvaluator<OutputType> - Class in gov.sandia.cognition.learning.function
The ConstantEvaluator class implements an Evaluator that always returns the same output value.
ConstantEvaluator() - Constructor for class gov.sandia.cognition.learning.function.ConstantEvaluator
Creates a new ConstantEvaluator.
ConstantEvaluator(OutputType) - Constructor for class gov.sandia.cognition.learning.function.ConstantEvaluator
Creates a new ConstantEvaluator.
ConstantLearner<ValueType> - Class in gov.sandia.cognition.learning.algorithm.baseline
A learner that always returns the same value as the result.
ConstantLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.baseline.ConstantLearner
Creates a new ConstantLearner with a null value.
ConstantLearner(ValueType) - Constructor for class gov.sandia.cognition.learning.algorithm.baseline.ConstantLearner
Creates a new ConstantLearner with the given value;
constantValue - Variable in class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction
The constant value is what the constant weight biases the function toward when there is near zero weight.
constantWeight - Variable in class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction
The constant weight is used as a weight for the constant value that is added to the result to bias the function to the constant value.
constructor - Variable in class gov.sandia.cognition.factory.ConstructorBasedFactory
The constructor to use to create new objects.
ConstructorBasedFactory<CreatedType> - Class in gov.sandia.cognition.factory
The ConstructorBasedFactory class implements a Factory that takes a constructor and parameters to that constructor used to create new objects.
ConstructorBasedFactory(Constructor<? extends CreatedType>, Object...) - Constructor for class gov.sandia.cognition.factory.ConstructorBasedFactory
Creates a new ConstructorBasedFactory from the given constructor and parameters.
consume(KeyType, double) - Method in interface gov.sandia.cognition.math.matrix.InfiniteVector.KeyValueConsumer
Consumes one entry in the infinite vector.
consume(int, double) - Method in interface gov.sandia.cognition.math.matrix.Vector.IndexValueConsumer
Consumes one entry in the vector.
consumeClusters(Collection<GaussianCluster>) - Method in class gov.sandia.cognition.learning.function.vector.GaussianContextRecognizer
Uses the given clusters to populate the internal clusters of this
contains(Object) - Method in class gov.sandia.cognition.collection.DefaultMultiCollection
 
contains(int) - Method in class gov.sandia.cognition.collection.IntegerSpan
Determines if the given value is within the inclusive bounds
contains(Object) - Method in class gov.sandia.cognition.collection.IntegerSpan
 
contains(Termable) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
 
contains(Term) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
Returns true if the given term is in the stop list.
contains(String) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
Returns true if the given word is in the stop list.
contains(Termable) - Method in interface gov.sandia.cognition.text.term.filter.StopList
Determines if the given term is contained in this stop list.
containsKey(KeyType) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
containsKey(Object) - Method in class gov.sandia.cognition.collection.DynamicArrayMap
Runs in O(1).
containsKey(int) - Method in class gov.sandia.cognition.collection.DynamicArrayMap
Returns true if this is a valid key in the mapping.
containsKey(KeyType) - Method in interface gov.sandia.cognition.collection.NumericMap
Determines if this map contains the given key.
containsNode(NodeNameType) - Method in class gov.sandia.cognition.graph.DenseMemoryGraph
 
containsNode(NodeNameType) - Method in interface gov.sandia.cognition.graph.DirectedNodeEdgeGraph
Returns whether or not the graph contains the specified vertex.
containsValue(Object) - Method in class gov.sandia.cognition.collection.DynamicArrayMap
Runs in O(n).
CONTENT_TYPE - Static variable in class gov.sandia.cognition.text.document.extractor.TextDocumentExtractor
The content type is "text/plain".
convergence(Vector, Double, Vector, Vector, double) - Static method in class gov.sandia.cognition.learning.algorithm.minimization.MinimizationStoppingCriterion
Tests for convergence on approximately zero slope and nonmovement along the x-axis
convert(int) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
Converts the given index from zero-based world to circular world
convert(InputType) - Method in class gov.sandia.cognition.text.convert.AbstractMultiTextualConverter
 
convert(InputType) - Method in class gov.sandia.cognition.text.convert.AbstractSingleTextualConverter
 
convert(InputType) - Method in interface gov.sandia.cognition.text.convert.MultiTextualConverter
Convert the input object into zero or more textual objects.
convert(InputType) - Method in interface gov.sandia.cognition.text.convert.SingleTextualConverter
Convert an input into its single textual form.
convertAll(Iterable<? extends InputType>) - Method in class gov.sandia.cognition.text.convert.AbstractMultiTextualConverter
 
convertAll(Iterable<? extends InputType>) - Method in class gov.sandia.cognition.text.convert.AbstractSingleTextualConverter
 
convertAll(Iterable<? extends InputType>) - Method in interface gov.sandia.cognition.text.convert.TextualConverter
Convert the given input objects into zero or more textual objects.
converter - Variable in class gov.sandia.cognition.data.convert.vector.NumberConverterToVectorAdapter
The converter to adapt for use with Vectors.
converter - Variable in class gov.sandia.cognition.text.convert.SingleToMultiTextualConverterAdapter
The single text converter being wrapped.
convertFromBytes(byte[]) - Static method in class gov.sandia.cognition.io.ObjectSerializationHandler
Takes a byte array produced by convertToBytes and returns the Object from the serialized byte array.
convertFromBytes(byte[]) - Method in class gov.sandia.cognition.io.serialization.AbstractStreamSerializationHandler
 
convertFromBytes(byte[]) - Method in interface gov.sandia.cognition.io.serialization.StreamSerializationHandler
Converts the first given object in the given byte array.
convertFromRotationMatrix(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets the quaternion to be equivalent to the given a 3-by-3 rotation matrix.
convertFromString(String) - Method in class gov.sandia.cognition.io.serialization.AbstractTextSerializationHandler
 
convertFromString(String) - Method in interface gov.sandia.cognition.io.serialization.TextSerializationHandler
Converts an object from its serialized string representation.
convertFromString(String) - Static method in class gov.sandia.cognition.io.XStreamSerializationHandler
Attempts to read an Object from the given string.
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression.Function
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.LinearCombinationFunction
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.AtanFunction
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.CosineFunction
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminant
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminantWithBias
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction
Sets the value of the exponent
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Converts this function from its parameters, which consists of the threshold value
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction
Converts a vector into the index to select from the vector.
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionLinearDiscriminant
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.vector.FeedforwardNeuralNetwork
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.vector.GeneralizedLinearModel
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant
Uploads a matrix from a row-stacked vector of parameters.
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminantWithBias
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
Assigns the values in the provided vector into this.
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
uploads a matrix from a column-stacked vector of parameters, so that v(k) = A(i,j) = A( k%M, k/M )
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
uploads a matrix from a column-stacked vector of parameters, so that v(k) = A(i,j) = A( k%M, k/M )
convertFromVector(Vector) - Method in interface gov.sandia.cognition.math.matrix.Matrix
uploads a matrix from a column-stacked vector of parameters, so that v(k) = A(i,j) = A( k%M, k/M )
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
 
convertFromVector(DenseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Incorporates the parameters in the given vector back into the object.
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
convertFromVector(Vector) - Method in interface gov.sandia.cognition.math.matrix.Vectorizable
Converts the object from a Vector of parameters.
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.MutableDouble
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.MutableInteger
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.MutableLong
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.signals.LinearDynamicalSystem
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.math.signals.MovingAverageFilter
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.BernoulliDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution
Sets the parameters of the distribution
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Sets the parameter of the chi-square PDF
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.DirichletDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Sets the parameters of the distribution
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.GeometricDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
Sets the parameters of the distribution from a 2-dimensional Vector with ( logNormalMean logNormalVariance )
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Sets the parameters of this PDF, which must be a 1-dimensional Vector containing the degrees of freedom
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
 
convertFromVector(Vector) - Method in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
 
convertInputFromInternal(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased.InternalFunction
Converts the internal x-axis value to real-world x-axis value
convertInputFromInternal(InputOutputSlopeTriplet) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased.InternalFunction
Converts an InternalFunction InputOutputSlopeTriplet to a real-world InputOutputSlopeTriplet by unreflection and flipping the sign of the slope (if the direction of search was backward).
convertInputToInternal(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased.InternalFunction
Converts a real-world "x" value to the internal values used inside the search algorithm.
convertTo2D(DataType) - Method in class gov.sandia.cognition.math.geometry.Quadtree
Converts the given item into a two-dimensional vector.
convertToBoolean(Number) - Method in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
Converts the given number to a boolean value by determining if it is closer to the number representing true or the number representing false.
convertToBytes(Serializable) - Static method in class gov.sandia.cognition.io.ObjectSerializationHandler
Converts the given Object into an array of bytes.
convertToBytes(SerializedType) - Method in class gov.sandia.cognition.io.serialization.AbstractStreamSerializationHandler
 
convertToBytes(SerializedType) - Method in interface gov.sandia.cognition.io.serialization.StreamSerializationHandler
Converts the given object to bytes.
convertToComplex(Collection<Double>) - Static method in class gov.sandia.cognition.math.signals.FourierTransform
Converts the Collection of real data to complex numbers
convertToNumber(Boolean) - Method in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
Converts the given boolean to a number using the
convertToRotationMatrix() - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Converts the quaternion to a 3-by-3 rotation matrix.
convertToString(SerializedType) - Method in class gov.sandia.cognition.io.serialization.AbstractTextSerializationHandler
 
convertToString(SerializedType) - Method in interface gov.sandia.cognition.io.serialization.TextSerializationHandler
Converts a given object to its serialized string representation.
convertToString(Serializable) - Static method in class gov.sandia.cognition.io.XStreamSerializationHandler
Writes the given object to a String.
convertToVector() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
 
convertToVector() - Method in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
 
convertToVector() - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression.Function
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.LinearCombinationFunction
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.AtanFunction
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.CosineFunction
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminant
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminantWithBias
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction
Returns the value of the exponent
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Converts this function into its parameters, which consists of the threshold value
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction
Converts the index to select into a vector (of length 1).
convertToVector() - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionLinearDiscriminant
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.vector.FeedforwardNeuralNetwork
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.vector.GeneralizedLinearModel
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant
Creates a row-stacked version of the discriminant.
convertToVector() - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminantWithBias
 
convertToVector() - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
 
convertToVector() - Method in class gov.sandia.cognition.math.matrix.AbstractVector
Returns this.
convertToVector() - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
convertToVector() - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
convertToVector() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Creates a column-stacked version of this, so that v(k) = A(i,j) = v(j*M+i)
convertToVector() - Method in interface gov.sandia.cognition.math.matrix.Matrix
Creates a column-stacked version of this, so that v(k) = A(i,j) = v(j*M+i)
convertToVector() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
convertToVector() - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
 
convertToVector() - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
convertToVector() - Method in interface gov.sandia.cognition.math.matrix.Vectorizable
Converts the object to a vector.
convertToVector() - Method in class gov.sandia.cognition.math.MutableDouble
 
convertToVector() - Method in class gov.sandia.cognition.math.MutableInteger
 
convertToVector() - Method in class gov.sandia.cognition.math.MutableLong
 
convertToVector() - Method in class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
 
convertToVector() - Method in class gov.sandia.cognition.math.signals.LinearDynamicalSystem
 
convertToVector() - Method in class gov.sandia.cognition.math.signals.MovingAverageFilter
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.BernoulliDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution
Gets the parameters of the distribution
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Returns the parameter of the chi-square PDF
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.DirichletDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Gets the parameters of the distribution
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.GeometricDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
Returns a 2-dimensional Vector with ( logNormalMean logNormalVariance )
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Returns the parameters of this PDF, which is a 1-dimensional Vector containing the degrees of freedom
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
 
convertToVector() - Method in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
 
convertToVector(Iterable<? extends Termable>) - Method in class gov.sandia.cognition.text.term.vector.BagOfWordsTransform
Converts a given list of terms to a vector by counting the occurrence of each term.
convertToVector(Iterable<? extends Termable>, VectorFactory<?>) - Method in class gov.sandia.cognition.text.term.vector.BagOfWordsTransform
Converts a given list of terms to a vector by counting the occurrence of each term.
convertToVector(Iterable<? extends Termable>, TermIndex, VectorFactory<?>) - Static method in class gov.sandia.cognition.text.term.vector.BagOfWordsTransform
Converts a given list of terms to a vector by counting the occurrence of each term.
ConvexReceiverOperatingCharacteristic - Class in gov.sandia.cognition.statistics.method
Computes the convex hull of the Receiver Operating Characteristic (ROC), which a mathematician might call a "concave down" function.
convolve(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Convolves this Gaussian with the other Gaussian.
convolve(UnivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
Convolves this Gaussian with the other Gaussian.
cooleyTukeyFFT(ArrayList<ComplexNumber>) - Static method in class gov.sandia.cognition.math.signals.FourierTransform
Computes the Cooley-Tukey Radix-2 Fast Fourier Transform (FFT).
copy(boolean[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
Creates a new copy of the given array.
copy(int[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
Creates a new copy of the given array.
copy(long[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
Creates a new copy of the given array.
copy(double[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
Creates a new copy of the given array.
copy(T[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
Creates a new copy of the given array.
copyArray(double[][]) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Copies the values from the array into the Matrix
copyArray(double[]) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
Creates a DenseVector based on the given array values.
copyArray(double[]) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Copies the values from the array into the Vector
copyArray(int, int[], double[]) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a new vector of the given dimensionality by setting the values at the given indices.
copyColumnVectors(Collection<? extends Vectorizable>) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new matrix by copying the given set of column vectors.
copyColumnVectors(Vectorizable...) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new matrix by copying the given set of column vectors.
copyMap(int, Map<Integer, ? extends Number>) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a vector from the given map of indices to values.
copyMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseMatrixFactory
Creates a deep copy of m into a DenseMatrix and returns it.
copyMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDiagonalMatrixFactory
Creates a deep copy new Matrix given another, argument is unchanged
copyMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseMatrixFactory
Creates a deep copy new Matrix given another, argument is unchanged
copyMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a deep copy new Matrix given another, argument is unchanged
copyMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ
 
copyMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
 
copyMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ
 
copyRowVectors(Collection<? extends Vectorizable>) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new matrix by copying the given set of row vectors.
copyRowVectors(Vectorizable...) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new matrix by copying the given set of row vectors.
copyValues(double...) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Copies the values from the given doubles into a Vector
copyValues(Collection<? extends Number>) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Copies the values from the given Collection.
copyVector(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
 
copyVector(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
 
copyVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
 
copyVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
 
copyVector(Vector) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a deep copy new Vector given another, argument is unchanged
cosine(VectorType) - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
 
cosine(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
cosine(VectorType) - Method in interface gov.sandia.cognition.math.matrix.VectorSpace
Computes the cosine between two Vectors
CosineDeltaCategorizer<CategoryType> - Class in gov.sandia.cognition.learning.algorithm.delta
The Cosine Delta algorithm implementation.
CosineDeltaCategorizer(CosineDeltaCategorizer.Learner<CategoryType>, ArrayList<Double>, ArrayList<Double>) - Constructor for class gov.sandia.cognition.learning.algorithm.delta.CosineDeltaCategorizer
Constructor that takes learner, featureStddev, and featureMeans.
CosineDeltaCategorizer.Learner<CategoryType> - Class in gov.sandia.cognition.learning.algorithm.delta
Learner for a CosineDeltaCategorizer.
CosineDistanceMetric - Class in gov.sandia.cognition.learning.function.distance
The CosineDistanceMetric class implements a semimetric between two vectors based on the cosine between the vectors.
CosineDistanceMetric() - Constructor for class gov.sandia.cognition.learning.function.distance.CosineDistanceMetric
Creates a new instance of CosineDistanceMetric.
CosineFunction - Class in gov.sandia.cognition.learning.function.scalar
A closed-form cosine function.
CosineFunction() - Constructor for class gov.sandia.cognition.learning.function.scalar.CosineFunction
Creates a new instance of CosineFunction
CosineFunction(double, double) - Constructor for class gov.sandia.cognition.learning.function.scalar.CosineFunction
Creates a new instance of CosineFunction
CosineFunction(double, double, double) - Constructor for class gov.sandia.cognition.learning.function.scalar.CosineFunction
Creates a new instance of CosineFunction
CosineSimilarityFunction - Class in gov.sandia.cognition.text.term.vector
A vector cosine similarity function.
CosineSimilarityFunction() - Constructor for class gov.sandia.cognition.text.term.vector.CosineSimilarityFunction
Creates a new CosineSimilarityFunction.
CostFunction<EvaluatedType,CostParametersType> - Interface in gov.sandia.cognition.learning.function.cost
The CostFunction interface defines the interface to evaluate some object to determine its cost.
costFunction - Variable in class gov.sandia.cognition.statistics.method.DistributionParameterEstimator.DistributionWrapper
Cost function to use in the minimization procedure
costParameters - Variable in class gov.sandia.cognition.learning.function.cost.AbstractCostFunction
The parameters of the cost function.
CostSpeedupEnergyFunction<LabelType,NodeNameType> - Class in gov.sandia.cognition.graph.inference
This class trades memory usage (to store all of the costs) for compute time.
CostSpeedupEnergyFunction(NodeNameAwareEnergyFunction<LabelType, NodeNameType>) - Constructor for class gov.sandia.cognition.graph.inference.CostSpeedupEnergyFunction
Initializes this with the wrapped function and empty values for the pairwise costs (which are only computed and stored as needed).
couldWrite(File) - Static method in class gov.sandia.cognition.io.FileUtil
Attempts to determine if the application might be able to write to the given file, which may or may not already exists.
count - Variable in class gov.sandia.cognition.statistics.AbstractSufficientStatistic
Number of data points used to create this SufficientStatistic
counterFactory - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Factory for counting votes.
countNonZeros() - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
Computes the number of non-zero entries in this
countNonZeros() - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
countNonZeros() - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
 
countNonZeros() - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
 
countNonZeros() - Method in interface gov.sandia.cognition.math.matrix.Vector
Counts the number of non-zero entries in the vector.
countOutputValues(Iterable<? extends InputOutputPair<?, ? extends OutputType>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Creates a data histogram over the output values from the given data.
covariance - Variable in class gov.sandia.cognition.learning.function.categorization.DefaultConfidenceWeightedBinaryCategorizer
The covariance matrix.
covarianceDivisor - Variable in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
Term that divides the covariance sampled from the inverseWishart, must be greater than zero.
create() - Static method in class gov.sandia.cognition.data.convert.IdentityDataConverter
Convenience method to create a new IdentityDataConverter.
create(Evaluator<? super InputType, ? extends IntermediateType>, Evaluator<? super IntermediateType, ? extends OutputType>) - Static method in class gov.sandia.cognition.evaluator.CompositeEvaluatorPair
A convenience method for creating composite evaluators.
create(Evaluator<? super InputType, ? extends FirstIntermediateType>, Evaluator<? super FirstIntermediateType, ? extends SecondIntermediateType>, Evaluator<? super SecondIntermediateType, ? extends OutputType>) - Static method in class gov.sandia.cognition.evaluator.CompositeEvaluatorTriple
A convenience method for creating composite evaluators.
create(ForwardType, ReverseType) - Static method in class gov.sandia.cognition.evaluator.ForwardReverseEvaluatorPair
Convenience method for creating a new forward-reverse evaluator pair.
create() - Static method in class gov.sandia.cognition.evaluator.IdentityEvaluator
Convenience method for creating an identity evaluator.
create(Map<InputType, OutputType>) - Static method in class gov.sandia.cognition.evaluator.ValueMapper
Creates an evaluator who is backed by the given map.
create() - Method in class gov.sandia.cognition.factory.ConstructorBasedFactory
Creates a new object by calling the constructor inside the factory with the parameters it is configured to take.
create() - Method in class gov.sandia.cognition.factory.DefaultFactory
Creates a new object using the default constructor of the class that the factory contains.
create() - Method in interface gov.sandia.cognition.factory.Factory
Creates a new instance of an object.
create() - Method in class gov.sandia.cognition.factory.PrototypeFactory
Creates a new object by calling the clone method on the prototype in the factory.
create(ValueType) - Static method in class gov.sandia.cognition.learning.algorithm.baseline.ConstantLearner
Creates a new ConstantLearner.
create() - Static method in class gov.sandia.cognition.learning.algorithm.baseline.IdentityLearner
A convenience method for creating a IdentityLearner.
create(int, Random) - Static method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
Creates a new parallelized k-means clustering algorithm for vector data with the given number of clusters (k) and random number generator.
create(int, Semimetric<? super Vector>, Random) - Static method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
Creates a new parallelized k-means clustering algorithm for vector data with the given number of clusters (k), distance metric, and random number generator.
create() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
 
create(int) - Static method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Create a partitional clusterer, using Euclidean distance and a vector mean centroid cluster creator.
create(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends IntermediateType>>, BatchLearner<? super Collection<? extends IntermediateType>, ? extends Evaluator<? super IntermediateType, ? extends OutputType>>) - Static method in class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
Creates a new CompositeBatchLearnerPair from the given learners.
create(IncrementalLearner<? super InputOutputPair<? extends InputType, CategoryType>, MemberType>, int, double, Random) - Static method in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
Convenience method for creating an OnlineBaggingCategorizerLearner.
create(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends TransformedInputType>>, BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType, TransformedOutputType>>, ? extends Evaluator<? super TransformedInputType, ? extends TransformedOutputType>>, BatchLearner<? super Collection<? extends OutputType>, ? extends ReversibleEvaluator<OutputType, TransformedOutputType, ?>>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the three learners.
create(Evaluator<? super InputType, ? extends TransformedInputType>, BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType, TransformedOutputType>>, ? extends Evaluator<? super TransformedInputType, ? extends TransformedOutputType>>, ReversibleEvaluator<OutputType, TransformedOutputType, ?>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the predefined input and output transforms and the supervised learner.
create(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends TransformedInputType>>, BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType, TransformedOutputType>>, ? extends Evaluator<? super TransformedInputType, ? extends TransformedOutputType>>, ReversibleEvaluator<OutputType, TransformedOutputType, ?>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the unsupervised input transform learner, supervised learners, and output transform.
create(Evaluator<? super InputType, ? extends TransformedInputType>, BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType, TransformedOutputType>>, ? extends Evaluator<? super TransformedInputType, ? extends TransformedOutputType>>, BatchLearner<? super Collection<? extends OutputType>, ? extends ReversibleEvaluator<OutputType, TransformedOutputType, ?>>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the input transform, supervised learner, and unsupervised output transform learner.
create() - Static method in class gov.sandia.cognition.learning.data.DefaultInputOutputPair
Convenience method to create a new DefaultInputOutputPair.
create(InputType, OutputType) - Static method in class gov.sandia.cognition.learning.data.DefaultInputOutputPair
Convenience method to create a new DefaultInputOutputPair.
create(Collection<DataType>, Collection<DataType>) - Static method in class gov.sandia.cognition.learning.data.DefaultPartitionedDataset
Convenience method to create a new DefaultPartitionedDataset from the two given collections.
create() - Static method in class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
Convenience method for creating a new DefaultTargetEstimatePair.
create(TargetType, EstimateType) - Static method in class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
Convenience method for creating a new DefaultTargetEstimatePair.
create(ValueType, DiscriminantType) - Static method in class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair
Convenience method for creating a new DefaultValueDiscriminantPair with the given value and discriminant.
create() - Static method in class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
Convenience method to create a new, empty DefaultWeightedInputOutputPair.
create(InputType, OutputType, double) - Static method in class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
Convenience method to create a new DefaultWeightedInputOutputPair.
create() - Static method in class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
Convenience method for creating a new DefaultWeightedTargetEstimatePair.
create(TargetType, EstimateType) - Static method in class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
Convenience method for creating a new DefaultWeightedTargetEstimatePair.
create(TargetType, EstimateType, double) - Static method in class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
Convenience method for creating a new DefaultWeightedTargetEstimatePair.
create(ValueType, double) - Static method in class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant
Convenience method for creating a new DefaultWeightedValueDiscriminant with the given value and weight.
create(WeightedValue<? extends ValueType>) - Static method in class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant
Convenience method for creating a new DefaultWeightedValueDiscriminant with a shallow copy of the given the given value and weight.
create(Collection<? extends DataType>, int) - Static method in class gov.sandia.cognition.learning.data.SequentialDataMultiPartitioner
Creates a partition of the given data into "numPartition" roughly equal sets, preserving their pre-existing sequential ordering, with the nonzero remainder elements going into the final partition.
create(OutputType) - Static method in class gov.sandia.cognition.learning.function.ConstantEvaluator
Creates a new ConstantEvaluator for the given value.
create(DivergenceFunction<? super ValueType, ? super InputType>, Collection<ValueType>) - Static method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
Convenience method for creation a DivergeceEvaluator.
create(BatchLearner<DataType, ? extends Collection<ValueType>>, DivergenceFunction<? super ValueType, ? super InputType>) - Static method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator.Learner
Convenience method for creating a DivergencesEvaluator.Learner.
create(LearnerType) - Static method in class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper
A convenience method for creating the wrapper for a learner.
create(Iterable<? extends TargetEstimatePair<? extends Boolean, ? extends Boolean>>) - Static method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Creates a new DefaultBinaryConfusionMatrix from the given target-estimate pairs.
create(Iterable<? extends TargetEstimatePair<? extends Boolean, ? extends Boolean>>, boolean) - Static method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Creates a new DefaultBinaryConfusionMatrix from the given target-estimate pairs.
create() - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.Factory
 
create(DenseMatrix) - Static method in class gov.sandia.cognition.math.matrix.mtj.decomposition.CholeskyDecompositionMTJ
Creates a Cholesky decomposition of the symmetric positive definite matrix A.
create(DenseMatrix) - Static method in class gov.sandia.cognition.math.matrix.mtj.decomposition.EigenDecompositionRightMTJ
Creates a new instance of EigenDecompositionRightMTJ.
create(Matrix) - Static method in class gov.sandia.cognition.math.matrix.mtj.decomposition.SingularValueDecompositionMTJ
Creates a new instance of SingularValueDecompositionMTJ
create(Collection<? extends Number>) - Static method in class gov.sandia.cognition.math.UnivariateSummaryStatistics
Creates a new instance of UnivariateSummaryStatistics from a Collection of scalar values.
create() - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator.SufficientStatistic
 
create(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator.SufficientStatistic
 
create() - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator.SufficientStatistic
 
create(MultivariateGaussianInverseGammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator.SufficientStatistic
 
create(ConditionalType, String, PriorType) - Static method in class gov.sandia.cognition.statistics.bayesian.DefaultBayesianParameter
Creates a new instance of DefaultBayesianParameter
create() - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.DefaultFactory
 
create() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
 
create(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
 
create() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
 
create(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
 
create() - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic
 
create(UnivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic
 
create(Collection<? extends InputOutputPair<Double, Boolean>>) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic
Creates an ROC curve based on the scored data with target information
create(DistributionType) - Method in interface gov.sandia.cognition.statistics.SufficientStatistic
Modifies the given distribution with the parameters indicated by the sufficient statistics
create(Collection<? extends Vectorizable>, TermIndex) - Method in class gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator
Creates a new similarity network between the terms in the given documents.
create() - Static method in class gov.sandia.cognition.util.DefaultIdentifiedValue
Convenience method to create a new, empty DefaultIdentifiedValue.
create(IdentifierType, ValueType) - Static method in class gov.sandia.cognition.util.DefaultIdentifiedValue
Creates a new DefaultIdentifiedValue with the given identifier and value.
create() - Static method in class gov.sandia.cognition.util.DefaultKeyValuePair
Convenience method to create a new, empty DefaultKeyValuePair.
create(KeyType, ValueType) - Static method in class gov.sandia.cognition.util.DefaultKeyValuePair
Convenience method to create a new DefaultKeyValuePair from the given key and value.
create(String, T) - Static method in class gov.sandia.cognition.util.DefaultNamedValue
Convenience method for creating an new DefaultNamedValue.
create() - Static method in class gov.sandia.cognition.util.DefaultPair
Creates a new, empty DefaultPair with both values being null.
create(FirstType, SecondType) - Static method in class gov.sandia.cognition.util.DefaultPair
Creates a new DefaultPair from the given values.
create(ValueType, double) - Static method in class gov.sandia.cognition.util.DefaultWeightedValue
Convenience method to create a new WeightedValue.
createArrayList(DataType, DataType) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Creates a new ArrayList from the given pair of values.
createAssignmentTasks() - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer
Creates the assignment tasks given the number of threads requested
createBag(ArrayList<Integer>, ArrayList<Integer>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedIVotingLearner
 
createBag(ArrayList<Integer>, ArrayList<Integer>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Create the next sample (bag) of examples to learn the next ensemble member from.
createBalanced(Collection<? extends PairType>) - Static method in class gov.sandia.cognition.math.geometry.KDTree
Creates a balanced KDTree based on the given collection of Pairs.
createBodyConverter() - Static method in class gov.sandia.cognition.text.convert.CommonDocumentTextualConverterFactory
Creates a document text converter that extracts the body field.
createCategorizationLearner(int, double, double, int, int, Random) - Static method in class gov.sandia.cognition.learning.algorithm.tree.RandomForestFactory
Creates a random forest learner for categorization outputs.
createCluster(Collection<? extends DataType>) - Method in interface gov.sandia.cognition.learning.algorithm.clustering.cluster.ClusterCreator
Create a new cluster from the given members of that cluster.
createCluster(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultClusterCreator
Creates a new DefaultCluster from the given list of members.
createCluster() - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultIncrementalClusterCreator
 
createCluster(Collection<? extends Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianClusterCreator
Creates a GaussianCluster from a given set of vectors by fitting a Gaussian to those vectors.
createCluster() - Method in interface gov.sandia.cognition.learning.algorithm.clustering.cluster.IncrementalClusterCreator
Creates a new, empty cluster.
createCluster(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.MedoidClusterCreator
Creates a CentroidCluster at the member that minimizes the sum of divergence between all members
createCluster() - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.NormalizedCentroidClusterCreator
 
createCluster(Collection<? extends Vectorizable>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.NormalizedCentroidClusterCreator
 
createCluster() - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanCentroidClusterCreator
 
createCluster(Collection<? extends Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanCentroidClusterCreator
 
createCluster(Collection<? extends Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanMiniBatchCentroidClusterCreator
 
createCluster(Collection<ObservationType>, DirichletProcessMixtureModel.Updater<ObservationType>) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Creates a cluster from the given cluster assignment
createClusterPosterior(Iterable<? extends Vector>, Random) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanCovarianceUpdater
 
createClusterPosterior(Iterable<? extends Vector>, Random) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanUpdater
 
createClusterPosterior(Iterable<? extends ObservationType>, Random) - Method in interface gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Updater
Updates the cluster from the values assigned to it
createClustersFromAssignments() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Creates the set of clusters using the current cluster assignments.
createClustersFromAssignments() - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer
 
CreateClustersFromAssignments() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer.CreateClustersFromAssignments
Creates a new instance of CreateClustersFromAssignments
createCogxel(SemanticIdentifier) - Method in interface gov.sandia.cognition.framework.CogxelFactory
Creates a new Cogxel for the given CogxelFactory from the given SemanticIdentifier.
createCogxel(SemanticIdentifier) - Method in class gov.sandia.cognition.framework.DefaultCogxelFactory
Creates a new Cogxel for the given CogxelFactory from the given SemanticIdentifier.
createCogxel(SemanticIdentifier) - Method in class gov.sandia.cognition.framework.lite.BooleanActivatableCogxelFactory
Creates a new Cogxel for the given CogxelFactory from the given SemanticIdentifier.
createConditionalDistribution(Vectorizable, Vector) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
Creates the distribution from which the outputs are generated, given the weights and the input to consider.
createConditionalDistribution(Vectorizable, Vector) - Method in interface gov.sandia.cognition.statistics.bayesian.BayesianRegression
Creates the distribution from which the outputs are generated, given the weights and the input to consider.
createConditionalDistribution(Vectorizable, Vector) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression
Creates the distribution from which the outputs are generated, given the weights and the input to consider.
createConditionalDistribution(ParameterType) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator
 
createConditionalDistribution(ParameterType) - Method in interface gov.sandia.cognition.statistics.bayesian.conjugate.ConjugatePriorBayesianEstimator
Creates an instance of the class conditional distribution, parameterized by the given parameter value.
createConditionalDistribution(Vector) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator
 
createConditionalDistribution(Vector) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator
 
createdClass - Variable in class gov.sandia.cognition.factory.DefaultFactory
The class whose default constructor is used to create new objects.
createDefaultAlphabet() - Static method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Creates the default alphabet, which are the lower-case English letters.
createDefaultState() - Method in interface gov.sandia.cognition.evaluator.StatefulEvaluator
Creates a new default state object.
createDefaultState() - Method in class gov.sandia.cognition.learning.data.feature.DelayFunction
 
createDefaultState() - Method in class gov.sandia.cognition.learning.data.feature.LinearRegressionCoefficientExtractor
 
createDefaultState() - Method in class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
 
createDefaultState() - Method in class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
 
createDefaultState() - Method in class gov.sandia.cognition.math.signals.LinearDynamicalSystem
 
createDefaultState() - Method in class gov.sandia.cognition.math.signals.MovingAverageFilter
 
createDefaultState() - Method in class gov.sandia.cognition.math.signals.PIDController
 
createDiagonal(Vectorizable) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new square matrix whose number of rows and columns match the dimensionality of the given vector.
createDistributionEstimatorTasks() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm
Creates the DistributionEstimatorTask
createEmptyInputVector() - Method in interface gov.sandia.cognition.framework.lite.PatternRecognizerLite
Creates an empty vector to use for input.
createEmptyInputVector() - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Creates an empty vector to use for input.
createEmptyVector() - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Creates an empty Vector for the converter, of the proper dimensionality.
createEvaluationTasks(Collection<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm
Creates the evaluation tasks to execute in parallel.
createFactory(T) - Static method in class gov.sandia.cognition.factory.PrototypeFactory
A convenience method for creating prototype factories.
createFolds(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.experiment.CrossFoldCreator
Creates the requested number of cross-validation folds from the given data.
createFolds(Collection<? extends DataType>, int, Random) - Static method in class gov.sandia.cognition.learning.experiment.CrossFoldCreator
Creates the requested number of cross-validation folds from the given data.
createFolds(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.experiment.LeaveOneOutFoldCreator
Creates a list of folds that is the same size as the given data.
createFolds(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.experiment.RandomByTwoFoldCreator
 
createFolds(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.experiment.RandomFoldCreator
Creates the folds from the given data by passing the data into the set data partitioner multiple times.
createFolds(Collection<? extends InputDataType>) - Method in interface gov.sandia.cognition.learning.experiment.ValidationFoldCreator
Creates a list of partitioned (training and testing) datasets from the given single dataset.
createFromActualPredictedPairs(Collection<? extends Pair<? extends Boolean, ? extends Boolean>>) - Static method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Creates a new DefaultConfusionMatrix from the given actual-predicted pairs.
createFromActualPredictedPairs(Collection<? extends Pair<? extends CategoryType, ? extends CategoryType>>) - Static method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
Creates a new DefaultConfusionMatrix from the given actual-predicted pairs.
createFromLogValue(double) - Static method in class gov.sandia.cognition.math.LogNumber
Creates a new LogNumber from the given value that is already in log-space.
createFromLogValue(boolean, double) - Static method in class gov.sandia.cognition.math.LogNumber
Creates a new LogNumber from the given value that is already in log-space.
createFromLogValue(double) - Static method in class gov.sandia.cognition.math.UnsignedLogNumber
Creates a new LogNumber from the given value that is already in log-space.
createFromTargetEstimatePairs(Collection<? extends Pair<Boolean, ? extends Number>>) - Static method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic
Creates an ROC curve based on the scored data with target information.
createFromValue(double) - Static method in class gov.sandia.cognition.math.LogNumber
Creates a new LogNumber from the given value.
createFromValue(double) - Static method in class gov.sandia.cognition.math.UnsignedLogNumber
Creates a new LogNumber from the given value.
createGaussianRandom(int, int, Random) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new Matrix filled with values sampled from a Gaussian distribution with mean 0 and variance 1.
createGaussianRandom(int, int, Random) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
 
createGaussianRandom(int, Random) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
Creates a new square Matrix of the given size with random values for the entries, Gaussian distributed with mean 0 and variance 1.
createGaussianRandom(int, Random) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a vector with random values sampled from a Gaussian distribution with mean 0 and variance 1.
createHashMapWithSize(int) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Creates a new HashMap with the given expected size.
createHashSetWithSize(int) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Creates a new HashSet with the given expected size.
createIdentity(int) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a Matrix with ones (1) on the diagonal, and zeros (0) elsewhere
createIdentity(int, int) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a Matrix with ones (1) on the diagonal, and zeros (0) elsewhere
createInitialEnsemble() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Create the initial, empty ensemble for the algorithm to use.
createInitialEnsemble() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner
 
createInitialEnsemble() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingRegressionLearner
 
createInitialEnsemble() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BinaryBaggingLearner
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.OnlineLearner
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.confidence.AdaptiveRegularizationOfWeights
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
 
createInitialLearnedObject() - Method in interface gov.sandia.cognition.learning.algorithm.IncrementalLearner
Creates a new initial learned object, before any data is given.
createInitialLearnedObject(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractKernelizableBinaryCategorizerOnlineLearner
 
createInitialLearnedObject(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractOnlineLinearBinaryCategorizerLearner
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Basic
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelBinaryCategorizerOnlineLearnerAdapter
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.RemoveOldestKernelPerceptron
 
createInitialLearnedObject(Kernel<? super InputType>) - Method in interface gov.sandia.cognition.learning.algorithm.perceptron.KernelizableBinaryCategorizerOnlineLearner
Creates the initial learned object with a given kernel.
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineVotedPerceptron
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
Creates the initial parameters from which to start the Markov chain.
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.KalmanFilter
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.Estimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.WeightedEstimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimatorCovarianceInverse
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.Estimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.IncrementalEstimator
 
createInitialLearnedObject() - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector.Learner
 
createInitialLinearLearnedObject(VectorFactory<?>) - Method in interface gov.sandia.cognition.learning.algorithm.perceptron.LinearizableBinaryCategorizerOnlineLearner
Creates the initial learned object.
createInitialParameter() - Method in interface gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm.Updater
Creates the initial parameterization
createInitialParticles(int) - Method in interface gov.sandia.cognition.statistics.bayesian.ParticleFilter.Updater
Creates the initial particles.
createInputTransformed(Evaluator<? super InputType, ? extends IntermediateType>, BatchLearner<? super Collection<? extends IntermediateType>, ? extends Evaluator<? super IntermediateType, ? extends OutputType>>) - Static method in class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
Creates a new CompositeBatchLearnerPair from the given input transform and learner.
createInputTransformed(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends TransformedInputType>>, BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType, OutputType>>, ? extends Evaluator<? super TransformedInputType, ? extends OutputType>>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the input and supervised learners, performing no transformation on the output type.
createInputTransformed(Evaluator<? super InputType, ? extends TransformedInputType>, BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType, OutputType>>, ? extends Evaluator<? super TransformedInputType, ? extends OutputType>>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the predefined input transform and the supervised learner.
createInternalFunction() - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
Creates the internal function that maps the parameter set of result as the input to the function, so that the minimization algorithms can perturb this input in their minimization schemes.
createInternalFunction() - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer
 
createInternalFunction() - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer
 
createKernelLearner(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractKernelizableBinaryCategorizerOnlineLearner
 
createKernelLearner(Kernel<? super InputType>) - Method in interface gov.sandia.cognition.learning.algorithm.perceptron.KernelizableBinaryCategorizerOnlineLearner
Creates a new kernel-based learner using the standard learning interfaces based on this learner and its parameters.
createLinearLearner(VectorFactory<?>) - Method in interface gov.sandia.cognition.learning.algorithm.perceptron.LinearizableBinaryCategorizerOnlineLearner
Creates a new linear learner using the standard learning interfaces based on this learner and its parameters.
createLinkedHashMapWithSize(int) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Creates a new LinkedHashMap with the given expected size.
createLinkedHashSetWithSize(int) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Creates a new LinkedHashSet with the given expected size.
createLogDominanceWeighter() - Static method in class gov.sandia.cognition.text.term.vector.weighter.CommonTermWeighterFactory
Creates a log-dominance weighting scheme.
createLogEntropyWeighter() - Static method in class gov.sandia.cognition.text.term.vector.weighter.CommonTermWeighterFactory
Creates a log-entropy weighting scheme.
createMatrix(int, int) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseMatrixFactory
Creates a new all-zero DenseMatrix of the specified dimensions.
createMatrix(int, int) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDiagonalMatrixFactory
Creates an empty Matrix of the specified dimensions, all elements must be all zeros!
createMatrix(int, int) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseMatrixFactory
Creates an empty Matrix of the specified dimensions, all elements must be all zeros!
createMatrix(int, int) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates an empty Matrix of the specified dimensions, all elements must be all zeros!
createMatrix(int, int, double) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a matrix with the given initial value.
createMatrix(int, int) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ
 
createMatrix(int, int) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
 
createMatrix(int) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
Creates a square diagonal matrix of dimensionality "dim" with zeros along the diagonal
createMatrix(int, int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
Creates a matrix with the given initial value on all of the elements of the diagonal.
createMatrix(int, int) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ
 
createModel() - Method in interface gov.sandia.cognition.framework.CognitiveModelFactory
Creates a CognitiveModel from the factory.
createModel() - Method in class gov.sandia.cognition.framework.concurrent.MultithreadedCognitiveModelFactory
Creates a MultithreadedCognitiveModel using the CognitiveModuleFactories that are part of the model factory.
createModel() - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteFactory
Creates a CognitiveModelLite using the CognitiveModuleFactories that are part of the model factory.
createModule(CognitiveModel) - Method in interface gov.sandia.cognition.framework.CognitiveModuleFactory
Creates a new CognitiveModule for the given CognitiveModel.
createModule(CognitiveModel) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactory
Creates a new CognitiveModule for the given CognitiveModel.
createModule(CognitiveModel) - Method in class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModuleFactory
Creates a new CognitiveModule for the given CognitiveModel.
createModule(CognitiveModel) - Method in class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLiteFactory
Creates a new MutableSemanticMemoryLite module for the given model.
createModule(CognitiveModel) - Method in class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteFactory
Creates a new SharedSemanticMemoryLite module for the given model.
createModule(CognitiveModel) - Method in class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModuleFactory
Creates a new CognitiveModule for the given CognitiveModel.
createNamedValuesList(Collection<T>) - Static method in class gov.sandia.cognition.util.DefaultNamedValue
Creates a list of named values from a collection of named objects.
createOutputTransformed(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends IntermediateType>>, Evaluator<? super IntermediateType, ? extends OutputType>) - Static method in class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
Creates a new CompositeBatchLearnerPair from the given learner and output transform..
createOutputTransformed(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, TransformedOutputType>>, ? extends Evaluator<? super InputType, ? extends TransformedOutputType>>, BatchLearner<? super Collection<? extends OutputType>, ? extends ReversibleEvaluator<OutputType, TransformedOutputType, ?>>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the supervised and output learners, performing no transformation on the input type.
createOutputTransformed(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, TransformedOutputType>>, ? extends Evaluator<? super InputType, ? extends TransformedOutputType>>, ReversibleEvaluator<OutputType, TransformedOutputType, ?>) - Static method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Creates a new InputOutputTransformedBatchLearner from the predefined output transforms and the supervised learner.
createPair(FirstType, SecondType) - Method in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
Creates a Pair from the needed data
createPair(InputType, OutputType) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter
 
createPair(TargetType, EstimateType) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter
 
createParameter(BernoulliDistribution, BetaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator
 
createParameter(BinomialDistribution, BetaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator
 
createParameter(ConditionalType, BeliefType) - Method in interface gov.sandia.cognition.statistics.bayesian.conjugate.ConjugatePriorBayesianEstimator
Creates a parameter linking the conditional and prior distributions
createParameter(ExponentialDistribution, GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator
 
createParameter(GammaDistribution, GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator
 
createParameter(MultinomialDistribution, DirichletDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator
 
createParameter(MultivariateGaussian, MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator
 
createParameter(MultivariateGaussian, NormalInverseWishartDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator
 
createParameter(PoissonDistribution, GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator
 
createParameter(UniformDistribution, ParetoDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator
 
createParameter(UnivariateGaussian, UnivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator
 
createParameter(UnivariateGaussian, NormalInverseGammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator
 
createPartialPermutation(int, int, Random) - Static method in class gov.sandia.cognition.math.Permutation
Creates a random partial permutation of size k of the numbers 0 (inclusive) through n (exclusive).
createPartition(Collection<? extends DataType>) - Method in interface gov.sandia.cognition.learning.data.DataPartitioner
Partitions the given collection of data into a training set and a testing set.
createPartition(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.data.RandomDataPartitioner
Randomly partitions the given data into a training and testing set.
createPartition(Collection<? extends DataType>, double, Random) - Static method in class gov.sandia.cognition.learning.data.RandomDataPartitioner
Randomly partitions the given data into a training and testing set.
createPartitions() - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer
Splits the data across the numComponents cost functions
createPermutation(int, Random) - Static method in class gov.sandia.cognition.math.Permutation
Creates a random permutation of the numbers 0 (inclusive) through n (exclusive).
createPolynomials(double...) - Static method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction
Creates an array of PolynomialFunctions from the array of their exponents
createPredictionDataset(Collection<? extends DataType>, int) - Static method in class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner
Takes a collection and creates a multi-collection of sequences of input-output pairs that are from the given sequence with the given prediction horizon.
createPredictionDataset(MultiCollection<? extends DataType>, int) - Static method in class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner
Takes a multi-collection and creates a multi-collection of sequences of input-output pairs that are from the given sequence with the given prediction horizon.
createPredictionDataset(int, Collection<? extends InputOutputPair<? extends InputType, OutputType>>) - Static method in class gov.sandia.cognition.learning.algorithm.TimeSeriesPredictionLearner
Creates a dataset that can be used to predict the future by "predictionHorizon" samples.
createPredictiveDistribution(PosteriorType) - Method in interface gov.sandia.cognition.statistics.bayesian.BayesianEstimatorPredictor
Creates the predictive distribution of new data given the posterior.
createPredictiveDistribution(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
Creates the predictive distribution of outputs given the weight posterior
createPredictiveDistribution(PosteriorType) - Method in interface gov.sandia.cognition.statistics.bayesian.BayesianRegression
Creates the predictive distribution of outputs given the weight posterior
createPredictiveDistribution(MultivariateGaussianInverseGammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression
 
createPredictiveDistribution(BetaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator
 
createPredictiveDistribution(GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator
 
createPredictiveDistribution(DirichletDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator
 
createPredictiveDistribution(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator
 
createPredictiveDistribution(NormalInverseWishartDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator
 
createPredictiveDistribution(GammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator
 
createPredictiveDistribution(UnivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator
Creates the predictive distribution from the given posterior.
createPredictiveDistribution(NormalInverseGammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator
 
createPredictiveDistribution(MultivariateGaussian, ArrayList<InputType>) - Method in class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression
Creates the predictive distribution for future points.
createPriorPredictive(Iterable<? extends Vector>) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanCovarianceUpdater
 
createPriorPredictive(Iterable<? extends Vector>) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanUpdater
 
createPriorPredictive(Iterable<? extends ObservationType>) - Method in interface gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Updater
Creates the prior predictive distribution from the data.
createRandom(int, BatchLearner<Collection<? extends WeightedValue<? extends ObservationType>>, ? extends ComputableDistribution<ObservationType>>, Collection<? extends ObservationType>, Random) - Static method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Creates a Hidden Markov Model with the same PMF/PDF for each state, but sampling the columns of the transition matrix and the initial probability distributions from a diffuse Dirichlet.
createRandom(int, ComputableDistribution<ObservationType>, Random) - Static method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Creates a Hidden Markov Model with the same PMF/PDF for each state, but sampling the columns of the transition matrix and the initial probability distributions from a diffuse Dirichlet.
createRandom(Collection<? extends ProbabilityFunction<ObservationType>>, Random) - Static method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Creates a Hidden Markov Model with the given probability function for each state, but sampling the columns of the transition matrix and the initial probability distributions from a diffuse Dirichlet.
createRandom(Random) - Static method in class gov.sandia.cognition.math.matrix.mtj.Vector3
Creates a new random Vector3 from the given Random object.
createRegressionLearner(int, double, double, int, int, Random) - Static method in class gov.sandia.cognition.learning.algorithm.tree.RandomForestFactory
Creates a random forest learner for categorization outputs.
createReordering(Collection<? extends DataType>, Random) - Static method in class gov.sandia.cognition.math.Permutation
Takes a collection and returns an array list that contains a permutation of the elements of that collection.
createReverse() - Method in class gov.sandia.cognition.data.convert.AbstractReverseCachedDataConverter
Creates a new reverse converter.
createReverse() - Method in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
 
createReverse() - Method in class gov.sandia.cognition.data.convert.number.StringToDoubleConverter
 
createReverse() - Method in class gov.sandia.cognition.data.convert.number.StringToIntegerConverter
 
createSequentialPartitions(Iterable<? extends DataType>, int) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Creates a partition of the given data into "numPartition" roughly equal sets, preserving their pre-existing sequential ordering, with the nonzero remainder elements going into the final partition.
createSequentialPartitions(List<? extends DataType>, int) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Creates a partition of the given data into "numPartition" roughly equal sets, preserving their pre-existing sequential ordering, with the nonzero remainder elements going into the final partition.
createSpherical(int) - Static method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Create a spherical partitional clusterer, using Cosine distance and a vector mean centroid cluster creator.
createTerm(Token) - Method in interface gov.sandia.cognition.text.term.TermFactory
Creates a new term from the given token.
createTerm(String) - Method in interface gov.sandia.cognition.text.term.TermFactory
Creates a new term from the given string.
createTFIDFWeighter() - Static method in class gov.sandia.cognition.text.term.vector.weighter.CommonTermWeighterFactory
Creates a term-frequency inverse-document-frequency (TF-IDF) weighting scheme but without any normalization.
createTFIDFWeighterWithUnitNormalization() - Static method in class gov.sandia.cognition.text.term.vector.weighter.CommonTermWeighterFactory
Creates a term-frequency inverse-document-frequency (TF-IDF) weighting scheme with unit vector normalization (2-norm).
createTFWeighter() - Static method in class gov.sandia.cognition.text.term.vector.weighter.CommonTermWeighterFactory
Creates a term-frequency (TF) weighting scheme.
createThreadPool() - Static method in class gov.sandia.cognition.algorithm.ParallelUtil
Creates a thread pool with the "optimal" number of threads.
createThreadPool(int) - Static method in class gov.sandia.cognition.algorithm.ParallelUtil
Creates a thread pool with the given number of threads.
createThreadPool() - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer
Creates the thread pool using the Foundry's global thread pool.
createTitleAuthorBodyConverter() - Static method in class gov.sandia.cognition.text.convert.CommonDocumentTextualConverterFactory
Creates a document text converter that puts the title, author, and body fields together.
createTitleBodyConverter() - Static method in class gov.sandia.cognition.text.convert.CommonDocumentTextualConverterFactory
Creates a document text converter that puts the title and body fields together.
createUniformInitialProbability(int) - Static method in class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain
Creates a uniform initial-probability Vector
createUniformRandom(int, int, Random) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new Matrix filled with values sampled uniformly between 0 and 1.
createUniformRandom(int, int, double, double, Random) - Method in class gov.sandia.cognition.math.matrix.MatrixFactory
Creates a new Matrix of the given size with random values for the entries, uniformly distributed between the given minimum and maximum values.
createUniformRandom(int, int, Random) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
 
createUniformRandom(int, int, double, double, Random) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
 
createUniformRandom(int, double, double, Random) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
Creates a new square Matrix of the given size with random values for the entries, uniformly distributed between the given minimum and maximum values.
createUniformRandom(int, Random) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a vector with random values for the entries uniformly sampled between 0 and 1.
createUniformRandom(int, double, double, Random) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a Vector with random values for the entries, uniformly distributed between "min" and "max"
createUniformTransitionProbability(int) - Static method in class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain
Creates a uniform transition-probability Matrix
createUnweighted(Collection<? extends TargetEstimatePair<? extends CategoryType, ? extends CategoryType>>) - Static method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
Creates a new DefaultConfusionMatrix from the given actual-predicted pairs.
createVector(int) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
 
createVector(int) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
 
createVector(int) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
 
createVector(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
 
createVector(int) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
 
createVector(int) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates an empty Vector of the specified dimension, all elements must be all zeros!
createVector(int, double) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a Vector with the given initial value for all elements.
createVector1D(double) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
 
createVector1D(double) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
Creates a one-dimensional vector with the given x coordinate: (x).
createVector1D(double) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
 
createVector1D(double) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
 
createVector1D() - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a one-dimensional zero vector: (0.0).
createVector1D(double) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a one-dimensional vector with the given x coordinate: (x).
createVector2D(double, double) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
 
createVector2D(double, double) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
Creates a two-dimensional vector with the given x and y coordinates: (x, y).
createVector2D(double, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
 
createVector2D(double, double) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
 
createVector2D() - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a two-dimensional zero vector: (0.0, 0.0).
createVector2D(double, double) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a two-dimensional vector with the given x and y coordinates: (x, y).
createVector3D(double, double, double) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
 
createVector3D(double, double, double) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
Creates a three-dimensional vector with the given x, y, and z coordinates: (x, y, z).
createVector3D(double, double, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
 
createVector3D(double, double, double) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
 
createVector3D() - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a three-dimensional zero vector: (0.0, 0.0, 0.0).
createVector3D(double, double, double) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a three-dimensional vector with the given x, y, and z coordinates: (x, y, z).
createVectorCapacity(int, int) - Method in class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
 
createVectorCapacity(int, int) - Method in class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
 
createVectorCapacity(int, int) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
 
createVectorCapacity(int, int) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
 
createVectorCapacity(int, int) - Method in class gov.sandia.cognition.math.matrix.VectorFactory
Creates a new, empty vector with the given dimensionality and expected number of nonzero elements.
createWeightDistribution() - Method in class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer
 
createWeightDistribution() - Method in interface gov.sandia.cognition.learning.function.categorization.ConfidenceWeightedBinaryCategorizer
Creates a multivariate Gaussian distribution that represents the distribution of weight vectors that the algorithm has learned.
createWrapper(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ
Creates a new wrapper for a dense MTJ matrix.
createWrapper(DenseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
Creates a new wrapper for a dense MTJ vector.
createWrapper(FlexCompColMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ
Creates a new wrapper for a sparse column MTJ matrix.
createWrapper(FlexCompRowMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ
Creates a new wrapper for a sparse row MTJ matrix.
createWrapper(SparseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
Creates a new wrapper for a sparse MTJ vector.
creator - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The merger used to merge two clusters into one element.
creator - Variable in class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
The ClusterCreator to create the initial clusters from.
creator - Variable in class gov.sandia.cognition.learning.algorithm.clustering.initializer.RandomClusterInitializer
The creator for new clusters.
creator - Variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The merger used to merge two clusters into one cluster.
CrossFoldCreator<DataType> - Class in gov.sandia.cognition.learning.experiment
The CrossFoldCreator implements a validation fold creator that creates folds for a typical k-fold cross-validation experiment.
CrossFoldCreator() - Constructor for class gov.sandia.cognition.learning.experiment.CrossFoldCreator
Creates a new instance of CrossFoldCreator with a default number of folds (10) and a default Random number generator.
CrossFoldCreator(int) - Constructor for class gov.sandia.cognition.learning.experiment.CrossFoldCreator
Creates a new CrossFoldCreator.
CrossFoldCreator(int, Random) - Constructor for class gov.sandia.cognition.learning.experiment.CrossFoldCreator
Creates a new CrossFoldCreator.
crossover(GenomeType, GenomeType) - Method in interface gov.sandia.cognition.learning.algorithm.genetic.reproducer.CrossoverFunction
Crosses over the provided genomes to produce a new genome.
crossover(Vectorizable, Vectorizable) - Method in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.VectorizableCrossoverFunction
Crosses over each element of the parent vectors.
CrossoverFunction<GenomeType> - Interface in gov.sandia.cognition.learning.algorithm.genetic.reproducer
The CrossoverFunction interface implements standard functionality for implementing crossover for genetic algorithms.
CrossoverReproducer<GenomeType> - Class in gov.sandia.cognition.learning.algorithm.genetic.reproducer
The CrossoverReproducer takes a population of genomes, and applies the supplied CrossoverFunction to produce a new population.
CrossoverReproducer(Selector<GenomeType>, CrossoverFunction<GenomeType>) - Constructor for class gov.sandia.cognition.learning.algorithm.genetic.reproducer.CrossoverReproducer
Creates a new instance of CrossoverReproducer
CSV_EXTENSION - Static variable in class gov.sandia.cognition.framework.io.ModelFileHandler
The extension for comma-separated-value models.
CSVDefaultCognitiveModelLiteHandler - Class in gov.sandia.cognition.framework.io
The CSVDefaultCognitiveModelLiteHandler class implements a format handler for CSV files that specify a default setup for a CognitiveModelLite.
CSVDefaultCognitiveModelLiteHandler() - Constructor for class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Creates a new instance of CommaSeparatedValueHandler.
CSVParseException - Exception in gov.sandia.cognition.io
The CSVParseException class implements an exception that is thrown while parsing a CSV file.
CSVParseException() - Constructor for exception gov.sandia.cognition.io.CSVParseException
Creates a new instance of CSVParseException without detail message.
CSVParseException(String) - Constructor for exception gov.sandia.cognition.io.CSVParseException
Constructs an instance of CSVParseException with the specified detail message.
CSVParseException(Throwable) - Constructor for exception gov.sandia.cognition.io.CSVParseException
Constructs an instance of CSVParseException with the given cause of the exception.
CSVParseException(String, Throwable) - Constructor for exception gov.sandia.cognition.io.CSVParseException
Constructs an instance of CSVParseException with the given message and cause of the exception.
CSVUtility - Class in gov.sandia.cognition.io
The CSVUtility class implements some utility functions for dealing with comma-separated value (CSV) file types.
CSVUtility() - Constructor for class gov.sandia.cognition.io.CSVUtility
 
Cubic(double, double, double, double) - Constructor for class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic
Creates a new instance of Quadratic
Cubic(PolynomialFunction.Cubic) - Constructor for class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic
Copy constructor
CumulativeDistributionFunction<NumberType extends java.lang.Number> - Interface in gov.sandia.cognition.statistics
Functionality of a cumulative distribution function.
currentBag - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The current bag used to train the current ensemble member.
currentCorrectIndices - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The indices of examples that the ensemble currently gets correct.
currentEnsembleCorrect - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
A boolean for each example indicating if the ensemble currently gets the example correct or incorrect.
currentIncorrectIndices - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The indices of examples that the ensemble currently gets incorrect.
currentInput - Variable in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
Current input to the model.
currentMember - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The currently learned member of the ensemble.
currentMemberEstimates - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The estimates of the current member for each example.
currentParameter - Variable in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
The current parameters in the random walk.
CustomDenseMatrixFactory - Class in gov.sandia.cognition.math.matrix.custom
Factory that creates DenseMatrix instances.
CustomDenseMatrixFactory() - Constructor for class gov.sandia.cognition.math.matrix.custom.CustomDenseMatrixFactory
 
CustomDenseVectorFactory - Class in gov.sandia.cognition.math.matrix.custom
Dense vector factory.
CustomDenseVectorFactory() - Constructor for class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
 
CustomDiagonalMatrixFactory - Class in gov.sandia.cognition.math.matrix.custom
Factory for diagonal matrices.
CustomDiagonalMatrixFactory() - Constructor for class gov.sandia.cognition.math.matrix.custom.CustomDiagonalMatrixFactory
 
CustomSparseMatrixFactory - Class in gov.sandia.cognition.math.matrix.custom
Factory for Sparse Matrices.
CustomSparseMatrixFactory() - Constructor for class gov.sandia.cognition.math.matrix.custom.CustomSparseMatrixFactory
 
CustomSparseVectorFactory - Class in gov.sandia.cognition.math.matrix.custom
Generates Sparse Vectors with all settings initialized properly
CustomSparseVectorFactory() - Constructor for class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
 
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 
Skip navigation links