- Identified<IdentifierType> - Interface in gov.sandia.cognition.util
-
Defines functionality for an object that has some type of identifier.
- IdentifiedValue<IdentifierType,ValueType> - Interface in gov.sandia.cognition.util
-
Interface for a pairing of an identifier and its associated value.
- identifier - Variable in class gov.sandia.cognition.util.DefaultIdentifiedValue
-
The identifier for the value.
- identity() - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
-
- identity() - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
-
- identity() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
Formats the matrix as an identity matrix.
- identity() - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Formats the matrix as an identity matrix.
- identity() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
-
- IdentityDataConverter<DataType> - Class in gov.sandia.cognition.data.convert
-
A pass-through converter that just returns the given value.
- IdentityDataConverter() - Constructor for class gov.sandia.cognition.data.convert.IdentityDataConverter
-
Creates a new IdentityDataConverter.
- IdentityDistanceMetric - Class in gov.sandia.cognition.learning.function.distance
-
A distance metric that is 0 if two objects are equal and 1 if they are not.
- IdentityDistanceMetric() - Constructor for class gov.sandia.cognition.learning.function.distance.IdentityDistanceMetric
-
Creates a new IdentityDistanceMetric.
- IdentityEvaluator<DataType> - Class in gov.sandia.cognition.evaluator
-
An identity function that returns its input as its output.
- IdentityEvaluator() - Constructor for class gov.sandia.cognition.evaluator.IdentityEvaluator
-
Creates a new IdentityEvaluator, which has no parameters.
- IdentityLearner<ValueType> - Class in gov.sandia.cognition.learning.algorithm.baseline
-
A batch learner implementation that just returns its inputs, creating an
identity function.
- IdentityLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.baseline.IdentityLearner
-
Creates a new IdentityLearner, which has no parameters.
- IdentityScalarFunction - Class in gov.sandia.cognition.learning.function.scalar
-
A univariate scalar identity function: f(x) = x.
- IdentityScalarFunction() - Constructor for class gov.sandia.cognition.learning.function.scalar.IdentityScalarFunction
-
Creates a new LinearFunction.
- ImportanceSampler<DataType> - Class in gov.sandia.cognition.statistics.montecarlo
-
Importance sampling is a technique for estimating properties of
a target distribution, while only having samples generated from an
"importance" distribution rather than the target distribution.
- ImportanceSampler() - Constructor for class gov.sandia.cognition.statistics.montecarlo.ImportanceSampler
-
Creates a new instance of ImportanceSampler
- ImportanceSampler(ProbabilityDensityFunction<DataType>) - Constructor for class gov.sandia.cognition.statistics.montecarlo.ImportanceSampler
-
Creates a new instance of ImportanceSampler.
- ImportanceSampling<ObservationType,ParameterType> - Class in gov.sandia.cognition.statistics.bayesian
-
Importance sampling is a Monte Carlo inference technique where we sample
from an easy distribution over the hidden variables (parameters) and then
weight the result by the ratio of the likelihood of the parameters given
the evidence and the likelihood of generating the parameters.
- ImportanceSampling() - Constructor for class gov.sandia.cognition.statistics.bayesian.ImportanceSampling
-
Creates a new instance of ImportanceSampling
- ImportanceSampling - Class in gov.sandia.cognition.statistics.method
-
Importance sampling is a technique for estimating properties of
a target distribution, while only having samples generated from an
"importance" distribution rather than the target distribution.
- ImportanceSampling() - Constructor for class gov.sandia.cognition.statistics.method.ImportanceSampling
-
- ImportanceSampling.DefaultUpdater<ObservationType,ParameterType> - Class in gov.sandia.cognition.statistics.bayesian
-
Default ImportanceSampling Updater that uses a BayesianParameter
to compute the quantities of interest.
- ImportanceSampling.Updater<ObservationType,ParameterType> - Interface in gov.sandia.cognition.statistics.bayesian
-
Updater for ImportanceSampling
- incomingValue - Variable in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
-
The incoming value for the node.
- incompleteBetaContinuedFraction(double, double, double) - Static method in class gov.sandia.cognition.math.MathUtil
-
Evaluates the continued fraction of the incomplete beta function.
- incompleteGammaContinuedFraction(double, double) - Static method in class gov.sandia.cognition.math.MathUtil
-
Returns the incomplete Gamma function using the continued
fraction expansion evaluation using Lentz's method
- incompleteGammaSeriesExpansion(double, double) - Static method in class gov.sandia.cognition.math.MathUtil
-
Computes the series expansion approximation to the incomplete
gamma function.
- increment(KeyType, double) - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap
-
- increment(KeyType) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
-
- increment(KeyType, double) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
-
- increment(KeyType) - Method in interface gov.sandia.cognition.collection.ScalarMap
-
Increments the value associated with the given key by 1.0.
- increment(KeyType, double) - Method in interface gov.sandia.cognition.collection.ScalarMap
-
Increments the value associated with the given key by the given amount.
- increment(int, int) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
-
- increment(int, int, double) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
-
- increment(int) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
-
- increment(int, double) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
-
- increment(int, int) - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Increments the value at the given position by 1.
- increment(int, int, double) - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Increments the value at the given position by the given value.
- increment(int, int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
-
- increment(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
-
- increment(int) - Method in interface gov.sandia.cognition.math.matrix.Vector
-
Increments the value of the given index by 1.
- increment(int, double) - Method in interface gov.sandia.cognition.math.matrix.Vector
-
Increments the value of the given index by the given value.
- increment(ValueType, double) - Method in class gov.sandia.cognition.statistics.distribution.DataCountTreeSetBinnedMapHistogram
-
- increment(KeyType, double) - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
-
- IncrementalClusterCreator<ClusterType extends Cluster<DataType>,DataType> - Interface in gov.sandia.cognition.learning.algorithm.clustering.cluster
-
An interface for a ClusterCreator that can incrementally add and
remove members from a cluster.
- IncrementalEstimator(int) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator
-
Creates a new instance of IncrementalEstimator
- IncrementalEstimator(double, MultivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator
-
Creates a new instance of IncrementalEstimator
- IncrementalEstimator(int) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator
-
Creates a new instance of IncrementalEstimator
- IncrementalEstimator(InverseGammaDistribution, MultivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator
-
Creates a new instance of IncrementalEstimator
- IncrementalEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator
-
Default constructor
- IncrementalEstimator(double) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator
-
Creates a new instance of IncrementalEstimator
- IncrementalEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.IncrementalEstimator
-
Creates a new IncrementalEstimator.
- IncrementalEstimator(double) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.IncrementalEstimator
-
Creates a new IncrementalEstimator with the given default
variance.
- IncrementalEstimator<DataType,DistributionType extends Distribution<? extends DataType>,SufficientStatisticsType extends SufficientStatistic<? super DataType,? extends DistributionType>> - Interface in gov.sandia.cognition.statistics
-
An estimator of a Distribution that uses SufficientStatistic to arrive
at its result.
- IncrementalEstimatorCovarianceInverse() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimatorCovarianceInverse
-
Default constructor
- IncrementalEstimatorCovarianceInverse(double) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimatorCovarianceInverse
-
Creates a new instance of IncrementalEstimatorCovarianceInverse
- incrementAll(Iterable<? extends KeyType>) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
-
- incrementAll(ScalarMap<? extends KeyType>) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
-
- incrementAll(Iterable<? extends KeyType>) - Method in interface gov.sandia.cognition.collection.ScalarMap
-
Increments the values associated all of the given keys by 1.0.
- incrementAll(ScalarMap<? extends KeyType>) - Method in interface gov.sandia.cognition.collection.ScalarMap
-
Increments all the keys in this map by the values in the other one.
- IncrementalLearner<DataType,ResultType> - Interface in gov.sandia.cognition.learning.algorithm
-
The IncrementalLearner interface defines the general functionality
of an object that is the implementation of a data-driven, incremental machine
learning algorithm.
- index - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask
-
Index into the gammas to pull the weights.
- index - Variable in class gov.sandia.cognition.learning.function.categorization.VectorElementThresholdCategorizer
-
The index to apply the threshold to.
- index - Variable in class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction
-
The index of the vector to get.
- index - Variable in class gov.sandia.cognition.math.Combinations.AbstractCombinationsIterator
-
Index into the universal set.
- index - Variable in class gov.sandia.cognition.text.term.DefaultIndexedTerm
-
The index of the term.
- IndexedTerm - Interface in gov.sandia.cognition.text.term
-
Interface for a term plus its index.
- IndexedTermSimilarityRelation - Class in gov.sandia.cognition.text.term.relation
-
A relationship between two indexed terms describing their term similarity.
- IndexedTermSimilarityRelation(IndexedTerm, IndexedTerm, double) - Constructor for class gov.sandia.cognition.text.term.relation.IndexedTermSimilarityRelation
-
Creates a new IndexedTermSimilarityRelation.
- Indexer<ValueType> - Interface in gov.sandia.cognition.collection
-
Defines the functionality of a collection that can map between values and
integer indices.
- IndexIterator(int, int) - Constructor for class gov.sandia.cognition.math.Combinations.IndexIterator
-
Creates a new instance of IndexIterator
- InfiniteVector<KeyType> - Interface in gov.sandia.cognition.math.matrix
-
A Vector that has a potentially infinite number of indices (keys), but will
only contain a countable number in any instance.
- InfiniteVector.Entry<KeyType> - Interface in gov.sandia.cognition.math.matrix
-
Entry for a InfiniteVector
- InfiniteVector.KeyValueConsumer<KeyType> - Interface in gov.sandia.cognition.math.matrix
-
Defines the functionality for a consumer of vector entries, which are an
index and a value.
- init(EnergyFunction<LabelType>) - Method in interface gov.sandia.cognition.graph.inference.EnergyFunctionSolver
-
Initializes internal state and stores the energy function for future
solutions.
- init(EnergyFunction<LabelType>) - Method in class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
-
- init() - Method in class gov.sandia.cognition.learning.algorithm.semisupervised.valence.MultipartiteValenceMatrix
-
This method must be called before an instance is passed to an iterative
solver and after all relationships and trusted/weighted elements are
added.
- initalBounds - Variable in class gov.sandia.cognition.math.geometry.Quadtree
-
The initial bounds for the tree.
- initialAlpha - Variable in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
-
Initial value of alpha, the concentration parameter of the
Dirichlet Process
- initialDomainCapacity - Variable in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.DefaultFactory
-
The initial domain capacity.
- initialGuess - Variable in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
-
Initial guess for the iterations.
- initialGuess - Variable in class gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer
-
Initial guess of the minimization routine
- initialize(LinearBinaryCategorizer, Vector, boolean) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
-
Initializes the linear binary categorizer.
- initialize(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
-
Initializes the kernel binary categorizer.
- initialize(LinearBinaryCategorizer, Vector, boolean) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
-
- initialize(DefaultKernelBinaryCategorizer<InputType>, InputType, boolean) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
-
- initialize(AdaptiveRejectionSampling.LogEvaluator<?>, double, double, double, double, double) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
-
Initializes the Adaptive Rejection Sampling method
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
-
Called to initialize the learning algorithm's state based on the
data that is stored in the data field.
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineStochasticGradient
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
-
Called to initialize the learning algorithm's state based on the
data that is stored in the data field.
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderNewtonsMethod
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderSecantMethod
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
-
- initializeAlgorithm(double) - Method in class gov.sandia.cognition.math.LentzMethod
-
Initializes Lentz's method using the given values
- initializeAlgorithm() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
-
- initializeAlgorithm() - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
-
- initializeClusters(int, Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
-
Initializes a given number of clusters from the given elements using the
greedy initialization algorithm.
- initializeClusters(int, Collection<? extends DataType>) - Method in interface gov.sandia.cognition.learning.algorithm.clustering.initializer.FixedClusterInitializer
-
Initializes a given number of clusters from the given elements.
- initializeClusters(int, Collection<? extends Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.NeighborhoodGaussianClusterInitializer
-
- initializeClusters(int, Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.RandomClusterInitializer
-
- initializeCognitiveState(CognitiveModelLiteState) - Method in class gov.sandia.cognition.framework.lite.AbstractCognitiveModelLite
-
This method takes a cognitive state and initializes it by initializing
all the module states on it.
- initializeDegreeAssortativity() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initialize the degree assortativity for the whole graph.
- initializeEdgeTriangles() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the datastructure for all triangles that all nodes and edges
participate in.
- initializeNewtonsMethod(SmoothCumulativeDistributionFunction, double, double) - Static method in class gov.sandia.cognition.statistics.method.InverseTransformSampling
-
Initializes Newton's method for inverse transform sampling.
- initializeNodeDegrees() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the unweighted degree values for all nodes in the graph.
- initializeNodeNeighbors() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the neighbors (undirected) for all nodes in the graph at
once.
- initializeNodeSuccessors() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the node successors (directed version of neighbors).
- initializeNodeTriangles() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the datastructure for all triangles that all nodes and edges
participate in.
- initializePerEdgeJaccardSimilarity() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the Jaccard similarity for each edge in the graph.
- initializePerEdgeTriangleDensity() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the per-edge triangle density.
- initializePerNodeBetweennessCentrality() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the per-node eccentricity.
- initializePerNodeEccentricity() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Initializes the per-node eccentricity.
- initializer - Variable in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
-
The initializer for the algorithm.
- initializeSimplex(InputOutputPair<Vector, Double>, double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead
-
Initializes the simplex about the initial point
- initializeSolver(MatrixVectorMultiplier) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver
-
- initializeSolver(MatrixVectorMultiplierWithPreconditioner) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver
-
- initializeSolver(Operator) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Called before iterations begin in learn.
- initializeSolver(OverconstrainedMatrixVectorMultiplier) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer
-
- initializeSolver(MatrixVectorMultiplier) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver
-
- initializeState(CognitiveModelState) - Method in interface gov.sandia.cognition.framework.CognitiveModule
-
This method initializes the state object for a CognitiveModel by adding
any necessary information to the model state and returining the default
state for the module.
- initializeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule
-
This method initializes the state object for a CognitiveModel by adding
any necessary information to the model state and returining the default
state for the module.
- initializeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.learning.StatefulEvaluatorBasedCognitiveModule
-
This method initializes the state object for a CognitiveModel by adding
any necessary information to the model state and returining the default
state for the module.
- initializeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.lite.AbstractSemanticMemoryLite
-
This method initializes the state object for the CognitiveModule by
calling the initialState function on the underlying pattern recognizer.
- initializeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModule
-
This method initializes the state object for a CognitiveModel by adding
any necessary information to the model state and returining the default
state for the module.
- initializeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModule
-
This method initializes the state object for a CognitiveModel by adding
any necessary information to the model state and returining the default
state for the module.
- initializeVectors(int) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractEntropyBasedGlobalTermWeighter
-
- initializeVectors(int) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
-
Initializes internal vectors to the given dimensionality.
- initializeWeights(int, int, int) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
-
Initializes the neural net parameters for the given dimensions, not
including the bias terms, using the object's random-number generator
uniformly between the initialization range (and its negative value).
- initialPartition(Map<NodeNameType, Integer>) - Method in class gov.sandia.cognition.graph.community.Louvain
-
The input partition will serve as the initial partition for the graph
(replacing Louvain's default "each node to its own community"
partitioning).
- initialProbability - Variable in class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain
-
Initial probability Vector over the states.
- initialState() - Method in interface gov.sandia.cognition.framework.lite.PatternRecognizerLite
-
Creates a new initial state for the recognizer.
- initialState() - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
-
Creates a new initial state for the recognizer.
- InOrderKDTreeIterator(KDTree<VectorType, DataType, PairType>) - Constructor for class gov.sandia.cognition.math.geometry.KDTree.InOrderKDTreeIterator
-
Creates a new instance of InOrderKDTreeIterator
- input - Variable in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule
-
A place to temporarily store the input read in by a call to readState;
this temporary store is blown away as soon as it used by evaluate,
because we NEVER retain state interally across module update cycles
- inputDimensionality - Variable in class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator
-
The expected dimensionality of the input.
- inputLearner - Variable in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
-
The unsupervised learning algorithm for creating the input
transformation.
- InputOutputPair<InputType,OutputType> - Interface in gov.sandia.cognition.learning.data
-
The InputOutputPair interface is just a container for an input and its
associated output used in supervised learning.
- InputOutputSlopeTriplet - Class in gov.sandia.cognition.learning.algorithm.minimization.line
-
Stores an InputOutputPair with corresponding slope (gradient) information
- InputOutputSlopeTriplet() - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.InputOutputSlopeTriplet
-
Creates a new instance of InputOutputSlopeTriplet
- InputOutputSlopeTriplet(Double, Double, Double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.InputOutputSlopeTriplet
-
Creates a new instance of InputOutputSlopeTriplet
- InputOutputSlopeTriplet(InputOutputSlopeTriplet) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.InputOutputSlopeTriplet
-
Copy constructor
- InputOutputTransformedBatchLearner<InputType,TransformedInputType,TransformedOutputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm
-
An adapter class for performing supervised learning from data where both
the input and output have to be transformed before they are passed to the
learning algorithm.
- InputOutputTransformedBatchLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
-
Creates a new, empty InputOutputTransformedBatchLearner.
- InputOutputTransformedBatchLearner(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends TransformedInputType>>, BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType, TransformedOutputType>>, ? extends Evaluator<? super TransformedInputType, ? extends TransformedOutputType>>, BatchLearner<? super Collection<? extends OutputType>, ? extends ReversibleEvaluator<OutputType, TransformedOutputType, ?>>) - Constructor for class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
-
Creates a new InputOutputTransformedBatchLearner with the given
learners.
- inputsList(Iterable<? extends InputOutputPair<? extends InputType, ?>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
-
Creates a list containing all of the input values from the given data.
- inputsTransposed - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
-
A list representing a transposed form of the matrix of inputs.
- inputToHiddenBiasWeights - Variable in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
-
Bias weights to add to each of the hidden units.
- inputToHiddenWeights - Variable in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
-
Matrix of weights to pre-multiply the inputs by.
- inspectAPI(Class<?>) - Static method in class gov.sandia.cognition.util.ObjectUtil
-
Creates a String representing the Constructors and Methods from the
given Class, inspects public constructors and all
public/private/protected methods (except those from the Object class).
- inspectFields(Class<?>) - Static method in class gov.sandia.cognition.util.ObjectUtil
-
Returns a String representing the values of all public/private/protected
fields in the given Class, e.g., "protected double myField"
- inspectFieldValues(Object) - Static method in class gov.sandia.cognition.util.ObjectUtil
-
Returns a String representing the values of all public/private/protected
fields in the given instantiated Object, e.g., "double myField = 3.14"
- inspector(Object) - Static method in class gov.sandia.cognition.util.ObjectUtil
-
Prints out the Methods and Fields associated with the argument.
- INSTANCE - Static variable in class gov.sandia.cognition.collection.NumberComparator
-
Instance of the NumberComparator.
- INSTANCE - Static variable in class gov.sandia.cognition.framework.DefaultCogxelFactory
-
An instance of the factory since it has no internal state.
- INSTANCE - Static variable in class gov.sandia.cognition.framework.lite.BooleanActivatableCogxelFactory
-
An instance of the factory since it has no internal state.
- INSTANCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanCentroidClusterCreator
-
An instance of this class since it has no internal data.
- INSTANCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanMiniBatchCentroidClusterCreator
-
An instance of this class.
- INSTANCE - Static variable in class gov.sandia.cognition.learning.algorithm.clustering.divergence.GaussianClusterDivergenceFunction
-
An instance of the class since it has no internal data.
- INSTANCE - Static variable in class gov.sandia.cognition.learning.function.distance.CosineDistanceMetric
-
An instance of CosineDistanceMetric to use since this class has
no internal data.
- INSTANCE - Static variable in class gov.sandia.cognition.learning.function.distance.EuclideanDistanceMetric
-
An instance of EuclideanDistanceMetric to use since the class has no
internal data.
- INSTANCE - Static variable in class gov.sandia.cognition.learning.function.distance.EuclideanDistanceSquaredMetric
-
An instance of EuclideanDistanceSquaredMetric to use since the class
has no internal data.
- INSTANCE - Static variable in class gov.sandia.cognition.learning.function.distance.ManhattanDistanceMetric
-
An instance of the ManhattanDistanceMetric to use since this
class has no internal data.
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.custom.CustomDenseMatrixFactory
-
An instance of this class.
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory
-
An instance of this class.
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.custom.CustomDiagonalMatrixFactory
-
An instance of this class.
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.custom.CustomSparseMatrixFactory
-
An instance of this class.
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory
-
An instance of this class.
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ
-
Default instance of this
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ
-
Default instance of this
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ
-
Default instance of the class
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.mtj.MatrixEntryIndexComparatorMTJ
-
An instance of this class since it has no internal fields.
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ
-
Default instance of this
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
-
Default instance of this
- INSTANCE - Static variable in class gov.sandia.cognition.math.matrix.VectorEntryIndexComparator
-
A single instance of this class to use because it has no internal memory.
- INSTANCE - Static variable in class gov.sandia.cognition.math.NumberAverager
-
Instance of NumberAverager, since it has no state.
- INSTANCE - Static variable in class gov.sandia.cognition.math.WeightedNumberAverager
-
Instance of WeightedNumberAverager, since it has no state.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.ErrorFunction
-
Default instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.ErrorFunction.Inverse
-
Default instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay
-
Default instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.BernoulliConfidence
-
This class has no members, so here's a static instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.ChebyshevInequality
-
This class has no members, so here's a static instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.ChiSquareConfidence
-
Default instance variable since the class has no members.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.FriedmanConfidence
-
Default instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.GaussianConfidence
-
This class has no members, so here's a static instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence
-
Default instance of the K-S test.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.MarkovInequality
-
This class has no members, so here's a static instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.NemenyiConfidence
-
Default instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.StudentTConfidence
-
This class has no members, so here's a static instance.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence
-
Default instance since the class has no state.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.montecarlo.MultivariateMonteCarloIntegrator
-
Default instance because this class has no state.
- INSTANCE - Static variable in class gov.sandia.cognition.statistics.montecarlo.UnivariateMonteCarloIntegrator
-
Default instance because this class has no state.
- IntArrayList - Class in gov.sandia.cognition.collection
-
A memory-dense, base-type int vector that permits adding new elements,
altering elements, etc.
- IntArrayList() - Constructor for class gov.sandia.cognition.collection.IntArrayList
-
Initializes an empty vector with a default allocation.
- IntArrayList(int) - Constructor for class gov.sandia.cognition.collection.IntArrayList
-
Initializes an empty vector (allocating startSize locations for
additions).
- IntArrayList(IntArrayList) - Constructor for class gov.sandia.cognition.collection.IntArrayList
-
Copy constructor
- IntegerDistribution - Interface in gov.sandia.cognition.statistics
-
Defines a distribution over natural numbers.
- IntegerSpan - Class in gov.sandia.cognition.collection
-
An Iterable that starts at a given Integer and goes until another, inclusive.
- IntegerSpan(int, int) - Constructor for class gov.sandia.cognition.collection.IntegerSpan
-
Creates a new instance of IntegerSpan
- integrate(Collection<? extends SampleType>, Evaluator<? super SampleType, ? extends OutputType>) - Method in interface gov.sandia.cognition.statistics.montecarlo.MonteCarloIntegrator
-
Integrates the given function given samples from another function.
- integrate(List<? extends WeightedValue<? extends SampleType>>, Evaluator<? super SampleType, ? extends OutputType>) - Method in interface gov.sandia.cognition.statistics.montecarlo.MonteCarloIntegrator
-
Integrates the given function given weighted samples from another
function.
- integrate(Collection<? extends SampleType>, Evaluator<? super SampleType, ? extends Vector>) - Method in class gov.sandia.cognition.statistics.montecarlo.MultivariateMonteCarloIntegrator
-
- integrate(List<? extends WeightedValue<? extends SampleType>>, Evaluator<? super SampleType, ? extends Vector>) - Method in class gov.sandia.cognition.statistics.montecarlo.MultivariateMonteCarloIntegrator
-
- integrate(Collection<? extends SampleType>, Evaluator<? super SampleType, ? extends Double>) - Method in class gov.sandia.cognition.statistics.montecarlo.UnivariateMonteCarloIntegrator
-
- integrate(List<? extends WeightedValue<? extends SampleType>>, Evaluator<? super SampleType, ? extends Double>) - Method in class gov.sandia.cognition.statistics.montecarlo.UnivariateMonteCarloIntegrator
-
- integrateExp() - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LineSegment
-
Integrates the exponent of the line segment
- intercept(PolynomialFunction.Linear, PolynomialFunction.Linear) - Static method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.Point
-
Computes the x-axis value where the two lines intersect
- InternalFunction() - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased.InternalFunction
-
- InternalIterator() - Constructor for class gov.sandia.cognition.collection.FiniteCapacityBuffer.InternalIterator
-
Default constructor
- interpolate(Quaternion, double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
-
Interpolates between this quaternion and the given quaternion.
- interpolateEquals(Quaternion, double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
-
Interpolates between this quaternion and the given quaternion and sets
it in this quaternion.
- interpolateLinear(Vectorizable, Vectorizable, double) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
-
Performs linear interpolation between two vectors.
- interpolateLinear(Vector, Vector, double) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
-
Performs linear interpolation between two vectors.
- intValue() - Method in class gov.sandia.cognition.math.LogNumber
-
- intValue() - Method in class gov.sandia.cognition.math.MutableDouble
-
- intValue() - Method in class gov.sandia.cognition.math.MutableInteger
-
- intValue() - Method in class gov.sandia.cognition.math.MutableLong
-
- intValue() - Method in class gov.sandia.cognition.math.UnsignedLogNumber
-
- inverse() - Method in class gov.sandia.cognition.math.AbstractField
-
- inverse() - Method in interface gov.sandia.cognition.math.Field
-
Returns the inverse of this.
- inverse(double) - Static method in class gov.sandia.cognition.math.LogMath
-
Takes the inverse of a log-domain value.
- inverse() - Method in class gov.sandia.cognition.math.LogNumber
-
- inverse() - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
-
- inverse() - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
-
Computes the full-blown inverse of this, which must be a
square matrix
- inverse() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
Computes the full-blown inverse of this, which must be a
square matrix
- inverse() - Method in interface gov.sandia.cognition.math.matrix.DiagonalMatrix
-
- inverse() - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Computes the full-blown inverse of this, which must be a
square matrix
- inverse() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
-
- inverse() - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
-
- inverse() - Method in interface gov.sandia.cognition.math.matrix.Quaternion
-
Returns the inverse of this quaternion.
- inverse() - Method in class gov.sandia.cognition.math.MutableDouble
-
- inverse(Collection<ComplexNumber>) - Static method in class gov.sandia.cognition.math.signals.FourierTransform
-
Static function that inverts a Fourier transform.
- Inverse() - Constructor for class gov.sandia.cognition.math.signals.FourierTransform.Inverse
-
Default constructor
- inverse() - Method in class gov.sandia.cognition.math.UnsignedLogNumber
-
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.CDF
-
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.CDF
-
Computes the inverse of the CDF for the give probability.
- inverse(LaplaceDistribution, double) - Static method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.CDF
-
Computes the inverse of the CDF for the give probability.
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution.CDF
-
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution.CDF
-
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.CDF
-
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution.CDF
-
Evaluates the Inverse Student-t CDF for the given probability
and degrees of freedom
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF
-
- inverse(double) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF
-
- Inverse() - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF.Inverse
-
Creates a new instance of UnivariateGaussian
with zero mean and unit variance
- Inverse(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF.Inverse
-
Creates a new instance of UnivariateGaussian
- Inverse(UnivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF.Inverse
-
Copy constructor
- Inverse() - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.ErrorFunction.Inverse
-
Default constructor
- inverse(double) - Method in interface gov.sandia.cognition.statistics.InvertibleCumulativeDistributionFunction
-
Computes the inverse of the CDF for the given probability.
- inverse(CumulativeDistributionFunction<NumberType>, double) - Static method in class gov.sandia.cognition.statistics.method.InverseTransformSampling
-
Inverts the given CDF, finding the value of "x" so that CDF(x)=p using
a root-finding algorithm.
- inverse(CumulativeDistributionFunction<DataType>, double) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
-
Inverts the discrete CDF, that is p=Pr{x<=X}.
- inverseDocumentFrequency - Variable in class gov.sandia.cognition.text.term.vector.weighter.global.InverseDocumentFrequencyGlobalTermWeighter
-
The (cached) value of the inverse document frequency.
- InverseDocumentFrequencyGlobalTermWeighter - Class in gov.sandia.cognition.text.term.vector.weighter.global
-
Implements the inverse-document-frequency (IDF) term global weighting scheme.
- InverseDocumentFrequencyGlobalTermWeighter() - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.InverseDocumentFrequencyGlobalTermWeighter
-
Creates a new InverseDocumentFrequencyGlobalTermWeighter.
- InverseDocumentFrequencyGlobalTermWeighter(VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.text.term.vector.weighter.global.InverseDocumentFrequencyGlobalTermWeighter
-
Creates a new InverseDocumentFrequencyGlobalTermWeighter.
- inverseEquals() - Method in class gov.sandia.cognition.math.ComplexNumber
-
- inverseEquals() - Method in interface gov.sandia.cognition.math.Field
-
Changes this value to be its inverse.
- inverseEquals() - Method in class gov.sandia.cognition.math.LogNumber
-
- inverseEquals() - Method in interface gov.sandia.cognition.math.matrix.Quaternion
-
Changes this quaternion to be its inverse.
- inverseEquals() - Method in class gov.sandia.cognition.math.MutableDouble
-
- inverseEquals() - Method in class gov.sandia.cognition.math.UnsignedLogNumber
-
- inverseGamma - Variable in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
-
Inverse-Gamma component
- InverseGammaDistribution - Class in gov.sandia.cognition.statistics.distribution
-
Defines an inverse-gamma distribution.
- InverseGammaDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
-
Creates a new instance of InverseGammaDistribution
- InverseGammaDistribution(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
-
Creates a new instance of InverseGammaDistribution
- InverseGammaDistribution(InverseGammaDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
-
Copy constructor
- InverseGammaDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
-
CDF of the inverseRootFinder-gamma distribution.
- InverseGammaDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution
-
PDF of the inverseRootFinder-Gamma distribution.
- inverseNewtonsMethod(SmoothUnivariateDistribution, double, double) - Static method in class gov.sandia.cognition.statistics.method.InverseTransformSampling
-
Inverts the given CDF, finding the value of "x" so that CDF(x)=p using
a root-finding algorithm.
- inverseRootFinder(RootFinder, CumulativeDistributionFunction<Double>, double) - Static method in class gov.sandia.cognition.statistics.method.InverseTransformSampling
-
Inverts the given CDF, finding the value of "x" so that CDF(x)=p using
a root-finding algorithm.
- inverseScale - Variable in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
-
Inverse scale matrix, must be symmetric and positive definite.
- InverseTransformSampling - Class in gov.sandia.cognition.statistics.method
-
Inverse transform sampling is a method by which one can sample from an
arbitrary distribution using only a uniform random-number generator and
the ability to empirically invert the CDF.
- InverseTransformSampling() - Constructor for class gov.sandia.cognition.statistics.method.InverseTransformSampling
-
- inverseWishart - Variable in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
-
Generates the covariance for the Gaussian.
- InverseWishartDistribution - Class in gov.sandia.cognition.statistics.distribution
-
The Inverse-Wishart distribution is the multivariate generalization of the
inverse-gamma distribution.
- InverseWishartDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
-
Creates a new instance of InverseWishartDistribution
- InverseWishartDistribution(int) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
-
Creates a new instance of InverseWishartDistribution
- InverseWishartDistribution(Matrix, int) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
-
Creates a new instance of InverseWishartDistribution
- InverseWishartDistribution(InverseWishartDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
-
Copy constructor.
- InverseWishartDistribution.MultivariateGammaFunction - Class in gov.sandia.cognition.statistics.distribution
-
Multivariate generalization of the Gamma function.
- InverseWishartDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution
-
PDF of the Inverse-Wishart distribution, though I have absolutely no
idea why anybody would evaluate the PDF of an Inverse-Wishart...
- InvertibleCumulativeDistributionFunction<NumberType extends java.lang.Number> - Interface in gov.sandia.cognition.statistics
-
A cumulative distribution function that is empirically invertible.
- isActivated() - Method in interface gov.sandia.cognition.framework.Activatable
-
Returns whether or not the object is isActivated.
- isActivated() - Method in class gov.sandia.cognition.framework.lite.BooleanActivatableCogxel
-
Returns whether or not the object is isActivated.
- isBiasEnabled() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
-
Gets whether or not the bias term is enabled.
- isCenterData() - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
-
Gets whether or not the data needs to be centered in the kernel space
before applying the function.
- isCenterData() - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
-
Gets whether or not the data needs to be centered in the kernel space
before applying the algorithm.
- isCompressed() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
This method tests if the matrix is currently compressed to the compressed
Yale format.
- isCompressed() - 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.
- isDemoteToZero() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
-
Gets whether or not the algorithm will demote features involved in an
incorrect categorization to zero (Winnow1).
- isEmpty() - Method in class gov.sandia.cognition.collection.AbstractScalarMap
-
- isEmpty(boolean[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
-
Determines if the given array is null or empty (length 0).
- isEmpty(int[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
-
Determines if the given array is null or empty (length 0).
- isEmpty(long[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
-
Determines if the given array is null or empty (length 0).
- isEmpty(double[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
-
Determines if the given array is null or empty (length 0).
- isEmpty(Object[]) - Static method in class gov.sandia.cognition.collection.ArrayUtil
-
Determines if the given array is null or empty (length 0).
- isEmpty(Collection<?>) - Static method in class gov.sandia.cognition.collection.CollectionUtil
-
Returns true if the given collection is null or empty.
- isEmpty(Iterable<?>) - Static method in class gov.sandia.cognition.collection.CollectionUtil
-
Returns true if the given iterable is null or empty.
- isEmpty() - Method in class gov.sandia.cognition.collection.DefaultIndexer
-
- isEmpty() - Method in class gov.sandia.cognition.collection.DynamicArrayMap
-
Runs in O(1).
- isEmpty() - Method in interface gov.sandia.cognition.collection.Indexer
-
Returns true if this indexer is empty, which means it has no values.
- isEmpty() - Method in interface gov.sandia.cognition.collection.NumericMap
-
Returns true if the map is empty.
- isEmpty() - Method in class gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix
-
- isEmpty() - Method in interface gov.sandia.cognition.learning.performance.categorization.ConfusionMatrix
-
Gets whether or not the matrix is empty.
- isEmpty() - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
-
Returns true if this is a leaf node and has no items in it.
- isEmpty(String) - Static method in class gov.sandia.cognition.util.StringUtil
-
Returns true if the given String is null or empty.
- isFactorsEnabled() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
-
Gets whether or not the factors are enabled.
- isFull() - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
-
Returns true if the finite-capacity buffer is full.
- isFull() - Method in class gov.sandia.cognition.math.geometry.KDTree.Neighborhood
-
Returns true if the Neighborhood is full.
- isInBounds(DataType) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
-
Returns true if the given point is within the bounds of this node.
- isInitialized() - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
-
Returns true if the state has been initialized.
- isInitialized() - Method in class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer
-
- isInitialized() - Method in interface gov.sandia.cognition.learning.function.categorization.ConfidenceWeightedBinaryCategorizer
-
Determines if this category has been initialized with a mean and
covariance.
- isInitialized() - Method in class gov.sandia.cognition.learning.function.categorization.DiagonalConfidenceWeightedBinaryCategorizer
-
- isInputLabel(SemanticLabel) - Method in interface gov.sandia.cognition.framework.lite.PatternRecognizerLite
-
Takes a SemanticLabel and returns true if it is a label used to
provide input to the PatternRecognizerLite.
- isInputLabel(SemanticLabel) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
-
Takes a SemanticLabel and returns true if it is a label used to
provide input to the PatternRecognizerLite.
- isLabel(SemanticLabel) - Method in interface gov.sandia.cognition.framework.lite.PatternRecognizerLite
-
Takes a SemanticLabel and returns true if the PatternRecognizer
uses it.
- isLabel(SemanticLabel) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
-
Takes a SemanticLabel and returns true if the PatternRecognizer
uses it.
- isLeaf() - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
-
- isLeaf() - Method in interface gov.sandia.cognition.learning.algorithm.tree.DecisionTreeNode
-
Returns true if this node is a leaf node (has no children) and false
otherwise.
- isLeaf() - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
-
Returns true if this node is a leaf node, which means it has no
children.
- isMatch(Field) - Method in class gov.sandia.cognition.statistics.method.FieldConfidenceInterval
-
Determines if the given field is a match to the internal Field
- isMatch(String) - Method in class gov.sandia.cognition.statistics.method.FieldConfidenceInterval
-
Determines if the given field is a match to the internal Field
- isNativeBLAS() - Static method in class gov.sandia.cognition.math.matrix.mtj.NativeMatrixTests
-
Tests if Native BLAS is loaded
- isNativeLAPACK() - Static method in class gov.sandia.cognition.math.matrix.mtj.NativeMatrixTests
-
Tests if Native LAPACK is loaded
- isNegative() - Method in class gov.sandia.cognition.math.LogNumber
-
Gets whether or not this value has a negative sign.
- isNode(SemanticLabel) - Method in class gov.sandia.cognition.framework.DefaultSemanticNetwork
-
Returns true if the given SemanticLabel is a node in the
SemanticNetwork.
- isNode(SemanticLabel) - Method in class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLite
-
Returns true if the given semantic label is a node in the network.
- isNode(SemanticLabel) - Method in interface gov.sandia.cognition.framework.SemanticNetwork
-
Returns true if the given SemanticLabel is a node in the
SemanticNetwork.
- isObject(Object) - Method in interface gov.sandia.cognition.text.relation.RelationNetwork
-
Determines whether or not the given object is a node in the relation
network.
- isObject(Object) - Method in class gov.sandia.cognition.text.term.relation.MatrixBasedTermSimilarityNetwork
-
- isOutputLabel(SemanticLabel) - Method in interface gov.sandia.cognition.framework.lite.PatternRecognizerLite
-
Takes a SemanticLabel and returns true if it is a label used as
output from the PatternRecognizerLite.
- isOutputLabel(SemanticLabel) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
-
Takes a SemanticLabel and returns true if it is a label used as
output from the PatternRecognizerLite.
- isPrime(long) - Static method in class gov.sandia.cognition.hash.HashFunctionUtil
-
Determines if a number is prime or not
- isResultValid() - Method in class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm
-
- isResultValid() - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
-
- isResultValid() - Method in interface gov.sandia.cognition.algorithm.StoppableAlgorithm
-
Indicates whether or not the algorithm results are in a consistent state
or not.
- isResultValid() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Returns true if execution stopped because the residual was below the
acceptable tolerance (vs.
- isResultValid() - Method in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
Returns true if this matrix has a potentially sparse underlying
structure.
- isSparse() - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
-
- isSparse() - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Returns true if this matrix has a potentially sparse underlying
structure.
- isSparse() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
-
- isSparse() - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
-
- isSparse() - Method in interface gov.sandia.cognition.math.matrix.Vector
-
Returns true if this vector has a potentially sparse underlying
structure.
- isSquare() - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
-
- isSquare() - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
-
- isSquare() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
Determines if the matrix is square (numRows == numColumns)
- isSquare() - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Determines if the matrix is square (numRows == numColumns)
- isSquare() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
-
- isSquare() - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
-
- isSymmetric() - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
-
- isSymmetric(double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
-
- isSymmetric(double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
-
- isSymmetric(double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
Determines if the matrix is effectively symmetric
- isSymmetric() - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Determines if the matrix is symmetric.
- isSymmetric(double) - Method in interface gov.sandia.cognition.math.matrix.Matrix
-
Determines if the matrix is effectively symmetric
- isSymmetric(double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
-
- isSymmetric() - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
-
- isSymmetric(double) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
-
- isTokenMember(char) - Method in class gov.sandia.cognition.text.token.AbstractCharacterBasedTokenizer
-
Determines if the given character is considered to be part of a token.
- isTokenMember(char) - Method in class gov.sandia.cognition.text.token.LetterNumberTokenizer
-
- isUnitVector() - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
-
- isUnitVector(double) - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
-
- isUnitVector() - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
-
- isUnitVector(double) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
-
- isUnitVector() - Method in interface gov.sandia.cognition.math.matrix.VectorSpace
-
Determines if this vector is a unit vector (norm2 = 1.0).
- isUnitVector(double) - Method in interface gov.sandia.cognition.math.matrix.VectorSpace
-
Determines if this vector is a unit vector within some tolerance for the
2-norm.
- isUpdateBias() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
-
Gets whether or not the algorithm is updating the bias.
- isValid() - Method in class gov.sandia.cognition.io.ReaderTokenizer
-
Returns the status of the ReaderTokenizer
- isValidBracket() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
-
- isValidBracket() - Method in interface gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizer
-
Returns true if the algorithm has found a valid bracket on a minimum,
false if the algorithm needs to continue the bracketing phase
- isVoteOutOfBagOnly() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
-
Gets whether during learning ensemble members can only vote on items
that they are not in their bag (training set).
- isWcc() - Method in class gov.sandia.cognition.graph.GraphMetrics
-
Returns true if the graph is a single weakly connected component (WCC),
else false.
- isWeightsEnabled() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
-
Gets whether or not the linear weight term is enabled.
- isWhitespace(String) - Static method in class gov.sandia.cognition.util.StringUtil
-
Returns true if the given String is null or all whitespace.
- isZero() - Method in class gov.sandia.cognition.math.AbstractRing
-
- isZero(double) - Method in class gov.sandia.cognition.math.ComplexNumber
-
- isZero() - Method in class gov.sandia.cognition.math.LogNumber
-
- isZero(double) - Method in class gov.sandia.cognition.math.LogNumber
-
- isZero(double) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
-
- isZero(double) - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
-
- isZero() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
Determines if this ring is equal to zero.
- isZero(double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
Determines if this ring is equal to zero using the element-wise effective
zero value.
- isZero() - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
-
- isZero(double) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
-
- isZero() - Method in class gov.sandia.cognition.math.MutableDouble
-
- isZero(double) - Method in class gov.sandia.cognition.math.MutableDouble
-
- isZero() - Method in class gov.sandia.cognition.math.MutableInteger
-
- isZero(double) - Method in class gov.sandia.cognition.math.MutableInteger
-
- isZero() - Method in class gov.sandia.cognition.math.MutableLong
-
- isZero(double) - Method in class gov.sandia.cognition.math.MutableLong
-
- isZero() - Method in interface gov.sandia.cognition.math.Ring
-
Determines if this ring is equal to zero.
- isZero(double) - Method in interface gov.sandia.cognition.math.Ring
-
Determines if this ring is equal to zero using the element-wise effective
zero value.
- isZero() - Method in class gov.sandia.cognition.math.UnsignedLogNumber
-
- isZero(double) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
-
- isZero(double) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
-
- items - Variable in class gov.sandia.cognition.math.geometry.Quadtree
-
All of the items in the tree.
- iterate() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver
-
- iterate() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver
-
- iterate() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Called during each step of the iterative solver.
- iterate() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer
-
- iterate() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver
-
- iterate(double, double) - Method in class gov.sandia.cognition.math.LentzMethod
-
Step of Lentz's iteration
- iteration - Variable in class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
-
Number of iterations the algorithm has executed.
- iterationCounter - Variable in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Counts the number of iterations executed thus far.
- IterationMeasurablePerformanceReporter - Class in gov.sandia.cognition.algorithm.event
-
An iterative algorithm listeners for MeasurablePerformanceAlgorithm
objects that reports the performance of the algorithm at the end of each
iteration.
- IterationMeasurablePerformanceReporter() - Constructor for class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter
-
Creates a new IterationMeasurablePerformanceReporter that
reports to System.out using the default format.
- IterationMeasurablePerformanceReporter(PrintStream) - Constructor for class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter
-
Creates a new IterationMeasurablePerformanceReporter that
reports to the given print stream using the default format.
- IterationMeasurablePerformanceReporter(String) - Constructor for class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter
-
Creates a new IterationMeasurablePerformanceReporter that
reports to System.out and the given format.
- IterationMeasurablePerformanceReporter(PrintStream, String) - Constructor for class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter
-
Creates a new IterationMeasurablePerformanceReporter that
reports to the given print stream and format.
- iterationsPerSample - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
-
The number of iterations to the Markov Chain Monte Carlo algorithm
between samples (after the burn-in iterations).
- IterationStartReporter - Class in gov.sandia.cognition.algorithm.event
-
An iterative algorithm listener that reports the start of each iteration
to the given print stream.
- IterationStartReporter() - Constructor for class gov.sandia.cognition.algorithm.event.IterationStartReporter
-
Creates a new IterationStartReporter that
reports to System.out using the default format.
- IterationStartReporter(PrintStream) - Constructor for class gov.sandia.cognition.algorithm.event.IterationStartReporter
-
Creates a new IterationStartReporter that
reports to the given print stream using the default format.
- IterationStartReporter(String) - Constructor for class gov.sandia.cognition.algorithm.event.IterationStartReporter
-
Creates a new IterationStartReporter that
reports to System.out and the given format.
- IterationStartReporter(PrintStream, String) - Constructor for class gov.sandia.cognition.algorithm.event.IterationStartReporter
-
Creates a new IterationStartReporter that
reports to the given print stream and format.
- IterativeAlgorithm - Interface in gov.sandia.cognition.algorithm
-
The IterativeAlgorithm interface defines the functionality of a
algorithm that works through multiple iteration steps in order to perform
its computation.
- IterativeAlgorithmListener - Interface in gov.sandia.cognition.algorithm
-
The IterativeAlgorithmListener interface defines the events that
are generated by an IterativeAlgorithm.
- IterativeMatrixSolver<Operator extends MatrixVectorMultiplier> - Class in gov.sandia.cognition.learning.algorithm.minimization.matrix
-
Base class for all iterative matrix solvers that takes care of most of the
basic iterative logic and the function minimizer interface.
- IterativeMatrixSolver(Vector, Vector) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Initializes a solver with basic necessary values
- IterativeMatrixSolver(Vector, Vector, double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Initializes a solver with a few more values
- IterativeMatrixSolver(Vector, Vector, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Inititalizes a solver with all user-definable parameters
- IterativeMatrixSolver(IterativeMatrixSolver<Operator>) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
-
Protected copy constructor
- iterator() - Method in class gov.sandia.cognition.collection.AbstractLogNumberMap.SimpleEntrySet
-
- iterator() - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntrySet
-
- iterator() - Method in class gov.sandia.cognition.collection.DefaultMultiCollection
-
- iterator() - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
-
- iterator() - Method in class gov.sandia.cognition.collection.IntegerSpan
-
- iterator() - Method in class gov.sandia.cognition.framework.lite.CogxelStateLite
- iterator() - Method in class gov.sandia.cognition.math.Combinations
-
- iterator() - Method in class gov.sandia.cognition.math.geometry.KDTree
-
Iterates through the KDTree using "inorder", also known as "symmetric
traversal", of the tree.
- iterator() - Method in class gov.sandia.cognition.math.geometry.KDTree.Neighborhood
-
- iterator() - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
-
- iterator() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
-
- iterator() - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
-
- iterator() - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
-
- iterator() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
-
- iterator() - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
-
- iterator() - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.Domain
-
- IVotingCategorizerLearner<InputType,CategoryType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
-
Learns an ensemble in a method similar to bagging except that on each
iteration the bag is built from two parts, each sampled from elements from
disjoint sets.
- IVotingCategorizerLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
-
Creates a new IVotingCategorizerLearner.
- IVotingCategorizerLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>, int, double, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
-
Creates a new IVotingCategorizerLearner.
- IVotingCategorizerLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>, int, double, double, boolean, Factory<? extends DataDistribution<CategoryType>>, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
-
Creates a new IVotingCategorizerLearner.
- IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria<InputType,CategoryType> - Class in gov.sandia.cognition.learning.algorithm.ensemble
-
Implements a stopping criteria for IVoting that uses the out-of-bag
error to determine when to stop learning the ensemble.