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D

dampingFactor - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The damping factor (lambda).
data - Variable in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
The data to learn from.
data - Variable in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer.CreateClustersFromAssignments
Data set to use for the task
data - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.LogLikelihoodTask
Data to compute the log-likelihood of
data - Variable in class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborExhaustive
The data that nearest-neighbor is performed over.
data - Variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
The data that the KPCA was performed over.
DataConverter<InputType,OutputType> - Interface in gov.sandia.cognition.data.convert
Defines an object used to convert data from one type to another.
DataCountTreeSetBinnedMapHistogram<ValueType extends java.lang.Comparable<? super ValueType>> - Class in gov.sandia.cognition.statistics.distribution
The DataCountTreeSetBinnedMapHistogram class extends a DefaultDataDistribution by mapping values to user defined bins using a TreeSetBinner.
DataCountTreeSetBinnedMapHistogram(TreeSetBinner<ValueType>) - Constructor for class gov.sandia.cognition.statistics.distribution.DataCountTreeSetBinnedMapHistogram
Creates a new DataCountTreeBinnedMapHistogram using the provided TreeSetBinner.
DataCountTreeSetBinnedMapHistogram(Collection<? extends ValueType>) - Constructor for class gov.sandia.cognition.statistics.distribution.DataCountTreeSetBinnedMapHistogram
Creates a new DataCountTreeBinnedMapHistogram using the provided list of bin boundaries.
DataDistribution<DataType> - Interface in gov.sandia.cognition.statistics
A distribution of data from which we can sample and perform Ring operations.
DataDistribution.PMF<KeyType> - Interface in gov.sandia.cognition.statistics
Interface for the probability mass function (PMF) of a data distribution.
dataFullEstimates - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The running estimate of the ensemble for each example.
dataInBag - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
An indicator of whether or not the data is in the current bag.
dataInBag - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
A counter for each example indicating how many times it exists in the current bag.
dataIndices - Variable in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
Indices of the data.
dataList - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
The data stored for efficient random access.
dataList - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The data represented as an array list.
dataList - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
The data in the form that it can be accessed in O(1) as a list.
dataList - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineStochasticGradient
The input data represented as a list for fast access.
dataList - Variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The data represented as a list.
dataOutOfBagEstimates - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The running estimate of the ensemble for each example where an ensemble member can only vote on elements that were not in the bag used to train it.
DataPartitioner<DataType> - Interface in gov.sandia.cognition.learning.data
The DataPartitioner interface defines the functionality of an object that can create a PartitionedDataset from a collection of data.
dataPerCategory - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner
The mapping of categories to indices of examples belonging to the category.
DataPoint(ScalarThresholdBinaryCategorizer, DefaultBinaryConfusionMatrix) - Constructor for class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.DataPoint
Creates a new instance of DataPoint
dataSampleSize - Variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The minimum of the sample size and the data size.
DatasetUtil - Class in gov.sandia.cognition.learning.data
Static class containing utility methods for handling Collections of data in the learning package.
DatasetUtil() - Constructor for class gov.sandia.cognition.learning.data.DatasetUtil
 
dataSize - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
The size of the data.
dataSize - Variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The size of the data in the training set.
DataToVectorEncoder<InputType> - Interface in gov.sandia.cognition.data.convert.vector
Defines a converter that can be used to encode data into a Vector.
date - Variable in class gov.sandia.cognition.text.document.DefaultDateField
The date stored in the field.
DAY - Static variable in class gov.sandia.cognition.time.DefaultDuration
A day in duration.
DBSCANClusterer<DataType extends Vectorizable,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering
The DBSCAN algorithm requires three parameters: a distance metric, a value for neighborhood radius, and a value for the minimum number of surrounding neighbors for a point to be considered non-noise.
DBSCANClusterer(Semimetric<? super DataType>, ClusterCreator<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Creates a new instance of DBSCANClusterer.
DBSCANClusterer(double, int, Semimetric<? super DataType>, ClusterCreator<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Creates a new instance of AffinityPropagation.
decider - Variable in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
The decider used to make a decision as to which child use.
deciderLearner - Variable in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner
The learning algorithm for the decision function.
DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>> - Interface in gov.sandia.cognition.learning.algorithm.tree
The DeciderLearner interface defines the functionality of a learner that can be used to learn a decision function inside a decision tree.
DecisionTree<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.tree
The DecisionTree class implements a standard decision tree that is made up of DecisionTreeNode objects.
DecisionTree() - Constructor for class gov.sandia.cognition.learning.algorithm.tree.DecisionTree
Creates a new instance of DecisionTree.
DecisionTree(DecisionTreeNode<InputType, OutputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.tree.DecisionTree
Creates a new instance of DecisionTree.
DecisionTreeNode<InputType,OutputType> - Interface in gov.sandia.cognition.learning.algorithm.tree
The DecisionTreeNode interface defines the functionality of a node in a decision tree.
decompress() - 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 decompressed from the compressed Yale format.
decompress() - 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.
decoupleVectorDataset(Collection<? extends Vector>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Takes a dataset of M-dimensional Vectors and turns it into M datasets of Doubles
decoupleVectorPairDataset(Collection<? extends InputOutputPair<? extends Vector, ? extends Vector>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Takes a set of equal-dimension Vector-Vector InputOutputPairs and turns them into a collection of Double-Double InputOutputPairs.
decrement(KeyType) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
decrement(KeyType, double) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
decrement(KeyType) - Method in interface gov.sandia.cognition.collection.ScalarMap
Decrements the value associated with a given key by 1.0.
decrement(KeyType, double) - Method in interface gov.sandia.cognition.collection.ScalarMap
Decrements the value associated with the given key by the given amount.
decrement(int, int) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
decrement(int, int, double) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
decrement(int) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
decrement(int, double) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
decrement(int, int) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Decrements the value at the given position by 1.
decrement(int, int, double) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Decrements the value at the given position by the given value.
decrement(int) - Method in interface gov.sandia.cognition.math.matrix.Vector
Decrements the value of the given index by 1.
decrement(int, double) - Method in interface gov.sandia.cognition.math.matrix.Vector
Decrements the value of the given index by the given value.
decrement(ValueType, double) - Method in class gov.sandia.cognition.statistics.distribution.DataCountTreeSetBinnedMapHistogram
 
decrementAll(Iterable<? extends KeyType>) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
decrementAll(ScalarMap<? extends KeyType>) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
decrementAll(Iterable<? extends KeyType>) - Method in interface gov.sandia.cognition.collection.ScalarMap
Decrements the values associated all of the given keys by 1.0.
decrementAll(ScalarMap<? extends KeyType>) - Method in interface gov.sandia.cognition.collection.ScalarMap
Decrements all the keys in this map by the values in the other one.
deepCopy(DirectedNodeEdgeGraph<NodeType>) - Static method in class gov.sandia.cognition.graph.GraphUtil
Makes a deep copy of the input graph, matching implementation of the interface.
deepCopy(T) - Static method in class gov.sandia.cognition.util.ObjectUtil
Performs a deep copy of a given object.
DEFALUT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Default scale, 1.0.
DEFAULT_AGGRESSIVENESS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin
The default aggressiveness is 0.001.
DEFAULT_ALPHA - Static variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Default concentration parameter of the Dirichlet Process, 1.0.
DEFAULT_ALPHA - Static variable in class gov.sandia.cognition.statistics.distribution.BetaDistribution
Default alpha, 2.0.
DEFAULT_ALPHA - Static variable in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Default concentration parameter, 1.0.
DEFAULT_ALPHA - Static variable in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment
Default alpha (p-value threshold), 0.05.
DEFAULT_ALPHA - Static variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The default value of alpha is 5.0.
DEFAULT_BETA - Static variable in class gov.sandia.cognition.statistics.distribution.BetaDistribution
Default beta, 2.0.
DEFAULT_BETA - Static variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The default value of beta is 0.5.
DEFAULT_BIAS - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.AdditiveEnsemble
The default bias is 0.0.
DEFAULT_BIAS - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAdditiveEnsemble
The default bias is 0.0.
DEFAULT_BIAS - Static variable in class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
The default value for the bias is 0.0.
DEFAULT_BIAS - Static variable in class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer
The default bias is 0.0.
DEFAULT_BIAS - Static variable in class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction
The default value for the bias is 0.0.
DEFAULT_BIAS - Static variable in class gov.sandia.cognition.learning.function.scalar.LinearVectorScalarFunction
The default bias is 0.0.
DEFAULT_BIAS_ENABLED - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default for bias enabled is true.
DEFAULT_BIAS_REGULARIZATION - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default bias regularization parameter is 0.0.
DEFAULT_BLOCK_EXPERIMENT_COMPARISON - Static variable in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment
Default block-experiment comparison, FriedmanConfidence.
DEFAULT_BUDGET - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineBudgetedKernelBinaryCategorizerLearner
The default budget is 100.
DEFAULT_BURN_IN_ITERATIONS - Static variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The default number of burn-in iterations is 2000.
DEFAULT_CAPACITY - Static variable in class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
Default capacity, 100.
DEFAULT_CDF - Static variable in class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
Default CDF, a 3-DOF Chi-Square.
DEFAULT_CENTER_DATA - Static variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
The default setting for centering data is true.
DEFAULT_COMPONENT_COUNT - Static variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
The default number of components to create is 10.
DEFAULT_CONFIDENCE - Static variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
The default confidence is 0.85.
DEFAULT_CONFIDENCE - Static variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
The default confidence is 0.85.
DEFAULT_CONSTANT - Static variable in class gov.sandia.cognition.learning.function.kernel.PolynomialKernel
The default constant is 1.0.
DEFAULT_CONSTANT - Static variable in class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
The default value for the constant is 0.0.
DEFAULT_CONSTANT_VALUE - Static variable in class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction
The default constant value is 0.0.
DEFAULT_CONSTANT_WEIGHT - Static variable in class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction
The default constant weight is 0.0.
DEFAULT_COOLING_FACTOR - Static variable in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
The default cooling factor for learning, 0.1.
DEFAULT_COST_FUNCTION - Static variable in class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
Default cost function, SumSquaredErrorCostFunction
DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianClusterCreator
Default covariance, 1.0E-4
DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.initializer.NeighborhoodGaussianClusterInitializer
Default covariance to put on the diagonal entries, 1.0.
DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator
Default covariance, 1.0E-5.
DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.MaximumLikelihoodEstimator
Default covariance used in estimation, 1.0E-5.
DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
Default covariance of the statistics, 1.0E-5.
DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.WeightedMaximumLikelihoodEstimator
Default covariance used in estimation, 1.0E-5.
DEFAULT_COVARIANCE_DIVISOR - Static variable in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
Default covariance divisor, 1.0.
DEFAULT_COVARIANCE_INVERSE - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimatorCovarianceInverse
Default covariance Inverse, 99999.99999999999.
DEFAULT_COVARIANCE_INVERSE - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
Default covariance of the statistics, 99999.99999999999.
DEFAULT_COVARIANCE_SYMMETRY_TOLERANCE - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Tolerance check for symmetry covariance tolerance, 1.0E-5.
DEFAULT_CURVATURE_CONDITION - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased
This is a fairly accurate line search, 0.1.
DEFAULT_DAMPING - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
Default initial value of the damping factor 1.0
DEFAULT_DAMPING_DIVISOR - Static variable in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
Divisor of the damping factor on unsuccessful iteration, dividing damping factor on cost-reducing iteration 2.0
DEFAULT_DAMPING_DIVISOR - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
Divisor of the damping factor on unsuccessful iteration, dividing damping factor on cost-reducing iteration 10.0
DEFAULT_DAMPING_FACTOR - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The default damping factor (lambda) is 0.5.
DEFAULT_DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.DiagonalCovarianceLearner
The default value for default covariance is 1.0E-5.
DEFAULT_DEFAULT_COVARIANCE - Static variable in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.FullCovarianceLearner
The default value for default covariance is 1.0E-5.
DEFAULT_DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
The default variance is 1.0.
DEFAULT_DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
The default variance is 1.0.
DEFAULT_DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.IncrementalEstimator
The default value for the default variance is 1.0E-5.
DEFAULT_DEGREE - Static variable in class gov.sandia.cognition.learning.function.kernel.PolynomialKernel
The default degree is 2.
DEFAULT_DEGREES_OF_FREEDOM - Static variable in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Default degrees of freedom, 2.0.
DEFAULT_DEGREES_OF_FREEDOM - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
Default degrees of freedom, 3.0.
DEFAULT_DEGREES_OF_FREEDOM - Static variable in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Default degrees of freedom, 1d/0d.
DEFAULT_DEGREES_OF_FREEDOM - Static variable in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Default degrees of freedom, 3.0.
DEFAULT_DELIMITER - Static variable in class gov.sandia.cognition.math.matrix.AbstractVector
The default delimiter for a vector.
DEFAULT_DELTA_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
Default deltaSize, 1.0E-5
DEFAULT_DEMOTE_TO_ZERO - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
The default value of demoteToZero is false.
DEFAULT_DENSE_INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.MatrixFactory
The default dense implementation of a MatrixFactory.
DEFAULT_DENSE_INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.VectorFactory
The default VectorFactory instance.
DEFAULT_DERIVATIVE_GAIN - Static variable in class gov.sandia.cognition.math.signals.PIDController
Default derivative-error gain, 0.25.
DEFAULT_DIAGONAL_INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.MatrixFactory
The default implementation of a factory that creates a DiagonalMatrix
DEFAULT_DIMENSION - Static variable in class gov.sandia.cognition.statistics.bayesian.KalmanFilter
Default autonomous dimension, 1.
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering
Default dimensionality, 2.
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator
Default dimensionality, 1.
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
Default inverse scale dimensionality, 2.
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Default dimensionality of the Gaussian, 2
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
Default dimensionality, 2.
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
Default dimensionality, 2.
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
Default dimensionality, 2.
DEFAULT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
Default dimensionality of the precision matrix, 2.
DEFAULT_EFFECTIVE_ZERO - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
The default effective value for zero is 1.0E-10.
DEFAULT_EFFECTIVE_ZERO - Static variable in class gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator
The default effective zero value is 0.0.
DEFAULT_ENSEMBLE_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
The default ensemble size is 100.
DEFAULT_EPS - Static variable in class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
The default stopping epsilon that will be used
DEFAULT_EPS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
The default eps is 0.5.
DEFAULT_ERROR_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
The default error tolerance is 0.001, which is what was recommended in the original Sequential Minimal Optimization paper.
DEFAULT_ETA - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron
The default value of eta is 0.01.
DEFAULT_FACTOR_COUNT - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default number of factors is 10.
DEFAULT_FACTOR_REGULARIZATION - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default factor regularization parameter is 0.01.
DEFAULT_FALSE_VALUE - Static variable in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
The default value for false is -1.0.
DEFAULT_FIELD_SEPARATOR - Static variable in class gov.sandia.cognition.text.convert.DocumentFieldConcatenator
The default field separator is a newline.
DEFAULT_FORMAT - Static variable in class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter
The default format for reporting performance is "Iteration %d. %s: %s".
DEFAULT_FORMAT - Static variable in class gov.sandia.cognition.algorithm.event.IterationStartReporter
The default format is "Iteration %d".
DEFAULT_FORMAT - Static variable in class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
The default format for reporting performance is "Iteration %d. Train: %s. Validation: %s".
DEFAULT_FUNCTION_MINIMIZER - Static variable in class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer
Default function minimizer, FunctionMinimizerDirectionSetPowell
DEFAULT_FUNCTION_MINIMIZER - Static variable in class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer
Default function minimizer, FunctionMinimizerBFGS with LineMinimizerBacktracking
DEFAULT_GEOMETRIC_DECREASE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
Default amount to decrease the step amount each iteration, 0.5.
DEFAULT_HIGH_VALUE - Static variable in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Default high value, 1.0
DEFAULT_INDEX - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster
The default index is -1.
DEFAULT_INDEX - Static variable in class gov.sandia.cognition.learning.function.categorization.VectorElementThresholdCategorizer
The default index is -1.
DEFAULT_INDEX - Static variable in class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction
The default index is 0.
DEFAULT_INDEX - Static variable in class gov.sandia.cognition.text.term.DefaultIndexedTerm
The default index is -1.
DEFAULT_INITIAL_CAPACITY - Static variable in class gov.sandia.cognition.collection.DynamicArrayMap
The default initial capacity is 10.
DEFAULT_INITIAL_CAPACITY - Static variable in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
The default capacity is 16.
DEFAULT_INITIAL_CAPACITY - Static variable in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
Default initial capacity, 10.
DEFAULT_INITIAL_GUESS - Static variable in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
Default initial guess, 0.0
DEFAULT_INITIALIZATION_RANGE - Static variable in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Default initialization range, 0.001.
DEFAULT_INTEGRAL_GAIN - Static variable in class gov.sandia.cognition.math.signals.PIDController
Default integral-error gain, 0.0.
DEFAULT_INTERPOLATOR - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased
Default interpolator to use to create a new candidate point to evaluate
DEFAULT_INTERPOLATOR - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeFree
Default interpolation algorithm, LineBracketInterpolatorBrent.
DEFAULT_ITERATION - Static variable in class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
The default iteration number is zero.
DEFAULT_ITERATIONS_PER_SAMPLE - Static variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The default number of iterations per sample is 100.
DEFAULT_K - Static variable in interface gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighbor
The default value for k is 1.
DEFAULT_KAPPA - Static variable in class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
The default value for kappa is 1.0.
DEFAULT_KERNEL_CACHE_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
The default size of the kernel cache.
DEFAULT_KNOWN_VARIANCE - Static variable in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator
Default known variance of the estimated distribution, 1.0.
DEFAULT_LAMBDA - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
The default value of lambda is 0.001.
DEFAULT_LEAF_COUNT_THRESHOLD - Static variable in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
The default threshold for making a leaf node based on count.
DEFAULT_LEAF_COUNT_THRESHOLD - Static variable in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner
The default threshold for making a leaf node based on count.
DEFAULT_LEAKAGE - Static variable in class gov.sandia.cognition.learning.function.scalar.LeakyRectifiedLinearFunction
The default leakage is 0.01.
DEFAULT_LEARNING_RATE - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineStochasticGradient
The default learning rate is 0.001.
DEFAULT_LEARNING_RATE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Default learning rate
DEFAULT_LENGTH - Static variable in class gov.sandia.cognition.text.AbstractOccurrenceInText
The default length is 0.
DEFAULT_LINE_MINIMIZER - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
Default line minimization algorithm, LineMinimizerDerivativeBased
DEFAULT_LINE_MINIMIZER - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell
Default line minimization algorithm, LineMinimizerDerivativeFree
DEFAULT_LINE_MINIMIZER - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton
Default line minimization algorithm, LineMinimizerDerivativeBased
DEFAULT_LINE_MINIMIZER - Static variable in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
Default line minimization algorithm, LineMinimizerDerivativeFree
DEFAULT_LINE_MINIMIZER - Static variable in class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm
Default line minimizer, LineMinimizerDerivativeBased.
DEFAULT_LOCATION - Static variable in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Default location, 0.0.
DEFAULT_LOCATION - Static variable in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Default location, 0.0.
DEFAULT_LOG_NORMAL_MEAN - Static variable in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
Default log normal mean, 0.0.
DEFAULT_LOG_NORMAL_VARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
Default log normal variance, 1.0.
DEFAULT_LOW_VALUE - Static variable in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Default low value, -1.0
DEFAULT_MARGIN_NEGATIVE - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
The default negative margin, 0.0.
DEFAULT_MARGIN_NEGATIVE - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
The default negative margin, 0.0.
DEFAULT_MARGIN_POSITIVE - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
The default positive margin, 0.0.
DEFAULT_MARGIN_POSITIVE - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
The default positive margin, 0.0.
DEFAULT_MAX - Static variable in class gov.sandia.cognition.statistics.distribution.UniformDistribution
Default max, 1.0.
DEFAULT_MAX_BUFFER_SIZE - Static variable in class gov.sandia.cognition.learning.data.feature.LinearRegressionCoefficientExtractor
Default maximum buffer size, 20.
DEFAULT_MAX_CRITERION_DECREASE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The default maximum decrease in the training criterion is 1.0.
DEFAULT_MAX_DEPTH - Static variable in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
The default maximum depth to grow the tree to.
DEFAULT_MAX_DEPTH - Static variable in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner
The default maximum depth to grow the tree to.
DEFAULT_MAX_DISTANCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The default maximum distance is 1.7976931348623157E308.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
The default maximum number of iterations that will be run
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
The default number of maximum iterations, 1000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The default maximum number of iterations is 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The default maximum number of iterations 2147483647
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
The default maximum number of iterations 2147483647
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
The default maximum number of iterations is 1000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
The default maximum number of iterations is 100000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The default maximum number of iterations is 2147483647.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
The default maximum number of iterations is 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
The default maximum number of iterations is 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The default maximum number of iterations is 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost
The default maximum number of iterations is 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default maximum number of iterations is 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
The default maximum number of iterations, 1000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
Default maximum number of iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
Default maximum number of iterations before stopping, 1000
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell
Default maximum number of iterations before stopping, 1000
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Default max iterations
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead
Default max iterations, 4000
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton
Default maximum number of iterations before stopping, 1000
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Default number of iterations to run the algorithm, 100
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
The default maximum number of iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
The default maximum number of iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
The default maximum number of iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
The default maximum number of iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
Default number of iterations before stopping, 100
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Default maximum number of iterations before stopping 1000
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
The default maximum number of iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
Default maximum number of iterations before stopping
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
Default number of iterations before stopping, 100
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder
Default maximum number of iterations, 1000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
Default max iterations, 100
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The default maximum number of iterations is 10000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
The default maximum number of iterations is 1000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
The default maximum number of iterations, 1000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner
Default max iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
Default max iterations, 100.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The default maximum number is iterations is 10000.
DEFAULT_MAX_ITERATIONS - Static variable in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
The default maximum number of iterations is 250.
DEFAULT_MAX_ITERATIONS_WITHOUT_IMPROVEMENT - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
Default maximum number of iterations without improvement before stopping 4
DEFAULT_MAX_MAGNITUDE - Static variable in class gov.sandia.cognition.learning.function.scalar.AtanFunction
The default max magnitude, which is PI / 2.
DEFAULT_MAX_MIN_DISTANCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Deprecated.
DEFAULT_MAX_NUM_POINTS - Static variable in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Default number of points, 50.
DEFAULT_MAX_PENALTY - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
The default maximum penalty is infinite, which means that it is hard-assignment.
DEFAULT_MAX_SUPPORT - Static variable in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
The default maximum support is 0.
DEFAULT_MAX_WEIGHT - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
The default maximum weight is 100.0.
DEFAULT_MAXIMUM_ITERATIONS - Static variable in class gov.sandia.cognition.math.matrix.decomposition.EigenvectorPowerIteration
Default maximum iterations for power iteration, 100.
DEFAULT_MAXIMUM_LENGTH - Static variable in class gov.sandia.cognition.text.term.filter.TermLengthFilter
The default maximum length is 28.
DEFAULT_MEAN - Static variable in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
The default mean is 0.0.
DEFAULT_MEAN - Static variable in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
Default mean, 0.0.
DEFAULT_MEAN - Static variable in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
Default mean, 0.0.
DEFAULT_MEAN - Static variable in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Default mean, 0.0.
DEFAULT_MEAN - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
Default mean, 0.0.
DEFAULT_MEASUREMENT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression
Default assumed variance of the measurements, 1.0.
DEFAULT_MIN - Static variable in class gov.sandia.cognition.statistics.distribution.UniformDistribution
Default min, 0.0.
DEFAULT_MIN_CHANGE - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
The default minimum change is 1.0E-5.
DEFAULT_MIN_CHANGE - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
The default minimum change is 1.0E-4.
DEFAULT_MIN_CLUSTER_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The default minimum number of elements per cluster is 1.
DEFAULT_MIN_FUNCTION_VALUE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased
Default minimum function value, 0.0.
DEFAULT_MIN_MARGIN - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
The default minimum margin is 0.0.
DEFAULT_MIN_MARGIN - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
The default minimum margin is 0.0.
DEFAULT_MIN_MARGIN - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron
The default minimum margin is 0.0.
DEFAULT_MIN_MARGIN - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.ProportionalUpdate
The default minimum margin is 0.001.
DEFAULT_MIN_NUM_CLUSTERS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The default minimum number of clusters is 1.
DEFAULT_MIN_SAMPLES - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
The default minimum samples is 5.
DEFAULT_MIN_SENSITIVITY - Static variable in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
The default minimum sensitivity, 10.0.
DEFAULT_MIN_SPLIT_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
The default value for the minimum split size is 1.
DEFAULT_MIN_SPLIT_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdVarianceLearner
The default value for the minimum split size is 1.
DEFAULT_MIN_SUPPORT - Static variable in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
The default minimum support is 0.
DEFAULT_MINIMUM_CHANGE - Static variable in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
The default minimum change is 1.0E-10.
DEFAULT_MINIMUM_LENGTH - Static variable in class gov.sandia.cognition.text.term.filter.TermLengthFilter
The default minimum length is 3.
DEFAULT_MOMENTUM - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Default momentum
DEFAULT_N - Static variable in class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator
Default n, 1.
DEFAULT_N - Static variable in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Default n, 1.
DEFAULT_N - Static variable in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
Default N, 1.
DEFAULT_NAME - Static variable in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule
Default name given to modules of this type
DEFAULT_NAME - Static variable in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner
Default name for this module
DEFAULT_NAME - Static variable in class gov.sandia.cognition.text.document.DefaultTextField
The default name for the field is the empty string.
DEFAULT_NULL_VALUE - Static variable in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
The default value for null is 0.0.
DEFAULT_NUM_CLASSES - Static variable in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator
Default number of classes/labels, 2.
DEFAULT_NUM_CLASSES - Static variable in class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
Default number of classes (labels or parameters), 2.
DEFAULT_NUM_CLASSES - Static variable in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
Default number of classes (labels or parameters), 2.
DEFAULT_NUM_CLUSTERS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
The default number of clusters is 10.
DEFAULT_NUM_CUSTOMERS - Static variable in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Default number of customers, 2.
DEFAULT_NUM_FOLDS - Static variable in class gov.sandia.cognition.learning.experiment.CrossFoldCreator
The default number of folds is 10.
DEFAULT_NUM_FOLDS - Static variable in class gov.sandia.cognition.learning.experiment.RandomFoldCreator
The default number of folds is 10.
DEFAULT_NUM_INITIAL_CLUSTERS - Static variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Default number of initial clusters
DEFAULT_NUM_REQUESTED_CLUSTERS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
The default number of requested clusters is 10.
DEFAULT_NUM_REQUESTED_CLUSTERS - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
The default number of requested clusters is 2147483647.
DEFAULT_NUM_SAMPLES - Static variable in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
Default number of sample/iterations, 1000.
DEFAULT_NUM_SAMPLES - Static variable in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling
Default maximum number of samples, 1000.
DEFAULT_NUM_SAMPLES - Static variable in class gov.sandia.cognition.statistics.bayesian.RejectionSampling
Default number of samples, 1000.
DEFAULT_NUM_SAMPLES - Static variable in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Number of samples to draw for Monte Carlo estimates, 1000.
DEFAULT_NUM_SAMPLES - Static variable in class gov.sandia.cognition.statistics.UnivariateRandomVariable
Default number of samples to draw from a distribution to perform the empirical algebra approximation, 10000.
DEFAULT_NUM_SPLITS - Static variable in class gov.sandia.cognition.learning.experiment.RandomByTwoFoldCreator
The default number of splits is 5.
DEFAULT_NUM_STATES - Static variable in class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain
Default number of states, 3.
DEFAULT_NUM_THREADS - Static variable in class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
The default number of threads that will be used
DEFAULT_NUM_TRIALS - Static variable in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
The default number of trials is 10.
DEFAULT_NUM_TRIALS - Static variable in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator
Default number of trials, 2.
DEFAULT_NUM_TRIALS - Static variable in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
Default number of trials, 1.
DEFAULT_NUM_TRIALS - Static variable in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
Default number of trials, 1.
DEFAULT_NUMERICAL_DERIVATIVE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
Default flag to use numerical differentiation, true.
DEFAULT_OFFSET - Static variable in class gov.sandia.cognition.learning.function.scalar.LinearFunction
The default offset is 0.0.
DEFAULT_OUTLIER_PERCENT - Static variable in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer.Learner
The default percentage of outliers is 0.0.
DEFAULT_OUTPUT_DIMENSIONALITY - Static variable in class gov.sandia.cognition.learning.data.feature.FeatureHashing
The default output dimensionality is 100.
DEFAULT_OUTPUT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
Default output variance, 1.0.
DEFAULT_OVERRELAXATION - Static variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
The default overrelaxation is 1.3.
DEFAULT_P - Static variable in class gov.sandia.cognition.statistics.distribution.BernoulliDistribution
Default Bernoulli parameter, 0.5
DEFAULT_P - Static variable in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
Default p, 0.5.
DEFAULT_P - Static variable in class gov.sandia.cognition.statistics.distribution.GeometricDistribution
Default p, 0.5.
DEFAULT_P - Static variable in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
Default p, 0.5.
DEFAULT_PAIRWISE_TEST - Static variable in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison
Default pair-wise confidence test: Student's Paired t-test.
DEFAULT_PERCENT_TO_SAMPLE - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
The default percent to sample is 1.0 (which represents 100%).
DEFAULT_PERCENT_TO_SAMPLE - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The default percent to sample 0.1.
DEFAULT_PERCENT_TO_SAMPLE - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
The default percent to sample is 1.0 (which represents 100%).
DEFAULT_PERCENT_TO_SAMPLE - Static variable in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
The default percent to sample is 0.1.
DEFAULT_POINT - Static variable in class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
Default point, 0.0
DEFAULT_POST_HOC_TEST - Static variable in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment
Default post-host multiple hypothesis comparison test, NemenyiConfidence.
DEFAULT_POWER - Static variable in class gov.sandia.cognition.learning.function.distance.MinkowskiDistanceMetric
The default power is 2.0.
DEFAULT_PRECISION - Static variable in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Default precision, 1.0.
DEFAULT_PRECISION - Static variable in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Default precision, 1.0.
DEFAULT_PRECISION - Static variable in class gov.sandia.cognition.text.evaluation.DefaultPrecisionRecallPair
The default precision is 0.0.
DEFAULT_PREDICTION_HORIZION - Static variable in class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner
The default prediction horizon is 1.
DEFAULT_PREDICTION_HORIZON - Static variable in class gov.sandia.cognition.learning.algorithm.TimeSeriesPredictionLearner
Default prediction horizon, 1.
DEFAULT_PRIME - Static variable in class gov.sandia.cognition.hash.FNV1a32Hash
Default FNV-1 prime, 16777619.
DEFAULT_PRIME - Static variable in class gov.sandia.cognition.hash.FNV1a64Hash
Default FNV-1 prime, 1099511628211L.
DEFAULT_PROBABILITY - Static variable in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.VectorizableCrossoverFunction
Default probability of cross over, 0.5.
DEFAULT_PROPORTION_INCORRECT_IN_SAMPLE - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
By default use 50% incorrect (and 50%) correct in the percent to sample.
DEFAULT_PROPORTIONAL_GAIN - Static variable in class gov.sandia.cognition.math.signals.PIDController
Default proportional-error gain, 0.5.
DEFAULT_PSEUDO_INVERSE_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LinearBasisRegression
Tolerance for the pseudo inverse in the learn method, 1.0E-10.
DEFAULT_PSEUDO_INVERSE_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression
Tolerance for the pseudo inverse in the learn method, 1.0E-10.
DEFAULT_PSEUDO_INVERSE_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.regression.MultivariateLinearRegression
Tolerance for the pseudo inverse in the learn method, 1.0E-10.
DEFAULT_R - Static variable in class gov.sandia.cognition.learning.algorithm.confidence.AdaptiveRegularizationOfWeights
The default value of r is 0.001.
DEFAULT_R - Static variable in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
Default r, 1.0.
DEFAULT_RADIUS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.Ballseptron
The default radius is 0.1.
DEFAULT_RANDOM_SEED - Static variable in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Default random seed, 1.
DEFAULT_RANGE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.initializer.NeighborhoodGaussianClusterInitializer
Default range of the "neighborhood", 1.0.
DEFAULT_RATE - Static variable in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution
Default rate, 1.0.
DEFAULT_RATE - Static variable in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
Default rate parameter, 1.0.
DEFAULT_RECALL - Static variable in class gov.sandia.cognition.text.evaluation.DefaultPrecisionRecallPair
The default recall is 0.0.
DEFAULT_REDUCTION_TEST - Static variable in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
Reduction test for Equation 6.1.16 in Fletcher PMOO, 0.2 given on page 117.
DEFAULT_REESTIMATE_ALPHA - Static variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
The default value for re-estimating alpha is true.
DEFAULT_REESTIMATE_INITIAL_PROBABILITY - Static variable in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
Default flag to re-estimate initial probabilities, true.
DEFAULT_REGULARIZATION - Static variable in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
Default regularization, 0.0.
DEFAULT_REGULARIZATION - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression
Default regularization, 0.0.
DEFAULT_REGULARIZATION - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
Default regularization, 0.0.
DEFAULT_REGULARIZATION - Static variable in class gov.sandia.cognition.learning.algorithm.regression.MultivariateLinearRegression
Default regularization, 0.0.
DEFAULT_REGULARIZATION_WEIGHT - Static variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The default regularization weight is 1.0E-4.
DEFAULT_REQUESTED_RANK - Static variable in class gov.sandia.cognition.text.topic.LatentSemanticAnalysis
The default requested rank is 10.
DEFAULT_REQUESTED_RANK - Static variable in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
The default requested rank is 10.
DEFAULT_ROOT_BRACKETER - Static variable in class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder
Default root-bracketing algorithm, RootBracketExpander.
DEFAULT_ROOT_FINDER - Static variable in class gov.sandia.cognition.statistics.method.InverseTransformSampling
Default root finding method for the algorithm, RootFinderRiddersMethod.
DEFAULT_SAMPLE_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The default sample size is 100.
DEFAULT_SAMPLES - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering
Default number of samples, 1000.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Default scale, 1.0.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Default scale, 1.0.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Default scale, 1.0.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
Default scale, 1.0.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
Default scale, 1.0.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
Default scale, 1.0.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Default scale, 1.0.
DEFAULT_SCALE - Static variable in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Default scale, 1.0
DEFAULT_SCALE_FACTOR - Static variable in class gov.sandia.cognition.learning.function.vector.LinearVectorFunction
Scale factor for default constructor, 1.0.
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.Eva32Hash
Default seed: ( 0, 0, 0, 0 ).
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.Eva64Hash
Default seed: ( 0, 0, 0, 0, 0, 0, 0, 0 ).
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.FNV1a32Hash
Byte representation of DEFAULT_SEED_INT
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.FNV1a64Hash
Byte representation of DEFAULT_SEED_INT
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.MD5Hash
Default seed
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.Murmur32Hash
Default seed: ( 0, 0, 0, 0).
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.Prime32Hash
Default seed, the first seed from the SHA-2 256-bit hash.
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.Prime64Hash
Default seed, the first seed from the SHA-2 512-bit hash.
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.SHA1Hash
Default seed
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.SHA256Hash
Default seed
DEFAULT_SEED - Static variable in class gov.sandia.cognition.hash.SHA512Hash
Default seed
DEFAULT_SEED_INT - Static variable in class gov.sandia.cognition.hash.FNV1a32Hash
Default FNV-1 seed, -2128831035 == (signed) 2166136261
DEFAULT_SEED_LONG - Static variable in class gov.sandia.cognition.hash.FNV1a64Hash
Default FNV-1 seed, -3750763034362895579L == (signed) 14695981039346656037
DEFAULT_SEED_SCALE - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default seed initialization scale is 0.01.
DEFAULT_SELF_DIVERGENCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The default self similarity is 0.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator
Default shape, 1.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Default shape, 1.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Default shape, 1.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
Default shape, 3.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Default shape, 3.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Default shape, 2.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Default shape, 1.0.
DEFAULT_SHAPE - Static variable in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
Default shape, 3.0.
DEFAULT_SHIFT - Static variable in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Default shift, 0.0.
DEFAULT_SIGMA - Static variable in class gov.sandia.cognition.learning.function.kernel.RadialBasisKernel
The default value for sigma is 1.0.
DEFAULT_SIZE - Static variable in class gov.sandia.cognition.learning.data.feature.RandomSubspace
The default size is 10.
DEFAULT_SIZE - Static variable in class gov.sandia.cognition.text.term.filter.NGramFilter
The default is a bigram.
DEFAULT_SLOPE - Static variable in class gov.sandia.cognition.learning.function.scalar.LinearFunction
The default slope is 1.0.
DEFAULT_SLOPE_CONDITION - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased
This is a fairly accurate line search, 0.01.
DEFAULT_SMOOTHING_WINDOW_SIZE - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
The default smoothing window size is 25.
DEFAULT_SPARSE_INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.MatrixFactory
The default sparse implementation of a MatrixFactory.
DEFAULT_SPARSE_INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.VectorFactory
The default SparseVectorFactory instance.
DEFAULT_SPLIT_THRESHOLD - Static variable in class gov.sandia.cognition.math.geometry.Quadtree
This is the default minimum number of items allowed in a leaf node, 10.
DEFAULT_SQUASHING_FUNCTION - Static variable in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Default squashing function, AtanFunction.
DEFAULT_START - Static variable in class gov.sandia.cognition.text.AbstractOccurrenceInText
The default start is 0.
DEFAULT_STARTING_TEMPERATURE - Static variable in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
The default starting temperature for the algorithm, 1.0.
DEFAULT_STOPPING_THRESHOLD - Static variable in class gov.sandia.cognition.math.matrix.decomposition.EigenvectorPowerIteration
Default stopping threshold for power iteration, 1.0E-5.
DEFAULT_SUFFICIENT_DECREASE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
Default sufficient decrease value, 0.5
DEFAULT_TEXT_FILE_EXTENSIONS - Static variable in class gov.sandia.cognition.text.document.extractor.TextDocumentExtractor
The default set of file extensions for text files.
DEFAULT_THRESHOLD - Static variable in class gov.sandia.cognition.learning.function.categorization.AbstractThresholdBinaryCategorizer
Default threshold, 0.0.
DEFAULT_THRESHOLD - Static variable in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Default threshold, 0.0
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
Default tolerance, 1.0E-5
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell
Default tolerance, 1.0E-5
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Default tolerance
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead
Default tolerance, 0.001
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton
Default tolerance, 1.0E-5
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Default tolerance of the algorithm 1.0E-5
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolator
Default collinearity or identity tolerance, 1.0E-6
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
Default tolerance change in weights before stopping, 1.0E-10
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Default convergence criterion 1.0E-7
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
Default tolerance stopping criterion
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
Default tolerance change in weights before stopping, 1.0E-10
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder
Default tolerance of the algorithm, 1.0E-5.
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner
Default tolerance, 1.0E-5.
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
Default tolerance, 1.0E-5.
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.statistics.method.InverseTransformSampling
Tolerance for Newton's method, 1.0E-10.
DEFAULT_TOLERANCE - Static variable in class gov.sandia.cognition.statistics.method.StudentTConfidence
Default tolerance for the standard deviation, 1.0E-10.
DEFAULT_TOPIC_COUNT - Static variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The default topic count is 10.
DEFAULT_TRAINING_PERCENT - Static variable in class gov.sandia.cognition.learning.data.RandomDataPartitioner
The default percentage of training data is 50%.
DEFAULT_TREATMENT_COUNT - Static variable in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Default treatment count, 2.
DEFAULT_TRUE_VALUE - Static variable in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
The default value for true is 1.0.
DEFAULT_UNCOMPENSATED_ALPHA - Static variable in interface gov.sandia.cognition.statistics.method.MultipleHypothesisComparison
Default uncompensatedAlpha, 0.05.
DEFAULT_UPDATE_BIAS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
MIRA does not use a bias by default.
DEFAULT_UPDATE_BIAS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron
By default the Passive-Aggressive Perceptron does not use a bias.
DEFAULT_UPDATE_BIAS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron
By default the bias is updated.
DEFAULT_UPDATE_BIAS - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
Algorithm does not update the bias by default.
DEFAULT_V1 - Static variable in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
Default value of v1, 3.0.
DEFAULT_V2 - Static variable in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
Default value of v2, 5.0.
DEFAULT_VALUE - Static variable in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeNode
The default value for the node is 0.0.
DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
The default variance is 1.0.
DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.StudentTDistribution.MaximumLikelihoodEstimator
Typical value of a defaultVariance, 1.0E-5
DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
Default variance, 1.0.
DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.MaximumLikelihoodEstimator
Typical value of a defaultVariance, 1.0E-5
DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.montecarlo.MultivariateMonteCarloIntegrator
Default variance to add to the Gaussian, 0.0.
DEFAULT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.montecarlo.UnivariateMonteCarloIntegrator
Default variance to add to the Gaussian, 0.0.
DEFAULT_VOTE_OUT_OF_BAG_ONLY - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The default value to vote out-of-bag.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble
The default weight when adding a member is 1.0.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble
The default weight when adding a member is 1.0.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble
The default weight when adding a member is 1.0.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
The default weight is 1.0.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
The default weight is 1.0.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant
The default weight is 0.0.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.learning.function.kernel.WeightedKernel
The default weight is 1.0.
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.util.AbstractWeighted
Default weight, 1.0
DEFAULT_WEIGHT - Static variable in class gov.sandia.cognition.util.DefaultWeightedPair
The default weight for the pair is 0.0.
DEFAULT_WEIGHT_REGULARIZATION - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default weight regularization parameter is 0.001.
DEFAULT_WEIGHT_UPDATE - Static variable in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
The default value of the weight update is 2.0.
DEFAULT_WEIGHT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
Default weight variance, 1.0.
DEFAULT_WEIGHT_VARIANCE - Static variable in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression
Default weight variance, 1.0.
DEFAULT_WEIGHTS_ENABLED - Static variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The default for weights enabled is true.
DefaultBayesianParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>,PriorType extends Distribution<ParameterType>> - Class in gov.sandia.cognition.statistics.bayesian
Default implementation of BayesianParameter using reflection.
DefaultBayesianParameter(ConditionalType, String) - Constructor for class gov.sandia.cognition.statistics.bayesian.DefaultBayesianParameter
Creates a new instance of DefaultBayesianParameter
DefaultBayesianParameter(ConditionalType, String, PriorType) - Constructor for class gov.sandia.cognition.statistics.bayesian.DefaultBayesianParameter
Creates a new instance of DefaultBayesianParameter
DefaultBinaryConfusionMatrix - Class in gov.sandia.cognition.learning.performance.categorization
A default implementation of the BinaryConfusionMatrix.
DefaultBinaryConfusionMatrix() - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Creates a new, empty DefaultBinaryConfusionMatrix.
DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer - Class in gov.sandia.cognition.learning.performance.categorization
A confusion matrix summarizer that summarizes actual-predicted pairs.
DefaultBinaryConfusionMatrix.CombineSummarizer - Class in gov.sandia.cognition.learning.performance.categorization
A confusion matrix summarizer that adds together confusion matrices.
DefaultBinaryConfusionMatrix.PerformanceEvaluator<InputType> - Class in gov.sandia.cognition.learning.performance.categorization
An implementation of the SupervisedPerformanceEvaluator interface for creating a DefaultBinaryConfusionMatrix.
DefaultBinaryConfusionMatrixConfidenceInterval - Class in gov.sandia.cognition.learning.performance.categorization
Puts Student-t ConfidenceIntervals on each entry of the ConfusionMatrix
DefaultBinaryConfusionMatrixConfidenceInterval(double, ConfidenceInterval, ConfidenceInterval, ConfidenceInterval, ConfidenceInterval) - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Creates a new instance of ConfusionMatrixConfidenceInterval
DefaultBinaryConfusionMatrixConfidenceInterval.Summary - Class in gov.sandia.cognition.learning.performance.categorization
An implementation of the Summarizer interface for creating a ConfusionMatrixInterval
DefaultBooleanToNumberConverter - Class in gov.sandia.cognition.data.convert.number
Converts a Boolean to a Number by using predefined values for true, false, and (optionally) null.
DefaultBooleanToNumberConverter() - Constructor for class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
Creates a new DefaultBooleanToNumberConverter with default values.
DefaultBooleanToNumberConverter(Number, Number, Number) - Constructor for class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
Creates a new DefaultBooleanToNumberConverter.
DefaultBooleanToNumberConverter.Reverse - Class in gov.sandia.cognition.data.convert.number
The reverse converter for the DefaultBooleanToNumberConverter.
DefaultCluster<ClusterType> - Class in gov.sandia.cognition.learning.algorithm.clustering.cluster
The DefaultCluster class implements a default cluster which contains a list of members in an ArrayList along with an index that identifies the cluster.
DefaultCluster() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster
Creates a new instance of CentroidCluster.
DefaultCluster(int) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster
Creates a new instance of CentroidCluster.
DefaultCluster(Collection<? extends ClusterType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster
Creates a new instance of CentroidCluster.
DefaultCluster(int, Collection<? extends ClusterType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster
Creates a new instance of CentroidCluster.
DefaultClusterCreator<DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.cluster
The DefaultClusterCreator class implements a default ClusterCreator that just creates a DefaultCluster from the given list of members.
DefaultClusterCreator() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultClusterCreator
Creates a new DefaultClusterCreator.
DefaultClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering.hierarchy
A default implementation of the cluster hierarchy node.
DefaultClusterHierarchyNode() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode
Creates a new DefaultClusterHierarchyNode.
DefaultClusterHierarchyNode(ClusterType) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode
Creates a new DefaultClusterHierarchyNode.
DefaultClusterHierarchyNode(ClusterType, List<ClusterHierarchyNode<DataType, ClusterType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode
Creates a new DefaultClusterHierarchyNode.
DefaultClusterHierarchyNode(ClusterType, ClusterHierarchyNode<DataType, ClusterType>, ClusterHierarchyNode<DataType, ClusterType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode
Creates a new DefaultClusterHierarchyNode.
DefaultCogxel - Class in gov.sandia.cognition.framework
The DefaultCogxel provides a default implementation of the Cogxel interface that just stores the necessary peices of information: the SemanticIdentifier and its activation.
DefaultCogxel(SemanticIdentifier) - Constructor for class gov.sandia.cognition.framework.DefaultCogxel
Creates a new instance of Cogxel.
DefaultCogxel(SemanticIdentifier, double) - Constructor for class gov.sandia.cognition.framework.DefaultCogxel
Creates a new instance of Cogxel.
DefaultCogxel(DefaultCogxel) - Constructor for class gov.sandia.cognition.framework.DefaultCogxel
Creates a copy of a given Cogxel.
DefaultCogxelFactory - Class in gov.sandia.cognition.framework
This class implements a CogxelFactory that returns the default type of DefaultCogxel.
DefaultCogxelFactory() - Constructor for class gov.sandia.cognition.framework.DefaultCogxelFactory
Creates a new instance of DefaultCogxelFactory.
DefaultComparator<T extends java.lang.Comparable<? super T>> - Class in gov.sandia.cognition.collection
A default comparator that just calls compare on the comparable generic it uses.
DefaultComparator() - Constructor for class gov.sandia.cognition.collection.DefaultComparator
Creates a new DefaultComparator.
DefaultConfidenceWeightedBinaryCategorizer - Class in gov.sandia.cognition.learning.function.categorization
A default implementation of the ConfidenceWeightedBinaryCategorizer that stores a full mean and covariance matrix.
DefaultConfidenceWeightedBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.DefaultConfidenceWeightedBinaryCategorizer
Creates a new, uninitialized DefaultConfidenceWeightedBinaryCategorizer.
DefaultConfidenceWeightedBinaryCategorizer(Vector, Matrix) - Constructor for class gov.sandia.cognition.learning.function.categorization.DefaultConfidenceWeightedBinaryCategorizer
Creates a new DefaultConfidenceWeightedBinaryCategorizer with the given mean and covariance.
DefaultConfusionMatrix<CategoryType> - Class in gov.sandia.cognition.learning.performance.categorization
A default implementation of the ConfusionMatrix interface.
DefaultConfusionMatrix() - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
Creates a new, empty DefaultConfusionMatrix.
DefaultConfusionMatrix(ConfusionMatrix<? extends CategoryType>) - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix
Creates a copy of a given confusion matrix.
DefaultConfusionMatrix.ActualPredictedPairSummarizer<CategoryType> - Class in gov.sandia.cognition.learning.performance.categorization
A confusion matrix summarizer that summarizes actual-predicted pairs.
DefaultConfusionMatrix.CombineSummarizer<CategoryType> - Class in gov.sandia.cognition.learning.performance.categorization
A confusion matrix summarizer that adds together confusion matrices.
DefaultConfusionMatrix.Factory<CategoryType> - Class in gov.sandia.cognition.learning.performance.categorization
A factory for default confusion matrices.
defaultCovariance - Variable in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.DiagonalCovarianceLearner
The default covariance.
defaultCovariance - Variable in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.FullCovarianceLearner
The default covariance.
defaultCovariance - Variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
Default covariance of the distribution
defaultCovarianceInverse - Variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
Default covariance inverse of the distribution
defaultDaemonThreadFactory() - Static method in class gov.sandia.cognition.algorithm.ParallelUtil
Creates a version of the default thread factory from Executors.defaultThreadFactory() that creates daemon threads.
DefaultDataDistribution<KeyType> - Class in gov.sandia.cognition.statistics.distribution
A default implementation of ScalarDataDistribution that uses a backing map.
DefaultDataDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
Default constructor
DefaultDataDistribution(int) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
Creates a new instance of DefaultDataDistribution
DefaultDataDistribution(DataDistribution<? extends KeyType>) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
Creates a new instance of DefaultDataDistribution
DefaultDataDistribution(Iterable<? extends KeyType>) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
Creates a new instance of ScalarDataDistribution
DefaultDataDistribution(Map<KeyType, MutableDouble>, double) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
Creates a new instance of
DefaultDataDistribution.DefaultFactory<DataType> - Class in gov.sandia.cognition.statistics.distribution
A factory for DefaultDataDistribution objects using some given initial capacity for them.
DefaultDataDistribution.Estimator<KeyType> - Class in gov.sandia.cognition.statistics.distribution
Estimator for a DefaultDataDistribution
DefaultDataDistribution.PMF<KeyType> - Class in gov.sandia.cognition.statistics.distribution
PMF of the DefaultDataDistribution
DefaultDataDistribution.WeightedEstimator<KeyType> - Class in gov.sandia.cognition.statistics.distribution
A weighted estimator for a DefaultDataDistribution
DefaultDateField - Class in gov.sandia.cognition.text.document
A field for storing a date.
DefaultDateField() - Constructor for class gov.sandia.cognition.text.document.DefaultDateField
Creates a new, empty DefaultDateField.
DefaultDateField(String, Date) - Constructor for class gov.sandia.cognition.text.document.DefaultDateField
Creates a new DefaultDateField.
DefaultDistributionParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>> - Class in gov.sandia.cognition.statistics
Default implementation of DistributionParameter using introspection.
DefaultDistributionParameter(ConditionalType, String) - Constructor for class gov.sandia.cognition.statistics.DefaultDistributionParameter
Creates a new instance of DefaultDistributionParameter
DefaultDistributionParameter(ConditionalType, PropertyDescriptor) - Constructor for class gov.sandia.cognition.statistics.DefaultDistributionParameter
Creates a new instance of DefaultDistributionParameter
DefaultDivergenceFunctionContainer<FirstType,SecondType> - Class in gov.sandia.cognition.learning.function.distance
The DefaultDivergenceFunctionContainer class implements an object that holds a divergence function.
DefaultDivergenceFunctionContainer() - Constructor for class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer
Creates a new instance of DefaultDivergenceFunctionContainer.
DefaultDivergenceFunctionContainer(DivergenceFunction<? super FirstType, ? super SecondType>) - Constructor for class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer
Creates a new instance of DefaultDivergenceFunctionContainer.
DefaultDivergenceFunctionContainer(DefaultDivergenceFunctionContainer<? super FirstType, ? super SecondType>) - Constructor for class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer
Creates a new instance of DefaultDivergenceFunctionContainer.
DefaultDocument - Class in gov.sandia.cognition.text.document
A default implementation of the Document interface.
DefaultDocument() - Constructor for class gov.sandia.cognition.text.document.DefaultDocument
Creates a new DefaultDocument.
DefaultDuration - Class in gov.sandia.cognition.time
A default implementation of the Duration interface.
DefaultDuration(double) - Constructor for class gov.sandia.cognition.time.DefaultDuration
Creates a new DefaultDuration representing the given number of milliseconds.
DefaultFactory<CreatedType> - Class in gov.sandia.cognition.factory
The DefaultFactory class is a default implementation of the Factory interface that takes a class as its parameter and uses the default constructor of the class, called through newInstance(), to create new objects of that class.
DefaultFactory(Class<? extends CreatedType>) - Constructor for class gov.sandia.cognition.factory.DefaultFactory
Creates a new DefaultFactory for the given class.
DefaultFactory() - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.DefaultFactory
Creates a new DefaultFactory with a default initial domain capacity.
DefaultFactory(int) - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.DefaultFactory
Creates a new DefaultFactory with a given initial domain capacity.
DefaultIdentifiedValue<IdentifierType,ValueType> - Class in gov.sandia.cognition.util
A default implementation of the IdentifiedValue interface that stores a value along with its identifier.
DefaultIdentifiedValue() - Constructor for class gov.sandia.cognition.util.DefaultIdentifiedValue
Creates a new DefaultIdentifiedValue with null identifier and value.
DefaultIdentifiedValue(IdentifierType, ValueType) - Constructor for class gov.sandia.cognition.util.DefaultIdentifiedValue
Creates a new DefaultIdentifiedValue with the given identifier and value.
DefaultIncrementalClusterCreator<DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.cluster
A default implementation of the IncrementalClusterCreator interface that just creates a cluster as having a collection of members.
DefaultIncrementalClusterCreator() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultIncrementalClusterCreator
Creates a new DefaultIncrementalClusterCreator.
DefaultIndexedTerm - Class in gov.sandia.cognition.text.term
Default implementation of the IndexedTerm interface.
DefaultIndexedTerm() - Constructor for class gov.sandia.cognition.text.term.DefaultIndexedTerm
Creates a new DefaultIndexedTerm with default values.
DefaultIndexedTerm(int, Term) - Constructor for class gov.sandia.cognition.text.term.DefaultIndexedTerm
Creates a new DefaultIndexedTerm with the given index and term.
DefaultIndexer<ValueType> - Class in gov.sandia.cognition.collection
A default implementation of the Indexer interface that simply maps objects to a range from 0 to n-1 in the order they are given.
DefaultIndexer() - Constructor for class gov.sandia.cognition.collection.DefaultIndexer
Creates a new, empty DefaultIndexer.
DefaultIndexer(int) - Constructor for class gov.sandia.cognition.collection.DefaultIndexer
Creates a new, empty DefaultIndexer with the given initial capacity.
DefaultIndexer(Collection<? extends ValueType>) - Constructor for class gov.sandia.cognition.collection.DefaultIndexer
Creates a new DefaultIndexer and adds he given collection of values to it.
DefaultInfiniteVector<KeyType> - Class in gov.sandia.cognition.math.matrix
An implementation of an InfiniteVector backed by a LinkedHashMap.
DefaultInfiniteVector() - Constructor for class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
Creates a new, empty instance of DefaultInfiniteVector.
DefaultInfiniteVector(int) - Constructor for class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
Creates a new, empty instance of DefaultInfiniteVector with the given initial capacity.
DefaultInfiniteVector(LinkedHashMap<KeyType, MutableDouble>) - Constructor for class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
Creates a new AbstractMapInfiniteVector with the given backing map.
DefaultInfiniteVector.SimpleIterator - Class in gov.sandia.cognition.math.matrix
Simple iterator for DefaultInfiniteVector
DefaultInputOutputPair<InputType,OutputType> - Class in gov.sandia.cognition.learning.data
A default implementation of the InputOutputPair interface.
DefaultInputOutputPair() - Constructor for class gov.sandia.cognition.learning.data.DefaultInputOutputPair
Creates a new DefaultInputOutputPair with both the input and output as null.
DefaultInputOutputPair(InputType, OutputType) - Constructor for class gov.sandia.cognition.learning.data.DefaultInputOutputPair
Creates a new DefaultInputOutputPair with the given input and output.
DefaultInputOutputPair(Pair<? extends InputType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.learning.data.DefaultInputOutputPair
Creates a new DefaultInputOutputPair using the first element of the given pair as the input and the second element of the given pair as the output.
DefaultKernelBinaryCategorizer<InputType> - Class in gov.sandia.cognition.learning.function.categorization
A default implementation of the KernelBinaryCategorizer that uses the standard way of representing the examples (supports) using a DefaultWeightedValue.
DefaultKernelBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.DefaultKernelBinaryCategorizer
Creates a new DefaultKernelBinaryCategorizer with a null kernel, no examples, and a zero bias.
DefaultKernelBinaryCategorizer(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.function.categorization.DefaultKernelBinaryCategorizer
Creates a new DefaultKernelBinaryCategorizer with the given kernel, no examples, and a zero bias.
DefaultKernelBinaryCategorizer(Kernel<? super InputType>, Collection<DefaultWeightedValue<InputType>>, double) - Constructor for class gov.sandia.cognition.learning.function.categorization.DefaultKernelBinaryCategorizer
Creates a new DefaultKernelBinaryCategorizer with the given parameters.
DefaultKernelContainer<InputType> - Class in gov.sandia.cognition.learning.function.kernel
The DefaultKernelContainer class implements an object that contains a kernel inside.
DefaultKernelContainer() - Constructor for class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer
Creates a new instance of KernelContainer.
DefaultKernelContainer(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer
Creates a new instance of KernelContainer with the given kernel.
DefaultKernelContainer(DefaultKernelContainer<? super InputType>) - Constructor for class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer
Creates a new copy of a KernelContainer and the kernel inside.
DefaultKernelsContainer<InputType> - Class in gov.sandia.cognition.learning.function.kernel
The DefaultKernelsContainer class implements a container of kernels.
DefaultKernelsContainer() - Constructor for class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer
Creates a new instance of DefaultKernelsContainer.
DefaultKernelsContainer(Collection<? extends Kernel<? super InputType>>) - Constructor for class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer
Creates a new instance of DefaultKernelsContainer.
DefaultKernelsContainer(DefaultKernelsContainer<InputType>) - Constructor for class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer
Creates a new copy of the DefaultKernelsConainer.
DefaultKeyValuePair<KeyType,ValueType> - Class in gov.sandia.cognition.util
A default implementation of the KeyValuePair interface.
DefaultKeyValuePair() - Constructor for class gov.sandia.cognition.util.DefaultKeyValuePair
Creates a new, empty DefaultKeyValuePair.
DefaultKeyValuePair(KeyType, ValueType) - Constructor for class gov.sandia.cognition.util.DefaultKeyValuePair
Creates a new DefaultKeyValuePair from the given key and value.
DefaultKeyValuePair(KeyValuePair<? extends KeyType, ? extends ValueType>) - Constructor for class gov.sandia.cognition.util.DefaultKeyValuePair
Creates a new DefaultKeyValuePair as a shallow copy of the given key-value pair.
DefaultMultiCollection<EntryType> - Class in gov.sandia.cognition.collection
The DefaultMultiCollection class implements a Collection that just contains a set of internal collections inside.
DefaultMultiCollection(Collection<EntryType>, Collection<EntryType>) - Constructor for class gov.sandia.cognition.collection.DefaultMultiCollection
Creates a new instance of DefaultMultiCollection.
DefaultMultiCollection(Collection<? extends Collection<EntryType>>) - Constructor for class gov.sandia.cognition.collection.DefaultMultiCollection
Creates a new instance of DefaultMultiCollection.
DefaultNamedValue<ValueType> - Class in gov.sandia.cognition.util
The DefaultNamedValue class implements a container of a name-value pair.
DefaultNamedValue() - Constructor for class gov.sandia.cognition.util.DefaultNamedValue
Creates a new instance of DefaultNamedValue.
DefaultNamedValue(String, ValueType) - Constructor for class gov.sandia.cognition.util.DefaultNamedValue
Creates a new instance of DefaultNamedValue from the given name and value.
DefaultNamedValue(DefaultNamedValue<? extends ValueType>) - Constructor for class gov.sandia.cognition.util.DefaultNamedValue
Creates a shallow copy of the given DefaultNamedValue.
DefaultPair<FirstType,SecondType> - Class in gov.sandia.cognition.util
The DefaultPair class implements a simple structure for a pair of two objects, potentially of different types.
DefaultPair() - Constructor for class gov.sandia.cognition.util.DefaultPair
Creates a new instance of DefaultPair with no members.
DefaultPair(FirstType, SecondType) - Constructor for class gov.sandia.cognition.util.DefaultPair
Creates a new instance of DefaultPair.
DefaultPair(Pair<? extends FirstType, ? extends SecondType>) - Constructor for class gov.sandia.cognition.util.DefaultPair
Copy constructor.
DefaultPartitionedDataset<DataType> - Class in gov.sandia.cognition.learning.data
The PartitionedDataset class provides a simple container for the training and testing datasets to be held together.
DefaultPartitionedDataset(Collection<DataType>, Collection<DataType>) - Constructor for class gov.sandia.cognition.learning.data.DefaultPartitionedDataset
Creates a new instance of PartitionedDataset.
DefaultPrecisionRecallPair - Class in gov.sandia.cognition.text.evaluation
A default implementation of the PrecisionRecallPair interface.
DefaultPrecisionRecallPair() - Constructor for class gov.sandia.cognition.text.evaluation.DefaultPrecisionRecallPair
Creates a new DefaultPrecisionRecallPair.
DefaultPrecisionRecallPair(double, double) - Constructor for class gov.sandia.cognition.text.evaluation.DefaultPrecisionRecallPair
Creates a new DefaultPrecisionRecallPair.
DefaultSemanticIdentifier - Class in gov.sandia.cognition.framework
The DefaultSemanticIdentifier class implements a default version of the SemanticIdentifier interface that stores the SemanticLabel the identifier is for and the unique identifier integer.
DefaultSemanticIdentifier(SemanticLabel, int) - Constructor for class gov.sandia.cognition.framework.DefaultSemanticIdentifier
Creates a new instance of SemanticIdentifier.
DefaultSemanticIdentifierMap - Class in gov.sandia.cognition.framework
The DefaultSemanticIdentifierMap is an implementation of SemanticIdentifierMap that is backed by a HashMap (a hashtable).
DefaultSemanticIdentifierMap() - Constructor for class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap
Creates a new instance of DefaultSemanticIdentifierMap.
DefaultSemanticLabel - Class in gov.sandia.cognition.framework
This class implements a semantic label using a string.
DefaultSemanticLabel(String) - Constructor for class gov.sandia.cognition.framework.DefaultSemanticLabel
Creates a new DefaultSemanticLabel.
DefaultSemanticNetwork - Class in gov.sandia.cognition.framework
This class contains a default implementation of a SemanticNetwork.
DefaultSemanticNetwork() - Constructor for class gov.sandia.cognition.framework.DefaultSemanticNetwork
Creates a new instance of DefaultSemanticNetwork
DefaultStopList - Class in gov.sandia.cognition.text.term.filter
A default, case-insensitive stop-list.
DefaultStopList() - Constructor for class gov.sandia.cognition.text.term.filter.DefaultStopList
Creates a new, empty DefaultStopList.
DefaultStopList(Iterable<String>) - Constructor for class gov.sandia.cognition.text.term.filter.DefaultStopList
Creates a new DefaultStopList with the given set of words.
DefaultTargetEstimatePair<TargetType,EstimateType> - Class in gov.sandia.cognition.learning.data
A default implementation of the TargetEstimatePair.
DefaultTargetEstimatePair() - Constructor for class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
Creates a new instance of TargetEstimatePair, with null target and estimate values.
DefaultTargetEstimatePair(TargetType, EstimateType) - Constructor for class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
Creates a new instance of TargetEstimatePair with the given target and estimate values.
DefaultTargetEstimatePair(Pair<? extends TargetType, ? extends EstimateType>) - Constructor for class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
Creates a shallow copy of another target-estimate pair.
DefaultTemporalValue<ValueType> - Class in gov.sandia.cognition.util
The DefaultTemporalValue class is a default implementation of the TemporalValue interface.
DefaultTemporalValue() - Constructor for class gov.sandia.cognition.util.DefaultTemporalValue
Creates a new, empty DefaultTemporalValue.
DefaultTemporalValue(Date, ValueType) - Constructor for class gov.sandia.cognition.util.DefaultTemporalValue
Creates a new DefaultTemporalValue.
DefaultTerm - Class in gov.sandia.cognition.text.term
A default implementation of the Term interface.
DefaultTerm() - Constructor for class gov.sandia.cognition.text.term.DefaultTerm
Creates a new DefaultTerm that contains the empty string.
DefaultTerm(String) - Constructor for class gov.sandia.cognition.text.term.DefaultTerm
Creates a new DefaultTerm with the given text.
DefaultTermCounts - Class in gov.sandia.cognition.text.term
A default implementation of the TermCounts interface.
DefaultTermCounts() - Constructor for class gov.sandia.cognition.text.term.DefaultTermCounts
Creates a new, empty DefaultTermCounts.
DefaultTermIndex - Class in gov.sandia.cognition.text.term
A default implementation of the TermIndex interface.
DefaultTermIndex() - Constructor for class gov.sandia.cognition.text.term.DefaultTermIndex
Creates a new, empty DefaultTermIndex.
DefaultTermNGram - Class in gov.sandia.cognition.text.term
A default implementation of the TermNGram interface.
DefaultTermNGram() - Constructor for class gov.sandia.cognition.text.term.DefaultTermNGram
Creates a new DefaultTermNGram.
DefaultTermNGram(Term...) - Constructor for class gov.sandia.cognition.text.term.DefaultTermNGram
Creates a new DefaultTermNGram.
DefaultTermOccurrence - Class in gov.sandia.cognition.text.term
A default implementation of the TermOccurrence interface.
DefaultTermOccurrence() - Constructor for class gov.sandia.cognition.text.term.DefaultTermOccurrence
Creates a new DefaultTermOccurrence with default values.
DefaultTermOccurrence(Term, int, int) - Constructor for class gov.sandia.cognition.text.term.DefaultTermOccurrence
Creates a new DefaultTermOccurrence.
DefaultTextField - Class in gov.sandia.cognition.text.document
A default implementation of the Field interface.
DefaultTextField() - Constructor for class gov.sandia.cognition.text.document.DefaultTextField
Creates a new DefaultTextField with default name and text, both of which are the empty string.
DefaultTextField(String, String) - Constructor for class gov.sandia.cognition.text.document.DefaultTextField
Creates a new DefaultTextField with the given name and text.
DefaultTextual - Class in gov.sandia.cognition.text
A default implementation of the Textual interface that just stores a string value.
DefaultTextual() - Constructor for class gov.sandia.cognition.text.DefaultTextual
Creates a new DefaultTextual containing the empty string.
DefaultTextual(String) - Constructor for class gov.sandia.cognition.text.DefaultTextual
Creates a new DefaultTextual containing the given text.
DefaultTextual(Textual) - Constructor for class gov.sandia.cognition.text.DefaultTextual
Creates a new DefaultTextual that takes the string text value from the given Textual object.
DefaultToken - Class in gov.sandia.cognition.text.token
A default implementation of the Token interface.
DefaultToken() - Constructor for class gov.sandia.cognition.text.token.DefaultToken
Creates a new Token.
DefaultToken(String, int) - Constructor for class gov.sandia.cognition.text.token.DefaultToken
Creates a new Token with the given text.
DefaultToken(String, int, int) - Constructor for class gov.sandia.cognition.text.token.DefaultToken
Creates a new Token with the given text, start, and length.
DefaultTriple<FirstType,SecondType,ThirdType> - Class in gov.sandia.cognition.util
The DefaultTriple class implements a simple structure for a triple of three objects, potentially of different types.
DefaultTriple() - Constructor for class gov.sandia.cognition.util.DefaultTriple
Creates a new instance of DefaultTriple with initial null values.
DefaultTriple(FirstType, SecondType, ThirdType) - Constructor for class gov.sandia.cognition.util.DefaultTriple
Creates a new instance of DefaultTriple.
DefaultTwoVectorEntry - Class in gov.sandia.cognition.math.matrix
Stores an entry for two vectors.
DefaultTwoVectorEntry(Vector, Vector) - Constructor for class gov.sandia.cognition.math.matrix.DefaultTwoVectorEntry
Creates a new instance of DefaultTwoVectorEntry.
DefaultTwoVectorEntry(Vector, Vector, int) - Constructor for class gov.sandia.cognition.math.matrix.DefaultTwoVectorEntry
Creates a new instance of DefaultTwoVectorEntry.
DefaultUpdater() - Constructor for class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater
Default constructor.
DefaultUpdater(BayesianParameter<ParameterType, ? extends ProbabilityFunction<ObservationType>, ? extends ProbabilityFunction<ParameterType>>) - Constructor for class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater
Creates a new instance of DefaultUpdater
DefaultUpdater() - Constructor for class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Default constructor.
DefaultUpdater(BayesianParameter<ParameterType, ? extends ProbabilityFunction<ObservationType>, ? extends ProbabilityFunction<ParameterType>>) - Constructor for class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Creates a new instance of DefaultUpdater
DefaultUpdater(BayesianParameter<ParameterType, ? extends ProbabilityFunction<ObservationType>, ? extends ProbabilityFunction<ParameterType>>, ProbabilityFunction<ParameterType>) - Constructor for class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Creates a new instance of DefaultUpdater
DefaultUpdater(BayesianParameter<ParameterType, ? extends ProbabilityFunction<ObservationType>, ? extends ProbabilityFunction<ParameterType>>, Double, ProbabilityFunction<ParameterType>) - Constructor for class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Creates a new instance of DefaultUpdater
DefaultValueDiscriminantPair<ValueType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> - Class in gov.sandia.cognition.learning.data
A default implementation of the ValueDiscriminantPair interface.
DefaultValueDiscriminantPair() - Constructor for class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair
Creates a new DefaultValueDiscriminantPair with null value and discriminant.
DefaultValueDiscriminantPair(ValueType, DiscriminantType) - Constructor for class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair
Creates a new DefaultValueDiscriminantPair with the given value and discriminant.
defaultVariance - Variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
The default variance, which the diagonal of the covariance matrix is initialized to.
defaultVariance - Variable in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
The default variance, which the diagonal of the covariance matrix is initialized to.
defaultVariance - Variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.IncrementalEstimator
Amount to add to the variance to keep it from being 0.0.
DefaultVectorFactoryContainer - Class in gov.sandia.cognition.math.matrix
A default implementation of the VectorFactoryContainer interface.
DefaultVectorFactoryContainer() - Constructor for class gov.sandia.cognition.math.matrix.DefaultVectorFactoryContainer
Creates a new DefaultVectorFactoryContainer.
DefaultVectorFactoryContainer(VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.math.matrix.DefaultVectorFactoryContainer
Creates a new DefaultVectorFactoryContainer with the given factory.
DefaultWeightedInputOutputPair<InputType,OutputType> - Class in gov.sandia.cognition.learning.data
A default implementation of the WeightedInputOutputPair interface.
DefaultWeightedInputOutputPair() - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
Creates a new DefaultWeightedInputOutputPair with null as the input and output and a default weight of 1.0.
DefaultWeightedInputOutputPair(InputType, OutputType, double) - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
Creates a new DefaultWeightedInputOutputPair with the given input, output, and weight.
DefaultWeightedInputOutputPair(Pair<? extends InputType, ? extends OutputType>, double) - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
Creates a new DefaultWeightedInputOutputPair with the given input and output from the given pair plus a weight.
DefaultWeightedInputOutputPair(WeightedInputOutputPair<? extends InputType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
Creates a new DefaultWeightedInputOutputPair that is a shallow copy of the given WeightedInputOuptutPair.
DefaultWeightedPair<FirstType,SecondType> - Class in gov.sandia.cognition.util
The DefaultWeightedPair class extends the DefaultPair class to add a weight to the pair.
DefaultWeightedPair() - Constructor for class gov.sandia.cognition.util.DefaultWeightedPair
Creates a new instance of DefaultWeightedPair.
DefaultWeightedPair(FirstType, SecondType, double) - Constructor for class gov.sandia.cognition.util.DefaultWeightedPair
Creates a new instance of DefaultWeightedPair.
DefaultWeightedTargetEstimatePair<TargetType,EstimateType> - Class in gov.sandia.cognition.learning.data
Extends TargetEstimatePair with an additional weight field.
DefaultWeightedTargetEstimatePair() - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
Creates a new WeightedTargetEstimatePair with nulls for the target and estimate and 1.0 for the weight.
DefaultWeightedTargetEstimatePair(TargetType, EstimateType, double) - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
Creates a new WeightedTargetEstimatePair with the given target, estimate, and weight.
DefaultWeightedTargetEstimatePair(DefaultWeightedTargetEstimatePair<? extends TargetType, ? extends EstimateType>) - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
Creates a new WeightedTargetEstimatePair as a shallow copy of the given other object.
DefaultWeightedValue<ValueType> - Class in gov.sandia.cognition.util
The WeightedValue class implements a simple generic container that holds a value and a weight assigned to the value.
DefaultWeightedValue() - Constructor for class gov.sandia.cognition.util.DefaultWeightedValue
Creates a new instance of WeightedValue.
DefaultWeightedValue(ValueType) - Constructor for class gov.sandia.cognition.util.DefaultWeightedValue
Creates a new instance of WeightedValue with the given value and a default weight of 1.0.
DefaultWeightedValue(ValueType, double) - Constructor for class gov.sandia.cognition.util.DefaultWeightedValue
Creates a new instance of WeightedValue.
DefaultWeightedValue(WeightedValue<? extends ValueType>) - Constructor for class gov.sandia.cognition.util.DefaultWeightedValue
Creates a new shallow copy of a WeightedValue.
DefaultWeightedValue.WeightComparator - Class in gov.sandia.cognition.util
A comparator for weighted values based on the weight.
DefaultWeightedValueDiscriminant<ValueType> - Class in gov.sandia.cognition.learning.data
An implementation of ValueDiscriminantPair that stores a double as the discriminant.
DefaultWeightedValueDiscriminant() - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant
Creates a DefaultWeightedValueDiscriminant with a null value and a weight of 0.0.
DefaultWeightedValueDiscriminant(ValueType, double) - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant
Creates a DefaultWeightedValueDiscriminant with the given value and weight.
DefaultWeightedValueDiscriminant(WeightedValue<? extends ValueType>) - Constructor for class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant
Creates a new DefaultWeightedValueDiscriminant whose weight and value are taken from the given weighted value.
degree(int) - Method in class gov.sandia.cognition.graph.GraphMetrics
Return the degree for the input nodeId.
degree(NodeNameType) - Method in class gov.sandia.cognition.graph.GraphMetrics
Return the degree for the input node.
degree - Variable in class gov.sandia.cognition.learning.function.kernel.PolynomialKernel
The degree of the polynomial.
degreeAssortativity() - Method in class gov.sandia.cognition.graph.GraphMetrics
Returns the whole-graph degree assortativity score.
degreesOfFreedom - Variable in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
Degrees of freedom, must be greater than the inverse scale dimensionality.
degreesOfFreedom - Variable in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
Degrees of freedom in the distribution, usually the number of datapoints - 1, DOFs must be greater than zero.
degreesOfFreedom - Variable in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Number of subjects in each treatment minus one.
degreesOfFreedom - Variable in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Degrees of freedom in the distribution, usually the number of datapoints - 1, DOFs must be greater than zero.
DelayFunction<DataType> - Class in gov.sandia.cognition.learning.data.feature
Delays the input and returns the input from the parameterized number of samples previous.
DelayFunction() - Constructor for class gov.sandia.cognition.learning.data.feature.DelayFunction
Default constructor.
DelayFunction(int) - Constructor for class gov.sandia.cognition.learning.data.feature.DelayFunction
Creates a new instance of DelayFunction
DelayFunction(DelayFunction<DataType>) - Constructor for class gov.sandia.cognition.learning.data.feature.DelayFunction
Copy Constructor
demoteToZero - Variable in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
An option to demote to zero.
DenseMatrix - Class in gov.sandia.cognition.math.matrix.custom
A dense matrix implementation.
DenseMatrix(int, int) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Creates a zero matrix of the specified dimensions
DenseMatrix(int, int, double) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Creates a matrix of default val in all cells of the specified dimensions
DenseMatrix(DenseMatrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Copy constructor that creates a deep copy of the input matrix.
DenseMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Copy constructor that copies any input Matrix -- creating a deep copy of the matrix.
DenseMatrix(double[][]) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Constructor for creating a dense matrix from a 2-d double array.
DenseMatrix(List<List<Double>>) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Constructor for creating a dense matrix from a 2-d double List.
DenseMatrix() - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseMatrix
This should never be called by anything or anyone other than Java's serialization code.
DenseMatrix - Class in gov.sandia.cognition.math.matrix.mtj
Matrix that represents all its entries using a fixed-size storage scheme, based on MTJ's DenseMatrix storage class.
DenseMatrix(int, int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Creates a new instance of DenseMatrix
DenseMatrix(DenseMatrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Creates a new instance of DenseMatrix
DenseMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Creates a new instance of DenseMatrix
DenseMatrix(DenseMatrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Creates a new instance of DenseMatrix
DenseMatrix(MatrixReader) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Creates a new instance of DenseMatrix
DenseMatrix.LU - Class in gov.sandia.cognition.math.matrix.custom
Simple container class for LU decompositions.
DenseMatrix.QR - Class in gov.sandia.cognition.math.matrix.custom
Container class that stores the Q and R matrices formed by the QR decomposition of this.
DenseMatrix.SVD - Class in gov.sandia.cognition.math.matrix.custom
Simple container class for Singular Value Decomposition (SVD) results.
DenseMatrixFactoryMTJ - Class in gov.sandia.cognition.math.matrix.mtj
MatrixFactory for creating MTJ's DenseMatrix-based Matrix
DenseMatrixFactoryMTJ() - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ
Creates a new instance of DenseMatrixFactoryMTJ
DenseMemoryGraph<NodeNameType> - Class in gov.sandia.cognition.graph
Most basic-est of graph types.
DenseMemoryGraph() - Constructor for class gov.sandia.cognition.graph.DenseMemoryGraph
Initializes an empty graph.
DenseMemoryGraph(int, int) - Constructor for class gov.sandia.cognition.graph.DenseMemoryGraph
Initializes an empty graph, but sets aside O(m + n) memory.
DenseVector - Class in gov.sandia.cognition.math.matrix.custom
Our dense vector implementation.
DenseVector() - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseVector
This should never be called by anything or anyone other than Java's serialization code.
DenseVector(int) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseVector
Creates a dense vector of length n.
DenseVector(int, double) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseVector
Initializes the vector to length n with all values initialized to defaultVal.
DenseVector(DenseVector) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseVector
Copy constructor copies the input dense vector into this
DenseVector(double[]) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseVector
Helper constructor that copies the data from the array into this
DenseVector(List<Double>) - Constructor for class gov.sandia.cognition.math.matrix.custom.DenseVector
Helper constructor that copies the data from the list into this
DenseVector - Class in gov.sandia.cognition.math.matrix.mtj
A generally useful vector representation that allocates a fixed-size underlying vector, based on MTJ's DenseVector
DenseVector(int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVector
Creates a new instance of DenseVector
DenseVector(DenseVector) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVector
Creates a new instance of DenseVector
DenseVector(Vector) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVector
Copy constructor for DenseVector
DenseVector(AbstractMTJVector) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVector
Copy constructor
DenseVector(double...) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVector
Creates a new instance of DenseVector
DenseVector(DenseVector) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVector
Creates a new instance of DenseVector
DenseVector(VectorReader) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVector
Creates a new instance of DenseVector
DenseVectorFactoryMTJ - Class in gov.sandia.cognition.math.matrix.mtj
VectorFactory for MTJ's DenseVector-based Vector
DenseVectorFactoryMTJ() - Constructor for class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
Creates a new instance of DenseVectorFactoryMTJ
depth - Variable in class gov.sandia.cognition.math.geometry.Quadtree.Node
The depth of this node in the tree.
deserialize(String) - Static method in class gov.sandia.cognition.graph.DenseMemoryGraph
Helper method for deserializing from a file
deserialize(String) - Static method in class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
Helper method for deserializing from a file
destinationVectorPrior - Variable in class gov.sandia.cognition.statistics.TransferEntropy.TransferEntropyDistributionObject
The prior for the destination vector.
DeterministicDistribution - Class in gov.sandia.cognition.statistics.distribution
A deterministic distribution that returns samples at a single point.
DeterministicDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
Creates a new instance of DeterministicDistribution
DeterministicDistribution(double) - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
Creates a new instance of DeterministicDistribution
DeterministicDistribution(DeterministicDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
Copy Constructor
DeterministicDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
CDF of the deterministic distribution.
DeterministicDistribution.PMF - Class in gov.sandia.cognition.statistics.distribution
PMF of the deterministic distribution.
deviance(ComputableDistribution<ObservationType>, Iterable<? extends ObservationType>) - Static method in class gov.sandia.cognition.statistics.bayesian.BayesianUtil
Computes the deviance of the model, which is -2log(p(observations|parameter)).
DiagonalConfidenceWeightedBinaryCategorizer - Class in gov.sandia.cognition.learning.function.categorization
A confidence-weighted linear predictor with a diagonal covariance, which is stored as a vector.
DiagonalConfidenceWeightedBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.DiagonalConfidenceWeightedBinaryCategorizer
Creates a new DiagonalConfidenceWeightedBinaryCategorizer.
DiagonalCovarianceLearner() - Constructor for class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.DiagonalCovarianceLearner
Creates a new MultivariateDecorrelator.DiagonalCovarianceLearner with the default value for default covariance.
DiagonalCovarianceLearner(double) - Constructor for class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.DiagonalCovarianceLearner
Creates a new MultivariateDecorrelator.DiagonalCovarianceLearner with the given value for default covariance.
DiagonalMatrix - Class in gov.sandia.cognition.math.matrix.custom
Diagonal matrices are a special case, but a rather common one with very quick and simple solutions to multiplications, inverses, etc.
DiagonalMatrix(int) - Constructor for class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
Creates a square (n x n) diagonal matrix initialized to zero.
DiagonalMatrix(DiagonalMatrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
Copy constructor.
DiagonalMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
Creates a diagonal matrix as a copy of the given matrix.
DiagonalMatrix() - Constructor for class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
This should never be called by anything or anyone other than Java's serialization code.
DiagonalMatrix - Interface in gov.sandia.cognition.math.matrix
Interface describing a diagonal matrix.
DiagonalMatrixFactoryMTJ - Class in gov.sandia.cognition.math.matrix.mtj
An MatrixFactory that produces DiagonalMatrixMTJ matrices.
DiagonalMatrixFactoryMTJ() - Constructor for class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
Creates a new instance of DiagonalMatrixFactoryMTJ
DiagonalMatrixMTJ - Class in gov.sandia.cognition.math.matrix.mtj
A diagonal matrix that wraps MTJ's BandMatrix class.
DiagonalMatrixMTJ(int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
Creates a new instance of DiagonalMatrixMTJ
DiagonalMatrixMTJ(DiagonalMatrixMTJ) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
Copy Constructor
DiagonalMatrixMTJ(double[]) - Constructor for class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
Creates a new instance of DiagonalMatrixMTJ
diagonalValues(double[]) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
Creates a diagonal matrix with the array of values on its diagonal
DictionaryFilter - Class in gov.sandia.cognition.text.term.filter
A term filter that only allows terms in its dictionary.
DictionaryFilter() - Constructor for class gov.sandia.cognition.text.term.filter.DictionaryFilter
Creates a new DictionaryFilter with an empty set of allowed terms.
DictionaryFilter(Set<Term>) - Constructor for class gov.sandia.cognition.text.term.filter.DictionaryFilter
Creates a new DictionaryFilter with a given set of allowed terms.
DifferentiableCostFunction - Interface in gov.sandia.cognition.learning.function.cost
The DifferentiableCostFunction is a cost function that can be differentiated.
DifferentiableEvaluator<InputType,OutputType,DerivativeType> - Interface in gov.sandia.cognition.math
Interface that indicates that the Evaluator can be differentiated about the given input.
DifferentiableFeedforwardNeuralNetwork - Class in gov.sandia.cognition.learning.function.vector
A feedforward neural network that can have an arbitrary number of layers, and an arbitrary differentiable squashing (activation) function assigned to each layer.
DifferentiableFeedforwardNeuralNetwork(ArrayList<Integer>, ArrayList<DifferentiableUnivariateScalarFunction>, Random) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork
Creates a new instance of DifferentiableFeedforwardNeuralNetwork
DifferentiableFeedforwardNeuralNetwork(int, int, int, DifferentiableVectorFunction, Random) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork
Creates a new instance of FeedforwardNeuralNetwork
DifferentiableFeedforwardNeuralNetwork(int, int, int, DifferentiableUnivariateScalarFunction, Random) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork
Creates a new instance of FeedforwardNeuralNetwork
DifferentiableFeedforwardNeuralNetwork(DifferentiableGeneralizedLinearModel...) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork
Creates a new instance of FeedforwardNeuralNetwork
DifferentiableGeneralizedLinearModel - Class in gov.sandia.cognition.learning.function.vector
A GradientDescenable version of a GeneralizedLinearModel, in other words, a GeneralizedLinearModel where the squashing function is differentiable
DifferentiableGeneralizedLinearModel() - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
Default Constructor.
DifferentiableGeneralizedLinearModel(int, int, DifferentiableUnivariateScalarFunction) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
Creates a new instance of GeneralizedLinearModel
DifferentiableGeneralizedLinearModel(MultivariateDiscriminant, DifferentiableVectorFunction) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
Creates a new instance of DifferentiableGeneralizedLinearModel
DifferentiableGeneralizedLinearModel(MultivariateDiscriminant, DifferentiableUnivariateScalarFunction) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
Creates a new instance of DifferentiableGeneralizedLinearModel
DifferentiableGeneralizedLinearModel(DifferentiableGeneralizedLinearModel) - Constructor for class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
Creates a new instance of DifferentiableGeneralizedLinearModel
DifferentiableUnivariateScalarFunction - Interface in gov.sandia.cognition.math
A differentiable univariate scalar function
DifferentiableVectorFunction - Interface in gov.sandia.cognition.math.matrix
A VectorFunction that can is also differentiable
differentiate(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToDifferentiableScalarFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased.InternalFunction
 
differentiate(Vector) - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree
 
differentiate(Vector) - Method in class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.AtanFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.CosineFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.HardSigmoidFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.HardTanHFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.IdentityScalarFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.LeakyRectifiedLinearFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.LinearFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Quadratic
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.RectifiedLinearFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.SigmoidFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.SoftPlusFunction
 
differentiate(double) - Method in class gov.sandia.cognition.learning.function.scalar.TanHFunction
 
differentiate(Vector) - Method in class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel
 
differentiate(Vector) - Method in class gov.sandia.cognition.learning.function.vector.ElementWiseDifferentiableVectorFunction
 
differentiate(Vector) - Method in class gov.sandia.cognition.learning.function.vector.LinearVectorFunction
 
differentiate(Vector) - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant
 
differentiate(InputType) - Method in interface gov.sandia.cognition.math.DifferentiableEvaluator
Differentiates the output with respect to the input
differentiate(double) - Method in interface gov.sandia.cognition.math.DifferentiableUnivariateScalarFunction
Differentiates the output of the function about the given input
differentiate(Double) - Method in interface gov.sandia.cognition.math.DifferentiableUnivariateScalarFunction
 
differentiate(Vector) - Method in interface gov.sandia.cognition.math.matrix.DifferentiableVectorFunction
Differentiate the VectorFunction at input and return the Jacobian
differentiate(double, Evaluator<? super Double, Double>) - Static method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian
Static access to the numerical differentiation procedure.
differentiate(double, Evaluator<? super Double, Double>, double) - Static method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian
Static access to the numerical differentiation procedure.
differentiate(Double) - Method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian
 
differentiate(Vector, Evaluator<? super Vector, Vector>) - Static method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.MatrixJacobian
Static access to the numerical differentiation procedure.
differentiate(Vectorizable, Evaluator<? super Vector, Vector>, double) - Static method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.MatrixJacobian
Static access to the numerical differentiation procedure.
differentiate(Vector) - Method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.MatrixJacobian
 
differentiate(Vectorizable, Evaluator<? super Vector, Double>) - Static method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.VectorJacobian
Static access to the numerical differentiation procedure.
differentiate(Vectorizable, Evaluator<? super Vector, Double>, double) - Static method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.VectorJacobian
Static access to the numerical differentiation procedure.
differentiate(Vector) - Method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator.VectorJacobian
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF
 
differentiate(Double) - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution.CDF
 
differentiate(Vector) - Method in class gov.sandia.cognition.statistics.method.DistributionParameterEstimator.DistributionWrapper
 
dimensionality - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The dimensionality of the input to the factorization machine.
dimensionality - Variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The dimensionality of the dataset.
DimensionalityMismatchException - Exception in gov.sandia.cognition.math.matrix
Gets thrown when the dimensions don't agree for a matrix/vector operation
DimensionalityMismatchException() - Constructor for exception gov.sandia.cognition.math.matrix.DimensionalityMismatchException
Creates a new instance of DimensionalityMismatchException without detail message.
DimensionalityMismatchException(String) - Constructor for exception gov.sandia.cognition.math.matrix.DimensionalityMismatchException
Constructs an instance of DimensionalityMismatchException with the specified detail message.
DimensionalityMismatchException(int, int) - Constructor for exception gov.sandia.cognition.math.matrix.DimensionalityMismatchException
Constructs and instance of DimensionalityMismatchException with the two mismatching dimensions.
DimensionFilterableLearner - Interface in gov.sandia.cognition.learning.algorithm
Interface for a learner that can be filtered by which dimensions it includes in learning.
dimensionsToConsider - Variable in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
The array of dimensions for the learner to consider.
dimensionsToConsider - Variable in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
The dimensions to sample from in the learner.
dimensionsToConsider - Variable in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdVarianceLearner
The array of 0-based dimensions to consider in the input.
DirectedNodeEdgeGraph<NodeNameType> - Interface in gov.sandia.cognition.graph
This interface defines the minimal set of methods necessary to create and walk a directed graph.
DirectedWeightedNodeEdgeGraph<NodeNameType> - Interface in gov.sandia.cognition.graph
Adds the necessary methods for a graph with weighted edges.
DirectionalVectorToDifferentiableScalarFunction - Class in gov.sandia.cognition.learning.algorithm.minimization.line
Creates a truly differentiable scalar function from a differentiable Vector function, instead of using a forward-differences approximation to the derivative like DirectionalVectorToScalarFunction does.
DirectionalVectorToDifferentiableScalarFunction(DifferentiableEvaluator<? super Vector, ? extends Double, Vector>, Vector, Vector) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToDifferentiableScalarFunction
Creates a new instance of DirectionalVectorToDifferentiableScalarFunction
DirectionalVectorToScalarFunction - Class in gov.sandia.cognition.learning.algorithm.minimization.line
Maps a vector function onto a scalar one by using a directional vector and vector offset, and the parameter to the function is a scalar value along the direction from the start-point offset.
DirectionalVectorToScalarFunction(Evaluator<? super Vector, ? extends Double>, Vector, Vector) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
Creates a new function that restricts the vectorFunction to a particular vector direction
DirectionalVectorToScalarFunction(DirectionalVectorToScalarFunction) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
Copy constructor
DirectSampler<DataType> - Class in gov.sandia.cognition.statistics.montecarlo
Sampler that generates samples directly from a target distribution.
DirectSampler() - Constructor for class gov.sandia.cognition.statistics.montecarlo.DirectSampler
Creates a new instance of DirectSampler
DirichletDistribution - Class in gov.sandia.cognition.statistics.distribution
The Dirichlet distribution is the multivariate generalization of the beta distribution.
DirichletDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.DirichletDistribution
Creates a new instance of DirichletDistribution
DirichletDistribution(int) - Constructor for class gov.sandia.cognition.statistics.distribution.DirichletDistribution
Creates a new instance of DirichletDistribution
DirichletDistribution(Vector) - Constructor for class gov.sandia.cognition.statistics.distribution.DirichletDistribution
Creates a new instance of DirichletDistribution
DirichletDistribution(DirichletDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.DirichletDistribution
Copy Constructor.
DirichletDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution
PDF of the Dirichlet distribution.
DirichletProcessClustering - Class in gov.sandia.cognition.learning.algorithm.clustering
Clustering algorithm that wraps Dirichlet Process Mixture Model.
DirichletProcessClustering() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering
Creates a new instance of DirichletProcessClustering
DirichletProcessClustering(int) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering
Creates a new instance of DirichletProcessClustering
DirichletProcessClustering(DirichletProcessMixtureModel<Vector>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering
Creates a new instance of DirichletProcessClustering
DirichletProcessMixtureModel<ObservationType> - Class in gov.sandia.cognition.statistics.bayesian
An implementation of Dirichlet Process clustering, which estimates the number of clusters and the centroids of the clusters from a set of data.
DirichletProcessMixtureModel() - Constructor for class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Creates a new instance of DirichletProcessMixtureModel
DirichletProcessMixtureModel.DPMMCluster<ObservationType> - Class in gov.sandia.cognition.statistics.bayesian
Cluster for a step in the DPMM
DirichletProcessMixtureModel.DPMMLogConditional - Class in gov.sandia.cognition.statistics.bayesian
Container for the log conditional likelihood
DirichletProcessMixtureModel.MultivariateMeanCovarianceUpdater - Class in gov.sandia.cognition.statistics.bayesian
Updater that creates specified clusters with distinct means and covariances
DirichletProcessMixtureModel.MultivariateMeanUpdater - Class in gov.sandia.cognition.statistics.bayesian
Updater that creates specified clusters with identical covariances
DirichletProcessMixtureModel.Sample<ObservationType> - Class in gov.sandia.cognition.statistics.bayesian
A sample from the Dirichlet Process Mixture Model.
DirichletProcessMixtureModel.Updater<ObservationType> - Interface in gov.sandia.cognition.statistics.bayesian
Updater for the DPMM
DiscreteDistribution<DataType> - Interface in gov.sandia.cognition.statistics
A Distribution with a countable domain (input) set.
discreteFourierTransform(ArrayList<Double>) - Static method in class gov.sandia.cognition.math.signals.FourierTransform
Computes the brute-force discrete Fourier transform of the input data.
discreteFourierTransformComplex(ArrayList<ComplexNumber>) - Static method in class gov.sandia.cognition.math.signals.FourierTransform
Computes the brute-force discrete Fourier transform of the input data.
DiscreteNaiveBayesCategorizer<InputType,CategoryType> - Class in gov.sandia.cognition.learning.algorithm.bayes
Implementation of a Naive Bayes Classifier for Discrete Data.
DiscreteNaiveBayesCategorizer() - Constructor for class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Creates a new instance of DiscreteNaiveBayesCategorizer
DiscreteNaiveBayesCategorizer(int) - Constructor for class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Creates a new instance of DiscreteNaiveBayesCategorizer.
DiscreteNaiveBayesCategorizer(int, DefaultDataDistribution<CategoryType>, Map<CategoryType, List<DefaultDataDistribution<InputType>>>) - Constructor for class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Creates a new instance of DiscreteNaiveBayesCategorizer.
DiscreteNaiveBayesCategorizer.Learner<InputType,CategoryType> - Class in gov.sandia.cognition.learning.algorithm.bayes
Learner for a DiscreteNaiveBayesCategorizer.
DiscreteSamplingUtil - Class in gov.sandia.cognition.statistics
A utility class for sampling.
DiscreteSamplingUtil() - Constructor for class gov.sandia.cognition.statistics.DiscreteSamplingUtil
 
DiscreteTimeFilter<StateType extends CloneableSerializable> - Interface in gov.sandia.cognition.math.signals
A discrete-time filter.
discriminant - Variable in class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair
The discriminant.
DiscriminantBinaryCategorizer<InputType> - Interface in gov.sandia.cognition.learning.function.categorization
Interface for a linear discriminant categorizer in the binary categorization domain.
DiscriminantCategorizer<InputType,CategoryType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> - Interface in gov.sandia.cognition.learning.function.categorization
Interface for a Categorizer that can produce a value to discriminate between how well different instances fit a given category.
DistanceSamplingClusterInitializer<ClusterType extends Cluster<DataType>,DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.initializer
Implements FixedClusterInitializer that initializes clusters by first selecting a random point for the first cluster and then randomly sampling each successive cluster based on the squared minimum distance from the point to the existing selected clusters.
DistanceSamplingClusterInitializer() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.initializer.DistanceSamplingClusterInitializer
Creates a new, empty instance of MinDistanceSamplingClusterInitializer.
DistanceSamplingClusterInitializer(DivergenceFunction<? super DataType, ? super DataType>, ClusterCreator<ClusterType, DataType>, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.initializer.DistanceSamplingClusterInitializer
Creates a new instance of MinDistanceSamplingClusterInitializer.
Distribution<DataType> - Interface in gov.sandia.cognition.statistics
Describes a very high-level distribution of data.
distribution - Variable in class gov.sandia.cognition.statistics.method.DistributionParameterEstimator.DistributionWrapper
Distribution to estimate the parameters of
DistributionEstimationTask(ClosedFormComputableDistribution<DataType>, Collection<? extends DataType>) - Constructor for class gov.sandia.cognition.statistics.method.MaximumLikelihoodDistributionEstimator.DistributionEstimationTask
Creates a new instance of DistributionEstimationTask
distributionEstimator - Variable in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.Learner
The distributionLearner for the distribution of each dimension of each category.
DistributionEstimator<ObservationType,DistributionType extends Distribution<? extends ObservationType>> - Interface in gov.sandia.cognition.statistics
A BatchLearner that estimates a Distribution.
DistributionEstimatorTask(Collection<? extends ObservationType>, BatchLearner<Collection<? extends WeightedValue<? extends ObservationType>>, ? extends ComputableDistribution<ObservationType>>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask
Creates an instance of DistributionEstimatorTask
distributionEstimatorTasks - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm
Tasks for re-estimating the PDFs.
distributionFunction - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ObservationLikelihoodTask
The PDF.
distributionLearner - Variable in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.OnlineLearner
The incremental learner for the distribution used to represent each dimension.
distributionLearner - Variable in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
Learner for the Distribution Functions of the HMM.
distributionLearner - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask
My copy of the PDF estimator.
DistributionParameter<ParameterType,ConditionalType extends Distribution<?>> - Interface in gov.sandia.cognition.statistics
Allows access to a parameter within a closed-form distribution, given by the high-level String value.
DistributionParameterEstimator<DataType,DistributionType extends ClosedFormDistribution<? extends DataType>> - Class in gov.sandia.cognition.statistics.method
A method of estimating the parameters of a distribution using an arbitrary CostFunction and FunctionMinimizer algorithm.
DistributionParameterEstimator(DistributionType, CostFunction<? super DistributionType, Collection<? extends DataType>>) - Constructor for class gov.sandia.cognition.statistics.method.DistributionParameterEstimator
Creates a new instance of DistributionParameterEstimator
DistributionParameterEstimator(DistributionType, CostFunction<? super DistributionType, Collection<? extends DataType>>, FunctionMinimizer<Vector, Double, ? super DistributionParameterEstimator<DataType, DistributionType>.DistributionWrapper>) - Constructor for class gov.sandia.cognition.statistics.method.DistributionParameterEstimator
Creates a new instance of DistributionParameterEstimator
DistributionParameterEstimator.DistributionWrapper - Class in gov.sandia.cognition.statistics.method
Maps the parameters of a Distribution and a CostFunction into a Vector/Double Evaluator.
DistributionParameterUtil - Class in gov.sandia.cognition.statistics
Functions to assist in creating DistributionParameters.
DistributionParameterUtil() - Constructor for class gov.sandia.cognition.statistics.DistributionParameterUtil
 
distributions - Variable in class gov.sandia.cognition.statistics.distribution.LinearMixtureModel
Underlying distributions from which we sample
DistributionWeightedEstimator<ObservationType,DistributionType extends Distribution<? extends ObservationType>> - Interface in gov.sandia.cognition.statistics
A BatchLearner that estimates a Distribution from a Collection of weighted data.
DistributionWithMean<DataType> - Interface in gov.sandia.cognition.statistics
A Distribution that has a well-defined mean, or first central moment.
DistributionWrapper(DistributionType, CostFunction<? super DistributionType, ? super Collection<? extends DataType>>) - Constructor for class gov.sandia.cognition.statistics.method.DistributionParameterEstimator.DistributionWrapper
Creates a new instance of DistributionWrapper
divergence - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The divergence function to use.
divergenceFunction - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The divergence function used to find the distance between two clusters.
divergenceFunction - Variable in class gov.sandia.cognition.learning.algorithm.clustering.divergence.WithinClusterDivergenceWrapper
The divergence function.
divergenceFunction - Variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
The divergence function between cluster being used.
divergenceFunction - Variable in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
An optional DivergenceFunction that is used to create a WithinClusterDivergence function via a WithinClusterDivergenceWrapper.
divergenceFunction - Variable in class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer
The internal divergence function for the object to use.
divergenceFunction - Variable in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
The divergence function to apply between the data and the input.
divergenceFunction - Variable in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator.Learner
The divergence function to apply between the data and the input.
DivergenceFunction<FirstType,SecondType> - Interface in gov.sandia.cognition.math
The DivergenceFunction class defines the functionality of something that computes the divergence between two objects.
DivergenceFunctionContainer<FirstType,SecondType> - Interface in gov.sandia.cognition.learning.function.distance
Interface for a class that holds a divergence function.
DivergencesEvaluator<InputType,ValueType> - Class in gov.sandia.cognition.learning.function.distance
Evaluates the divergence (distance) between an input and a list of values, storing the resulting divergence values in a vector.
DivergencesEvaluator() - Constructor for class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
Creates a new DivergencesEvaluator with a null divergence function and an empty set of values.
DivergencesEvaluator(DivergenceFunction<? super ValueType, ? super InputType>, Collection<ValueType>) - Constructor for class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
Creates a new DivergencesEvaluator with the given divergence and values.
DivergencesEvaluator(DivergenceFunction<? super ValueType, ? super InputType>, Collection<ValueType>, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
Creates a new DivergencesEvaluator with the given divergence and values.
DivergencesEvaluator.Learner<DataType,InputType,ValueType> - Class in gov.sandia.cognition.learning.function.distance
A learner adapter for the DivergencesEvaluator.
divide(RingType) - Method in class gov.sandia.cognition.math.AbstractEuclideanRing
 
divide(ComplexNumber) - Method in class gov.sandia.cognition.math.ComplexNumber
Arithmetic division of this by other using polar coordinates: magnitude = this.magnitude / other.magnitude phase = this.phase - other.phase answer.realPart = magnitude * cos( phase ) answer.imaginaryPart = magnitude * sin( phase )
divide(RingType) - Method in interface gov.sandia.cognition.math.EuclideanRing
Divides this value by the other value, returning the result of the division as a new value.
divide(double, double) - Static method in class gov.sandia.cognition.math.LogMath
Divides two log-domain values.
divide(LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
Divides this value by another value and returns the result.
divide(MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
divide(MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
divide(MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
divide(UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
Divides this value by another value and returns the result.
divide(Duration) - Method in class gov.sandia.cognition.time.DefaultDuration
 
divide(double) - Method in class gov.sandia.cognition.time.DefaultDuration
 
divide(Duration) - Method in interface gov.sandia.cognition.time.Duration
Divides this duration by the given duration and returns the ratio.
divide(double) - Method in interface gov.sandia.cognition.time.Duration
Divides this duration by the given scalar value and returns the result.
divideByNorm1(Vector) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
Returns a new vector whose elements are the elements of the original vector, divided by the 1-norm of the vector (the sum of the absolute values of the elements).
divideByNorm1Equals(Vector) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
Divides all of the given elements of the vector by the 1-norm (the sum of the absolute values of the elements).
divideByNorm2(Vector) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
Returns a new vector whose elements are the elements of the original vector, divided by the 2-norm of the vector (the square root of the sum of the squared values of the elements).
divideByNorm2Equals(Vector) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
Divides all of the given elements of the vector by the 2-norm (the square root of the sum of the squared values of the elements).
dividedBy(ComplexNumber) - Method in class gov.sandia.cognition.math.ComplexNumber
Deprecated.
Use divide.
dividedByEquals(ComplexNumber) - Method in class gov.sandia.cognition.math.ComplexNumber
Deprecated.
Use divideEquals.
divideEquals(ComplexNumber) - Method in class gov.sandia.cognition.math.ComplexNumber
Inline arithmetic division of this by other: this.magnitude /= other.magnitude this.phase -= other.phase
divideEquals(RingType) - Method in interface gov.sandia.cognition.math.EuclideanRing
Inline divises this value by the other value, storing the result inside this.
divideEquals(LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
Divides this value by another value and stores the result in this value.
divideEquals(MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
divideEquals(MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
divideEquals(MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
divideEquals(UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
Divides this value by another value and stores the result in this value.
Document - Interface in gov.sandia.cognition.text.document
Defines the interface for a document.
Documentation - Annotation Type in gov.sandia.cognition.annotation
The Documentation annotation marks that something is just documentation.
documentCount - Variable in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
The number of documents the weight is computed over.
documentCount - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The number of documents in the dataset.
documentCount - Variable in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
The number of documents.
DocumentExtractionException - Exception in gov.sandia.cognition.text.document.extractor
An exception that occurs during document extraction.
DocumentExtractionException() - Constructor for exception gov.sandia.cognition.text.document.extractor.DocumentExtractionException
Creates a new instance of DocumentExtractionException without detail message.
DocumentExtractionException(String) - Constructor for exception gov.sandia.cognition.text.document.extractor.DocumentExtractionException
Constructs an instance of DocumentExtractionException with the specified detail message.
DocumentExtractionException(Throwable) - Constructor for exception gov.sandia.cognition.text.document.extractor.DocumentExtractionException
Constructs an instance of DocumentExtractionException with the specified cause.
DocumentExtractionException(String, Throwable) - Constructor for exception gov.sandia.cognition.text.document.extractor.DocumentExtractionException
Constructs an instance of DocumentExtractionException with the specified detail message and cause.
DocumentExtractor - Interface in gov.sandia.cognition.text.document.extractor
Interface for extracting documents from files.
DocumentFieldConcatenator - Class in gov.sandia.cognition.text.convert
A document-text converter that concatenates multiple text fields from a document together for further processing.
DocumentFieldConcatenator() - Constructor for class gov.sandia.cognition.text.convert.DocumentFieldConcatenator
Creates a new DocumentFieldConcatenator with an empty list of fields and a newline separator.
DocumentFieldConcatenator(List<String>, String) - Constructor for class gov.sandia.cognition.text.convert.DocumentFieldConcatenator
Creates a new DocumentFieldConcatenator with the given field names and field separator.
DocumentReference - Interface in gov.sandia.cognition.text.document
Interface for a reference to a document.
DocumentSampleTask(Vector, int, int) - Constructor for class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler.DocumentSampleTask
Creates a new instance of DocumentSampleTask
documentsByTerms - Variable in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
The document-by-term matrix.
DocumentSingleFieldConverter - Class in gov.sandia.cognition.text.convert
Extracts a single field from a document.
DocumentSingleFieldConverter() - Constructor for class gov.sandia.cognition.text.convert.DocumentSingleFieldConverter
Creates a new DocumentSingleFieldConverter with the body field as the field to extract.
DocumentSingleFieldConverter(String) - Constructor for class gov.sandia.cognition.text.convert.DocumentSingleFieldConverter
Creates a new DocumentSingleFieldConverter with the given field to extract.
documentTermCounts - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
For each unique term (unique per document), the number of times that term occurs in the document.
documentTermPairsCounts - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
the number of unique terms in each document.
documentTerms - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
For each unique term (unique per document) which term id it maps to.
documentTopicCount - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
For each document, the number of terms assigned to each topic.
documentTopicProbabilities - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler.Result
The document-topic probabilities, which are often called the theta model parameters.
documentTopicSum - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The number of term occurrences in each document.
documentWeights - Variable in class gov.sandia.cognition.text.algorithm.ValenceSpreader.Result
The weights assigned to all of the input documents.
Domain(int, int) - Constructor for class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.Domain
Creates a new instance of Domain
dominance - Variable in class gov.sandia.cognition.text.term.vector.weighter.global.DominanceGlobalTermWeighter
A vector caching the global dominance weight of the document collection.
DominanceGlobalTermWeighter - Class in gov.sandia.cognition.text.term.vector.weighter.global
Implements the dominance term gloal weighting scheme.
DominanceGlobalTermWeighter() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.DominanceGlobalTermWeighter
Creates a new DominanceGlobalTermWeighter.
DominanceGlobalTermWeighter(VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.DominanceGlobalTermWeighter
Creates a new DominanceGlobalTermWeighter.
dot(VectorType) - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
 
dot(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
dot(VectorType) - Method in interface gov.sandia.cognition.math.matrix.VectorSpace
The inner product of this vector with the given vector.
dotDivide(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
dotDivide(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
dotDivide(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Element-wise division of this by other.
dotDivide(Vector) - Method in interface gov.sandia.cognition.math.matrix.Vector
Element-wise division of this by other.
dotDivideEquals(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
dotDivideEquals(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
dotDivideEquals(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Inline element-wise division of this by other.
dotDivideEquals(Vector) - Method in interface gov.sandia.cognition.math.matrix.Vector
Inline element-wise division of this by other.
dotProduct(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
dotProduct(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
dotProduct(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
dotProduct(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
dotProduct(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
dotProduct(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
dotProduct(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
 
dotProduct(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
Inner Vector product between two Vectors
dotProduct(VectorType) - Method in interface gov.sandia.cognition.math.matrix.VectorSpace
The inner product of this vector with the given vector.
dotTimes(RingType) - Method in class gov.sandia.cognition.math.AbstractRing
 
dotTimes(LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
 
dotTimes(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
dotTimes(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
dotTimes(Matrix) - Method in interface gov.sandia.cognition.math.matrix.DiagonalMatrix
 
dotTimes(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
dotTimes(MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
dotTimes(MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
dotTimes(MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
dotTimes(RingType) - Method in interface gov.sandia.cognition.math.Ring
Element-wise multiplication of this and other
dotTimes(UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
dotTimesEquals(ComplexNumber) - Method in class gov.sandia.cognition.math.ComplexNumber
 
dotTimesEquals(LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
 
dotTimesEquals(Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
dotTimesEquals(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
dotTimesEquals(SparseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Type-specific version of dotTimesEquals for combining whatever type this is with the input sparse matrix.
dotTimesEquals(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
dotTimesEquals(DiagonalMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Type-specific version of dotTimesEquals for combining whatever type this is with the input diagonal matrix.
dotTimesEquals(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
dotTimesEquals(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
dotTimesEquals(SparseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
dotTimesEquals(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
dotTimesEquals(DiagonalMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
dotTimesEquals(SparseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Type-specific version of dotTimesEquals for combining whatever type this is with the input sparse matrix.
dotTimesEquals(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Type-specific version of dotTimesEquals for combining whatever type this is with the input dense matrix.
dotTimesEquals(DiagonalMatrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Type-specific version of dotTimesEquals for combining whatever type this is with the input diagonal matrix.
dotTimesEquals(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
dotTimesEquals(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
dotTimesEquals(InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
dotTimesEquals(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
dotTimesEquals(AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
Inline element-wise multiplication of the elements in this and matrix, modifies the elements of this
dotTimesEquals(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
 
dotTimesEquals(AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
dotTimesEquals(MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
dotTimesEquals(MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
dotTimesEquals(MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
dotTimesEquals(RingType) - Method in interface gov.sandia.cognition.math.Ring
Inline element-wise multiplication of this and other
dotTimesEquals(UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
dotTimesEquals(RandomVariable<Number>) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
DoubleArrayList - Class in gov.sandia.cognition.collection
A memory-dense, base-type double vector that permits adding new elements, altering elements, etc.
DoubleArrayList() - Constructor for class gov.sandia.cognition.collection.DoubleArrayList
Initializes an empty vector with a default allocation.
DoubleArrayList(int) - Constructor for class gov.sandia.cognition.collection.DoubleArrayList
Initializes an empty vector (allocating startSize locations for additions).
DoubleArrayList(DoubleArrayList) - Constructor for class gov.sandia.cognition.collection.DoubleArrayList
Copy constructor
DoubleJacobian() - Constructor for class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian
Default constructor
DoubleJacobian(Evaluator<? super Double, Double>) - Constructor for class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian
Creates a new instance of VectorJacobian
DoubleJacobian(Evaluator<? super Double, Double>, double) - Constructor for class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian
Create a new instance of VectorJacobian
DoubleReuseRandom - Class in gov.sandia.cognition.util
An extension of java.util.Random that builds a list of random doubles and then serves up the random values from the array, returning to the beginning when the end is reached.
DoubleReuseRandom(int) - Constructor for class gov.sandia.cognition.util.DoubleReuseRandom
Creates DoubleReuseRandom with the given parameters
DoubleReuseRandom(int, long) - Constructor for class gov.sandia.cognition.util.DoubleReuseRandom
Creates DoubleReuseRandom with the given parameters
doubleValue() - Method in class gov.sandia.cognition.math.LogNumber
 
doubleValue() - Method in class gov.sandia.cognition.math.MutableDouble
 
doubleValue() - Method in class gov.sandia.cognition.math.MutableInteger
 
doubleValue() - Method in class gov.sandia.cognition.math.MutableLong
 
doubleValue() - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
DPMMAssignments(ArrayList<Integer>, DirichletProcessMixtureModel.DPMMLogConditional) - Constructor for class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.DPMMAssignments
Constructor
DPMMCluster(Collection<? extends ObservationType>, ProbabilityFunction<? super ObservationType>) - Constructor for class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMCluster
Creates a new instance of DPMMCluster
DPMMLogConditional() - Constructor for class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMLogConditional
Default constructor
Duration - Interface in gov.sandia.cognition.time
Represents a duration of time.
DynamicArrayMap<ValueType> - Class in gov.sandia.cognition.collection
A DynamicArrayList is a class that implements a map from an integer to an Object type on top of an expanding array.
DynamicArrayMap() - Constructor for class gov.sandia.cognition.collection.DynamicArrayMap
Creates a new instance of DynamicArrayMap.
DynamicArrayMap(int) - Constructor for class gov.sandia.cognition.collection.DynamicArrayMap
Creates a new instance of DynamicArrayMap with the given initial capacity.
DynamicArrayMap(DynamicArrayMap<? extends ValueType>) - Constructor for class gov.sandia.cognition.collection.DynamicArrayMap
Creates a new instance of DynamicArrayMap using the given mapping to copy into this map.
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