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

W

weakLearner - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
The "weak learner" that must learn from the weighted input-output pairs on each iteration.
weakLearner - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost
The "weak learner" that must learn from the weighted input-output pairs on each iteration.
WeibullDistribution - Class in gov.sandia.cognition.statistics.distribution
Describes a Weibull distribution, which is often used to describe the mortality, lifespan, or size distribution of objects.
WeibullDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Creates a new instance of WeibullDistribution
WeibullDistribution(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Creates a new instance of WeibullDistribution
WeibullDistribution(WeibullDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Copy constructor
WeibullDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
CDF of the Weibull distribution
WeibullDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution
PDF of the Weibull distribution
weight - Variable in class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
The weight.
weight - Variable in class gov.sandia.cognition.learning.function.kernel.WeightedKernel
The weight on the kernel.
weight - Variable in class gov.sandia.cognition.util.AbstractWeighted
The weight
weight - Variable in class gov.sandia.cognition.util.DefaultWeightedPair
The weight for the pair.
WeightComparator() - Constructor for class gov.sandia.cognition.util.DefaultWeightedValue.WeightComparator
Creates a new WeightComarator.
Weighted - Interface in gov.sandia.cognition.util
The Weighted interface is to be used on objects that have some weight component assigned to them.
WeightedAdditiveEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends java.lang.Number>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An implementation of an ensemble that takes a weighted sum of the values returned by its members.
WeightedAdditiveEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAdditiveEnsemble
Creates a new, empty of WeightedAdditiveEnsemble.
WeightedAdditiveEnsemble(List<WeightedValue<MemberType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAdditiveEnsemble
Creates a new instance of WeightedAdditiveEnsemble.
WeightedAdditiveEnsemble(List<WeightedValue<MemberType>>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAdditiveEnsemble
Creates a new instance of WeightedAdditiveEnsemble.
weightedAverage(Iterable<? extends WeightedValue<? extends Number>>) - Static method in class gov.sandia.cognition.math.WeightedNumberAverager
Computes the weighted average of the given data.
WeightedAveragingEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends java.lang.Number>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An implementation of an ensemble that takes the weighted average of its members.
WeightedAveragingEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAveragingEnsemble
Creates a new, empty of WeightedAveragingEnsemble.
WeightedAveragingEnsemble(List<WeightedValue<MemberType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAveragingEnsemble
Creates a new instance of WeightedAveragingEnsemble.
WeightedBinaryEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends java.lang.Boolean>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
The WeightedBinaryEnsemble class implements an Ensemble of BinaryCategorizer objects where each categorizer is assigned a weight and the category is selected by choosing the one with the largest sum of weights.
WeightedBinaryEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble
Creates a new instance of WeightedBinaryEnsemble.
WeightedBinaryEnsemble(List<WeightedValue<MemberType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble
Creates a new instance of WeightedBinaryEnsemble.
weightedData - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
An array list containing the weighted version of the data.
weightedData - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost
An array list containing the weighted version of the data.
WeightedDenseMemoryGraph<NodeNameType> - Class in gov.sandia.cognition.graph
Implementation for a weighted graph type
WeightedDenseMemoryGraph() - Constructor for class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
Default constructor creates an empty graph Execution: O(1)
WeightedDenseMemoryGraph(int, int) - Constructor for class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
Initialize an empty graph with a default size (for speed-ups later) Execution: O(m + n) for reserving necessary space
WeightedEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.WeightedEstimator
Default constructor
WeightedEuclideanDistanceMetric - Class in gov.sandia.cognition.learning.function.distance
A distance metric that weights each dimension of a vector differently before computing Euclidean distance.
WeightedEuclideanDistanceMetric() - Constructor for class gov.sandia.cognition.learning.function.distance.WeightedEuclideanDistanceMetric
Creates a new WeightedEuclideanDistanceMetric with no initial weights.
WeightedEuclideanDistanceMetric(Vector) - Constructor for class gov.sandia.cognition.learning.function.distance.WeightedEuclideanDistanceMetric
Creates a new WeightedEuclideanDistanceMetric with the given weights.
WeightedInputOutputPair<InputType,OutputType> - Interface in gov.sandia.cognition.learning.data
The WeightedInputOutputPair class implements an additional weighting term on an InputOutputPair, typically used to inform learning algorithms of the relative weight between examples.
WeightedKernel<InputType> - Class in gov.sandia.cognition.learning.function.kernel
The WeightedKernel class implements a kernel that takes another kernel, evaluates it, and then the result is rescaled by a given weight.
WeightedKernel() - Constructor for class gov.sandia.cognition.learning.function.kernel.WeightedKernel
Creates a new instance of WeightedKernel with a default weight of 1.0 and a null kernel.
WeightedKernel(double, Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.function.kernel.WeightedKernel
Creates a new instance of WeightedKernel from the given weight and kernel.
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.WeightedMaximumLikelihoodEstimator
Default constructor.
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.WeightedMaximumLikelihoodEstimator
Default constructor
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.WeightedMaximumLikelihoodEstimator
Default constructor
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.WeightedMaximumLikelihoodEstimator
Default constructor.
WeightedMaximumLikelihoodEstimator(double) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.WeightedMaximumLikelihoodEstimator
Creates a new instance of WeightedMaximumLikelihoodEstimator
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.WeightedMaximumLikelihoodEstimator
Default constructor
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.PoissonDistribution.WeightedMaximumLikelihoodEstimator
Creates a new WeightedMaximumLikelihoodEstimator.
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.WeightedMaximumLikelihoodEstimator
Default constructor
WeightedMaximumLikelihoodEstimator(double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution.WeightedMaximumLikelihoodEstimator
Creates a new instance of WeightedMaximumLikelihoodEstimator
WeightedMaximumLikelihoodEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.WeightedMaximumLikelihoodEstimator
Default constructor
WeightedMaximumLikelihoodEstimator(double) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.WeightedMaximumLikelihoodEstimator
Creates a new instance of WeightedMaximumLikelihoodEstimator
WeightedMeanLearner - Class in gov.sandia.cognition.learning.algorithm.baseline
The WeightedMeanLearner class implements a baseline learner that computes the weighted mean output value.
WeightedMeanLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.baseline.WeightedMeanLearner
Creates a new MeanLearner.
WeightedMomentMatchingEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.BetaDistribution.WeightedMomentMatchingEstimator
Default constructor
WeightedMomentMatchingEstimator() - Constructor for class gov.sandia.cognition.statistics.distribution.GammaDistribution.WeightedMomentMatchingEstimator
Default constructor
WeightedMostFrequentLearner<OutputType> - Class in gov.sandia.cognition.learning.algorithm.baseline
The WeightedMostFrequentLearner class implements a baseline learning algorithm that finds the most frequent output of a given dataset based on the weights of the examples.
WeightedMostFrequentLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.baseline.WeightedMostFrequentLearner
Creates a new MostFrequentLearner.
WeightedNumberAverager - Class in gov.sandia.cognition.math
Averages together given set of weighted values by adding up the weight times the value and then dividing by the total weight.
WeightedNumberAverager() - Constructor for class gov.sandia.cognition.math.WeightedNumberAverager
Creates a new WeightedNumberAverager
WeightedPair<FirstType,SecondType> - Interface in gov.sandia.cognition.util
The WeightedPair interface defines an extension of a normal Pair that includes an additional weight.
WeightedRingAverager<RingType extends Ring<RingType>> - Class in gov.sandia.cognition.math
A type of Summarizer for Rings (Matrices, Vectors, ComplexNumbers).
WeightedRingAverager() - Constructor for class gov.sandia.cognition.math.WeightedRingAverager
Creates a new instance of WeightedRingAverager
WeightedTargetEstimatePair<TargetType,EstimateType> - Interface in gov.sandia.cognition.learning.data
Extends TargetEstimatePair with an additional weight field.
WeightedValue<ValueType> - Interface in gov.sandia.cognition.util
Interface for a wrapper for a value that associates a weight with it.
weightedValues - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask
Weighted values for the PDF estimator.
WeightedVotingCategorizerEnsemble<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
An ensemble of categorizers where each ensemble member is evaluated with the given input to find the category to which its weighted votes are assigned.
WeightedVotingCategorizerEnsemble() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble
Creates a new instance of WeightedVotingCategorizerEnsemble.
WeightedVotingCategorizerEnsemble(Set<CategoryType>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble
Creates a new instance of WeightedVotingCategorizerEnsemble.
WeightedVotingCategorizerEnsemble(Set<CategoryType>, List<WeightedValue<MemberType>>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble
Creates a new instance of WeightedVotingCategorizerEnsemble.
weightPrior - Variable in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
Prior distribution of the weights, typically a zero-mean, diagonal-variance distribution.
weightRegularization - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The regularization term for the linear weights.
weights - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
The weight vector (w) for each dimension.
weights - Variable in class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer
The weight vector.
weights - Variable in class gov.sandia.cognition.learning.function.distance.WeightedEuclideanDistanceMetric
The weights assigned to each dimension for the distance.
weightsEnabled - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
True if the linear weight term is enabled.
weightUpdate - Variable in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
The amount of the weight update (alpha).
weightUpdateInverse - Variable in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
The cached value of the inverse of weight update (commonly alpha or 1 + epsilon).
weightVector - Variable in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminant
Weight Vector to dot-product with the input
WilcoxonSignedRankConfidence - Class in gov.sandia.cognition.statistics.method
This is a Wilcoxon Signed-Rank Sum test, which performs a pair-wise test to determine if two datasets are different.
WilcoxonSignedRankConfidence() - Constructor for class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence
Creates a new instance of WilcoxonSignedRankConfidence
WilcoxonSignedRankConfidence.Statistic - Class in gov.sandia.cognition.statistics.method
ConfidenceStatistics associated with a Wilcoxon test
WinnerTakeAllCategorizer<InputType,CategoryType> - Class in gov.sandia.cognition.learning.function.categorization
Adapts an evaluator that outputs a vector to be used as a categorizer.
WinnerTakeAllCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer
Creates a new WinnerTakesAllCategorizer.
WinnerTakeAllCategorizer(Evaluator<? super InputType, ? extends Vectorizable>, Set<CategoryType>) - Constructor for class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer
Creates a new WinnerTakesAllCategorizer.
WinnerTakeAllCategorizer.Learner<InputType,CategoryType> - Class in gov.sandia.cognition.learning.function.categorization
A learner for the adapter.
Winnow - Class in gov.sandia.cognition.learning.algorithm.perceptron
An implementation of the Winnow incremental learning algorithm.
Winnow() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
Creates a new Winnow with default parameters.
Winnow(double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
Creates a new Winnow with the given weight update and the default demote to zero (false).
Winnow(double, boolean) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
Creates a new Winnow with the given parameters.
withCreator(ClusterCreator<MiniBatchCentroidCluster, Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer.Builder
 
WithinClusterDivergence<ClusterType extends Cluster<DataType>,DataType> - Interface in gov.sandia.cognition.learning.algorithm.clustering.divergence
Defines a function that computes the divergence of the elements in a cluster.
WithinClusterDivergenceWrapper<ClusterType extends Cluster<DataType>,DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
Accumulates the results of a ClusterDivergenceFunction by summing the divergence of each point to its cluster.
WithinClusterDivergenceWrapper(DivergenceFunction<? super ClusterType, ? super DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.WithinClusterDivergenceWrapper
withinInterval(double) - Method in class gov.sandia.cognition.statistics.method.ConfidenceInterval
Returns whether or not the value is within the specified interval
withinInterval(Object) - Method in class gov.sandia.cognition.statistics.method.FieldConfidenceInterval
Determines whether the Field within the given Object is within the specified interval
withInitializer(FixedClusterInitializer<MiniBatchCentroidCluster, Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer.Builder
 
WithinNormalizedCentroidClusterCosineDivergence<V extends Vectorizable> - Class in gov.sandia.cognition.learning.algorithm.clustering.divergence
This class calculates the total cosine divergence between all members of a cluster and the cluster's centroid
WithinNormalizedCentroidClusterCosineDivergence() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.divergence.WithinNormalizedCentroidClusterCosineDivergence
 
withMaxIterations(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer.Builder
 
withMinibatchSize(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer.Builder
 
withNumClusters(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer.Builder
 
withRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer.Builder
 
WolfeConditions - Class in gov.sandia.cognition.learning.algorithm.minimization.line
The Wolfe conditions define a set of sufficient conditions for "sufficient decrease" in inexact line search.
WolfeConditions(InputOutputSlopeTriplet, double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions
Creates a new instance of WolfeConditions
WolfeConditions(WolfeConditions) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions
Copy Constructor
wordCounts - Variable in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Maps known words to the number of times they've been seen.
words - Variable in class gov.sandia.cognition.text.term.filter.DefaultStopList
The set of words in the stop list, all in lower-case.
write(String, SemanticNetwork) - Static method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Writes a SemanticNetwork to the given file using the CSV format.
write(File, SemanticNetwork) - Static method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Writes a SemanticNetwork to the given file using the CSV format.
write(PrintWriter, SemanticNetwork) - Static method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Writes a SemanticNetwork to the given stream using the CSV format.
write(OutputStream, Serializable) - Static method in class gov.sandia.cognition.io.XStreamSerializationHandler
Writes the given object to the given OutputStream
write(Writer, Serializable) - Static method in class gov.sandia.cognition.io.XStreamSerializationHandler
Writes the given object to the given Writer
write(Matrix) - Method in class gov.sandia.cognition.math.matrix.MatrixWriter
Writes the given matrix to the Java-based writer
write(Vector) - Method in class gov.sandia.cognition.math.matrix.VectorWriter
Writes the given vector to the Java-based writer
writeCollection(Iterable<? extends Vector>) - Method in class gov.sandia.cognition.math.matrix.VectorWriter
Writes the collection of vectors to the Java-based writer
writeModelToFile(String, CognitiveModel) - Static method in class gov.sandia.cognition.framework.io.SerializedModelHandler
Writes the given CognitiveModel to the given file using Java object serialization
writeModelToFile(File, CognitiveModel) - Static method in class gov.sandia.cognition.framework.io.SerializedModelHandler
Writes the given CognitiveModel to the given file using Java object serialization
writeObject(OutputStream, SerializedType) - Method in class gov.sandia.cognition.io.serialization.AbstractTextSerializationHandler
 
writeObject(OutputStream, SerializedType) - Method in class gov.sandia.cognition.io.serialization.GZIPSerializationHandler
 
writeObject(OutputStream, Serializable) - Method in class gov.sandia.cognition.io.serialization.JavaDefaultBinarySerializationHandler
 
writeObject(OutputStream, SerializedType) - Method in interface gov.sandia.cognition.io.serialization.StreamSerializationHandler
Writes an object to a given output stream.
writeObject(Writer, SerializedType) - Method in interface gov.sandia.cognition.io.serialization.TextSerializationHandler
Writes an object to the given writer.
writeObject(Writer, Serializable) - Method in class gov.sandia.cognition.io.serialization.XStreamSerializationHandler
 
writeObjectToFile(File, Serializable) - Static method in class gov.sandia.cognition.io.ObjectSerializationHandler
Writes a Java serialized Object to the given file.
writeState(CognitiveModelState) - Method in interface gov.sandia.cognition.framework.concurrent.ConcurrentCognitiveModule
Write out the model and module state changes resulting from a call to evaluate NOTE: output state was held temporarily for the sole purpose of supporting concurrency of module evaluation; state is NEVER retained locally across module update cycles
writeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule
Write out the model and module state changes resulting from a call to evaluate NOTE: output state was held temporarily for the sole purpose of supporting concurrency of module evaluation; state is NEVER retained locally across module update cycles
writeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.learning.StatefulEvaluatorBasedCognitiveModule
Write out the model and module state changes resulting from a call to evaluate NOTE: output state was held temporarily for the sole purpose of supporting concurrency of module evaluation; state is NEVER retained locally across module update cycles
writeState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModule
Write out the model and module state changes resulting from a call to evaluate NOTE: output state was held temporarily for the sole purpose of supporting concurrency of module evaluation; state is NEVER retained locally across module update cycles
writeToFile(String, SerializedType) - Method in class gov.sandia.cognition.io.serialization.AbstractFileSerializationHandler
 
writeToFile(File, SerializedType) - Method in class gov.sandia.cognition.io.serialization.AbstractStreamSerializationHandler
 
writeToFile(String, SerializedType) - Method in interface gov.sandia.cognition.io.serialization.FileSerializationHandler
Writes an object to a given file.
writeToFile(File, SerializedType) - Method in interface gov.sandia.cognition.io.serialization.FileSerializationHandler
Reads an object from a given file.
writeToFile(String, Serializable) - Static method in class gov.sandia.cognition.io.XStreamSerializationHandler
Writes the given object to the given file using XStream serialization.
writeToFile(File, Serializable) - Static method in class gov.sandia.cognition.io.XStreamSerializationHandler
Writes the given object to the given file using XStream serialization.
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Skip navigation links