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safeFirstNext() - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
Try to advance the first entry...
safeFirstNext() - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
Try to advance the first entry...
safeGetDimensionality(Vectorizable) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
Gets the dimensionality of the given vector, if it is not null.
safeGetDimensionality(Vector) - Static method in class gov.sandia.cognition.math.matrix.VectorUtil
Gets the dimensionality of the given vector, if it is not null.
safeSecondNext() - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
Try to advance the second entry...
safeSecondNext() - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
Try to advance the second entry...
salt(HashFunction, byte[]...) - Static method in class gov.sandia.cognition.hash.HashFunctionUtil
Computes the salted hash of the given inputs, that is, we concatenate the inputs together and compute the hash of the concatenated bytes.
saltInto(byte[], HashFunction, byte[]...) - Static method in class gov.sandia.cognition.hash.HashFunctionUtil
Computes the salted hash of the given inputs, that is, we concatenate the inputs together and compute the hash of the concatenated bytes.
sample(Random) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
 
sample(Random, int) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
 
sample(Random) - Method in class gov.sandia.cognition.statistics.AbstractDataDistribution
 
sample(Random, int) - Method in class gov.sandia.cognition.statistics.AbstractDataDistribution
 
sample(Random) - Method in class gov.sandia.cognition.statistics.AbstractDistribution
 
sample(Random, int) - Method in class gov.sandia.cognition.statistics.AbstractDistribution
 
sample(Random) - Method in class gov.sandia.cognition.statistics.AbstractRandomVariable
 
sample(Random) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Draws a single sample by the method of adaptive rejection sampling.
sample(Random, int) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Draws samples by the adaptive rejection sampling method, which will have the distribution of the logFunction
sample(Random) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
 
sample(Random, int) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
 
sample(ClosedFormDistribution<ObservationType>, String, Distribution<ParameterType>, Random, int) - Static method in class gov.sandia.cognition.statistics.bayesian.BayesianUtil
Samples from the given BayesianParameter by first sampling the prior distribution, then updating the conditional distribution, then sampling from the updated conditional distribution.
sample(BayesianParameter<ParameterType, ? extends Distribution<ObservationType>, ? extends Distribution<ParameterType>>, Random, int) - Static method in class gov.sandia.cognition.statistics.bayesian.BayesianUtil
Samples from the given BayesianParameter by first sampling the prior distribution, then updating the conditional distribution, then sampling from the updated conditional distribution.
Sample(double, ArrayList<DirichletProcessMixtureModel.DPMMCluster<ObservationType>>) - Constructor for class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
Creates a new instance of Sample
sample(Random) - Method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
 
sample(double, Random, int) - Static method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Samples from a Chi-Square distribution with the given degrees of freedom
sample(Random) - Method in class gov.sandia.cognition.statistics.distribution.DirichletDistribution
 
sample(double, double, Random, int) - Static method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Efficiently samples from a Gamma distribution given by the shape and scale parameters.
sample(double, double, Random) - Static method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Provides a single sample from a Gamma distribution with the given shape and scale.
sample(Random, Vector, Matrix, int) - Static method in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
Creates a single sample covariance matrix inverse from the given parameters.
sample(Random) - Method in class gov.sandia.cognition.statistics.distribution.LinearMixtureModel
 
sample(Vector, Matrix, Random, int) - Static method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Returns a collection of draws this Gaussian with the given mean and covariance.
sample(Vector, Matrix, Random) - Static method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Returns a single draw from the Gaussian with the given mean and covariance.
sample(Random) - Method in interface gov.sandia.cognition.statistics.Distribution
Draws a single random sample from the distribution.
sample(Random, int) - Method in interface gov.sandia.cognition.statistics.Distribution
Draws multiple random samples from the distribution.
sample(Random) - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution
 
sample(ProbabilityDensityFunction<ValueType>, Evaluator<ValueType, Double>, Random, int) - Static method in class gov.sandia.cognition.statistics.method.ImportanceSampling
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.
sample(CumulativeDistributionFunction<Double>, Random, int) - Static method in class gov.sandia.cognition.statistics.method.InverseTransformSampling
Samples from the given CDF using the inverseRootFinder transform sampling method.
sample(ProbabilityFunction<DataType>, Random, int) - Method in class gov.sandia.cognition.statistics.montecarlo.DirectSampler
 
sample(Evaluator<? super DataType, Double>, Random, int) - Method in class gov.sandia.cognition.statistics.montecarlo.ImportanceSampler
 
sample(FunctionType, Random, int) - Method in interface gov.sandia.cognition.statistics.montecarlo.MonteCarloSampler
Draws samples according to the distribution of the target function.
sample(ProbabilityMassFunction<DataType>, Random, int) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples from the ProbabilityMassFunction.
sample(double[], List<? extends DataType>, Random) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples an element from the domain proportionately to the cumulative weights in the given weight array using a fast binary search algorithm.
sample(Random) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
sample(Random, int) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
sampleAsBoolean(Random) - Method in class gov.sandia.cognition.statistics.distribution.BernoulliDistribution
Samples from the Bernoulli distribution as a boolean.
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
Samples from this distribution as a double.
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution
 
sampleAsDouble(double, double, Random) - Static method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Efficiently samples from a Gamma distribution given by the shape and scale parameters.
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
 
sampleAsDouble(Random) - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
 
sampleAsDouble(Random) - Method in interface gov.sandia.cognition.statistics.SmoothUnivariateDistribution
Samples a value from this distribution as a double.
sampleAsDoubles(Random, int) - Method in class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution
 
sampleAsDoubles(double, Random, int) - Static method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Samples from a Chi-Square distribution with the given degrees of freedom
sampleAsDoubles(double, double, Random, int) - Static method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Efficiently samples from a Gamma distribution given by the shape and scale parameters.
sampleAsDoubles(Random, int) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
 
sampleAsDoubles(Random, int) - Method in interface gov.sandia.cognition.statistics.SmoothUnivariateDistribution
Samples values from this distribution as an array of doubles.
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.BernoulliDistribution
 
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
 
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
 
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.GeometricDistribution
 
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
 
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
 
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
 
sampleAsInt(Random) - Method in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
 
sampleAsInt(Random) - Method in interface gov.sandia.cognition.statistics.IntegerDistribution
Draws a single random sample from the distribution as an int.
sampleAsInts(Random, int) - Method in class gov.sandia.cognition.statistics.AbstractClosedFormIntegerDistribution
 
sampleAsInts(Random, int) - Method in interface gov.sandia.cognition.statistics.IntegerDistribution
Samples values from this distribution as an array of ints.
sampleCount - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
The number of model parameter samples that have been made.
sampleExp(double) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LineSegment
Sample from the exponent of the line segment
sampleIndexFromCumulativeProportions(Random, double[]) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples a random index from an array of cumulative proportions.
sampleIndexFromProbabilities(Random, double[]) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples an random index according to the given array of probabilities.
sampleIndexFromProbabilities(Random, Vector) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples an random index according to the given vector of probabilities.
sampleIndexFromProportions(Random, double[]) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples a random index according to the given proportions.
sampleIndexFromProportions(Random, double[], double) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples a random index according to the given proportions.
sampleIndicesFromCumulativeProportions(Random, double[], int) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples a multiple indices with replacement from an array of cumulative proportions.
sampleIndicesFromProportions(Random, double[], int) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples an array of indices from a given set of proportions.
sampleIndicesWithReplacementInto(ArrayList<Integer>, ArrayList<? extends DataType>, int, Random, ArrayList<DataType>, int[]) - Static method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Takes the given number of samples from the given list and places them in the given output list.
sampleInto(Random, int, Collection<? super ObservationType>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
 
sampleInto(Random, int, Collection<? super ObservationType>) - Method in class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer
 
sampleInto(Random, int[], int, int) - Method in class gov.sandia.cognition.statistics.AbstractClosedFormIntegerDistribution
 
sampleInto(Random, int, Collection<? super Double>) - Method in class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution
 
sampleInto(Random, int, Collection<? super KeyType>) - Method in class gov.sandia.cognition.statistics.AbstractDataDistribution
 
sampleInto(Random, int, Collection<? super Double>) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.BernoulliDistribution
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
 
sampleInto(Random, int[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
 
sampleInto(Random, int[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
 
sampleInto(Random, int, Collection<? super Double>) - Method in class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.DirichletDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution
 
sampleInto(double, double, Random, double[], int, int) - Static method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Efficiently samples from a Gamma distribution given by the shape and scale parameters.
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.GeometricDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
 
sampleInto(Random, int, Collection<? super Matrix>) - Method in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
 
sampleInto(Random, int, Collection<? super Double>) - Method in class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
 
sampleInto(Random, int, Collection<? super DataType>) - Method in class gov.sandia.cognition.statistics.distribution.LinearMixtureModel
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
 
sampleInto(Vector, Matrix, Random, int, Collection<? super Vector>) - Static method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Performs a collection of draws this Gaussian with the given mean and covariance.
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
 
sampleInto(Random, int[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
 
sampleInto(Random, int, Collection<? super Vector>) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
 
sampleInto(Random, int, Collection<? super Matrix>) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
 
sampleInto(Random, int[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
 
sampleInto(Random, int, Collection<? super DataType>) - Method in interface gov.sandia.cognition.statistics.Distribution
Draws multiple random samples from the distribution and puts the result into the given collection.
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
 
sampleInto(Random, int, Collection<? super Double>) - Method in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
 
sampleInto(Random, int, Collection<? super Double>) - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
 
sampleInto(Random, double[], int, int) - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
 
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
 
sampleInto(Random, int[], int, int) - Method in interface gov.sandia.cognition.statistics.IntegerDistribution
Samples values from this distribution as an array of ints.
sampleInto(CumulativeDistributionFunction<Double>, Random, int, Collection<? super Double>) - Static method in class gov.sandia.cognition.statistics.method.InverseTransformSampling
Samples from the given CDF using the inverseRootFinder transform sampling method.
sampleInto(ProbabilityMassFunction<DataType>, Random, int, Collection<? super DataType>) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples from the ProbabilityMassFunction.
sampleInto(Random, double[], int, int) - Method in interface gov.sandia.cognition.statistics.SmoothUnivariateDistribution
Samples values from this distribution as an array of doubles.
sampleInto(Random, int, Collection<? super Number>) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
sampleMultiple(ProbabilityMassFunction<DataType>, Random, int) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples from the ProbabilityMassFunction.
sampleMultiple(double[], List<? extends DataType>, Random, int) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples multiple elements from the domain proportionately to the cumulative weights in the given weight array using a fast binary search algorithm
sampleMultipleInto(ProbabilityMassFunction<DataType>, Random, int, Collection<? super DataType>) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples from the ProbabilityMassFunction.
sampleMultipleInto(double[], List<? extends DataType>, Random, int, Collection<? super DataType>) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples multiple elements from the domain proportionately to the cumulative weights in the given weight array using a fast binary search algorithm
sampleNextCustomer(Collection<Integer>, int, double, Random) - Static method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Determines where the next customer sits, given the number of customers already sitting at the various tables and the concentration parameter alpha.
sampler - Variable in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.ScalarEstimator.MinimizerFunction
Sampler function
SampleRange(Random, int, SmoothUnivariateDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.SampleRange
Creates a new instance of SampleRange
sampleSingle(ProbabilityMassFunction<DataType>, Random) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Draws a single sample from the given PMF
sampleSingle(double[], Collection<? extends DataType>, Random) - Static method in class gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil
Samples a single element from the domain proportionately to the given weights
sampleSize - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
The size of sample to create on each iteration.
sampleSize - Variable in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
The sample size requested by the user.
sampleStandard(double, Random) - Static method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Provides a single sample from a Gamma distribution with the given shape and a scale of 1.
sampleTopic(int, int, double[]) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
Samples a topic for a given document and term.
sampleWithoutReplacement(Random, List<DataType>, int) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples a a given number of items from a list without replacement.
sampleWithReplacement(Random, List<? extends DataType>, int) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples a a given number of items from a list with replacement.
sampleWithReplacementInto(Random, List<? extends DataType>, int, Collection<? super DataType>) - Static method in class gov.sandia.cognition.statistics.DiscreteSamplingUtil
Samples a a given number of items from a list with replacement and puts the samples into the given collection.
SamplingImportanceResamplingParticleFilter<ObservationType,ParameterType> - Class in gov.sandia.cognition.statistics.bayesian
An implementation of the standard Sampling Importance Resampling particle filter.
SamplingImportanceResamplingParticleFilter() - Constructor for class gov.sandia.cognition.statistics.bayesian.SamplingImportanceResamplingParticleFilter
Creates a new instance of SamplingImportanceResamplingParticleFilter
saveAsText(File) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
Saves the stop list to the given file.
saveAsText(PrintStream) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
Saves the stop list to the given stream.
saveFinalClustering() - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
Saves the final clustering for each data point.
ScalarBasisSet<InputType> - Class in gov.sandia.cognition.learning.function.vector
Collection of scalar basis functions, where the ith function operates on the ith element of the output Vector
ScalarBasisSet(Collection<? extends Evaluator<? super InputType, Double>>) - Constructor for class gov.sandia.cognition.learning.function.vector.ScalarBasisSet
Creates a new instance of ScalarBasisSet
ScalarBasisSet(ScalarBasisSet<InputType>) - Constructor for class gov.sandia.cognition.learning.function.vector.ScalarBasisSet
Copy Constructor
ScalarDataDistribution - Class in gov.sandia.cognition.statistics.distribution
A Data Distribution that uses Doubles as its keys, making it a univariate distribution
ScalarDataDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution
Creates a new instance of ScalarDataDistribution
ScalarDataDistribution(ScalarDataDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution
Copy constructor
ScalarDataDistribution(Iterable<? extends Number>) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution
Creates a new instance of ScalarDataDistribution
ScalarDataDistribution(Map<Double, MutableDouble>, double) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution
Creates a new instance of ScalarDataDistribution
ScalarDataDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
CDF of the ScalarDataDistribution, maintains the keys/domain in sorted order (TreeMap), so it's slower than it's peers.
ScalarDataDistribution.Estimator - Class in gov.sandia.cognition.statistics.distribution
Estimator for a ScalarDataDistribution
ScalarDataDistribution.PMF - Class in gov.sandia.cognition.statistics.distribution
PMF of the ScalarDataDistribution
ScalarEstimator(BayesianParameter<Double, ? extends ProbabilityFunction<ObservationType>, ? extends UnivariateProbabilityDensityFunction>, Iterable<? extends ObservationType>) - Constructor for class gov.sandia.cognition.statistics.bayesian.RejectionSampling.ScalarEstimator
Creates a new instance of ScalarEstimator
scalarFunction - Variable in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeNode
The function to apply for leaf nodes.
ScalarFunction<InputType> - Interface in gov.sandia.cognition.math
Interface for a function that maps some input onto a double.
ScalarFunctionKernel<InputType> - Class in gov.sandia.cognition.learning.function.kernel
The ScalarFunctionKernel class implements a kernel that applies a scalar function two the two inputs to the kernel and then returns their product.
ScalarFunctionKernel() - Constructor for class gov.sandia.cognition.learning.function.kernel.ScalarFunctionKernel
Creates a new instance of RealFunctionKernel.
ScalarFunctionKernel(Evaluator<? super InputType, Double>) - Constructor for class gov.sandia.cognition.learning.function.kernel.ScalarFunctionKernel
Creates a new instance of RealFunctionKernel.
ScalarFunctionToBinaryCategorizerAdapter<InputType> - Class in gov.sandia.cognition.learning.function.categorization
Adapts a scalar function to be a categorizer using a threshold.
ScalarFunctionToBinaryCategorizerAdapter() - Constructor for class gov.sandia.cognition.learning.function.categorization.ScalarFunctionToBinaryCategorizerAdapter
Creates a new ScalarFunctionToBinaryCategorizerAdapter.
ScalarFunctionToBinaryCategorizerAdapter(Evaluator<? super InputType, Double>) - Constructor for class gov.sandia.cognition.learning.function.categorization.ScalarFunctionToBinaryCategorizerAdapter
Creates a new ScalarFunctionToBinaryCategorizerAdapter with the given evaluator and a default threshold of 0.0.
ScalarFunctionToBinaryCategorizerAdapter(Evaluator<? super InputType, Double>, double) - Constructor for class gov.sandia.cognition.learning.function.categorization.ScalarFunctionToBinaryCategorizerAdapter
Creates a new ScalarFunctionToBinaryCategorizerAdapter with the given evaluator and threshold.
ScalarMap<KeyType> - Interface in gov.sandia.cognition.collection
An interface for a mapping of objects to scalar values represented as doubles.
ScalarMap.Entry<KeyType> - Interface in gov.sandia.cognition.collection
An entry in a scalar map.
ScalarMixtureDensityModel - Class in gov.sandia.cognition.statistics.distribution
ScalarMixtureDensityModel (SMDM) implements just that: a scalar mixture density model.
ScalarMixtureDensityModel() - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
Creates a new instance of ScalarMixtureDensityModel
ScalarMixtureDensityModel(SmoothUnivariateDistribution...) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
Creates a new instance of ScalarMixtureDensityModel
ScalarMixtureDensityModel(Collection<? extends SmoothUnivariateDistribution>) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
Creates a new instance of ScalarMixtureDensityModel
ScalarMixtureDensityModel(Collection<? extends SmoothUnivariateDistribution>, double[]) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
Creates a new instance of ScalarMixtureDensityModel
ScalarMixtureDensityModel(ScalarMixtureDensityModel) - Constructor for class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel
Copy constructor
ScalarMixtureDensityModel.CDF - Class in gov.sandia.cognition.statistics.distribution
CDFof the SMDM
ScalarMixtureDensityModel.EMLearner - Class in gov.sandia.cognition.statistics.distribution
An EM learner that estimates a mixture model from data
ScalarMixtureDensityModel.PDF - Class in gov.sandia.cognition.statistics.distribution
PDF of the SMDM
ScalarThresholdBinaryCategorizer - Class in gov.sandia.cognition.learning.function.categorization
The ScalarThresholdBinaryCategorizer class implements a binary categorizer that uses a threshold to categorize a given double.
ScalarThresholdBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer
Creates a new instance of ScalarThresholdBinaryCategorizer.
ScalarThresholdBinaryCategorizer(double) - Constructor for class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer
Creates a new instance of ScalarThresholdBinaryCategorizer.
ScalarThresholdBinaryCategorizer(ScalarThresholdBinaryCategorizer) - Constructor for class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer
Copy constructor.
scale(double) - Method in class gov.sandia.cognition.math.AbstractRing
 
scale(double) - Method in class gov.sandia.cognition.math.LogNumber
 
scale(double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
scale(double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
scale(double) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
scale(double) - Method in class gov.sandia.cognition.math.MutableDouble
 
scale(double) - Method in class gov.sandia.cognition.math.MutableInteger
 
scale(double) - Method in class gov.sandia.cognition.math.MutableLong
 
scale(double) - Method in interface gov.sandia.cognition.math.Ring
Element-wise scaling of this by scaleFactor
scale(double) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
scale - Variable in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Scale factor to multiply the sampler function by to envelop the conjunctive distribution.
scale - Variable in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Scale, similar to the beta parameter scale, must be greater than zero
scale - Variable in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Scale of the distribution, must be greater than zero.
scale - Variable in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
Scale parameter, must be greater than zero.
scale - Variable in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
Scale factor of the distribution, must be greater than zero.
scale - Variable in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
Scale of the distribution, proportionate to the standard deviation, must be greater than zero.
scale(Matrix) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Scales the MultivariateGaussian by premultiplying by the given Matrix
scale - Variable in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Scale parameter, must be greater than zero.
scale - Variable in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Scale parameter, must be greater than 0.0
SCALE_FACTOR - Static variable in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
Default scale factor on expansion, the golden ratio, 1.618034
scaledMinus(double, RingType) - Method in class gov.sandia.cognition.math.AbstractRing
 
scaledMinus(double, LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
 
scaledMinus(double, InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
scaledMinus(double, MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
scaledMinus(double, MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
scaledMinus(double, MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
scaledMinus(double, RingType) - Method in interface gov.sandia.cognition.math.Ring
Arithmetic subtraction other after element-wise scaling of other by scaleFactor from this.
scaledMinus(double, UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
scaledMinusEquals(double, RingType) - Method in class gov.sandia.cognition.math.AbstractRing
 
scaledMinusEquals(double, LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
 
scaledMinusEquals(double, InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
scaledMinusEquals(double, AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
Subtracts from this matrix the scaled version of the other given matrix.
scaledMinusEquals(double, AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
Subtracts from this vector the scaled version of the other given vector.
scaledMinusEquals(double, MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
scaledMinusEquals(double, MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
scaledMinusEquals(double, MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
scaledMinusEquals(double, RingType) - Method in interface gov.sandia.cognition.math.Ring
Inline arithmetic subtraction of other after element-wise scaling of other by scaleFactor from this.
scaledMinusEquals(double, UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
scaledPlus(double, RingType) - Method in class gov.sandia.cognition.math.AbstractRing
 
scaledPlus(double, LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
 
scaledPlus(double, InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
scaledPlus(double, MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
scaledPlus(double, MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
scaledPlus(double, MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
scaledPlus(double, RingType) - Method in interface gov.sandia.cognition.math.Ring
Arithmetic addition of this and other after element-wise scaling of other by scaleFactor.
scaledPlus(double, UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
scaledPlusEquals(double, ComplexNumber) - Method in class gov.sandia.cognition.math.ComplexNumber
 
scaledPlusEquals(double, LogNumber) - Method in class gov.sandia.cognition.math.LogNumber
 
scaledPlusEquals(double, Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
scaledPlusEquals(double, Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
scaledPlusEquals(SparseMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
scaledPlusEquals(DenseMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
scaledPlusEquals(DiagonalMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
scaledPlusEquals(DenseVector, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
scaledPlusEquals(SparseVector, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
scaledPlusEquals(SparseMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
Type-specific version of scaledPlusEquals for combining whatever type this is with the input sparse matrix.
scaledPlusEquals(DenseMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
Type-specific version of scaledPlusEquals for combining whatever type this is with the input dense matrix.
scaledPlusEquals(DiagonalMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
scaledPlusEquals(SparseMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Type-specific version of scaledPlusEquals for combining whatever type this is with the input sparse matrix.
scaledPlusEquals(DenseMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Type-specific version of scaledPlusEquals for combining whatever type this is with the input dense matrix.
scaledPlusEquals(DiagonalMatrix, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Type-specific version of scaledPlusEquals for combining whatever type this is with the input diagonal matrix.
scaledPlusEquals(DenseVector, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
Type-specific version of scaledPlusEquals for combining whatever type this is with the input dense vector.
scaledPlusEquals(SparseVector, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
scaledPlusEquals(double, InfiniteVector<KeyType>) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
scaledPlusEquals(double, Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
scaledPlusEquals(double, AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
Adds to this vector the scaled version of the other given vector.
scaledPlusEquals(double, Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
 
scaledPlusEquals(double, AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
Adds to this vector the scaled version of the other given vector.
scaledPlusEquals(double, MutableDouble) - Method in class gov.sandia.cognition.math.MutableDouble
 
scaledPlusEquals(double, MutableInteger) - Method in class gov.sandia.cognition.math.MutableInteger
 
scaledPlusEquals(double, MutableLong) - Method in class gov.sandia.cognition.math.MutableLong
 
scaledPlusEquals(double, RingType) - Method in interface gov.sandia.cognition.math.Ring
Inline arithmetic addition of this and other after element-wise scaling of other by scaleFactor.
scaledPlusEquals(double, UnsignedLogNumber) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
scaledPlusEquals(double, RandomVariable<Number>) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
scaleEquals(DefaultKernelBinaryCategorizer<?>, double) - Static method in class gov.sandia.cognition.learning.function.kernel.KernelUtil
Scales all of the weights in the given kernel binary categorizer by the given value.
scaleEquals(double) - Method in class gov.sandia.cognition.math.ComplexNumber
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.LogNumber
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Inline element-wise scaling of this by scaleFactor
scaleEquals(double) - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.MutableDouble
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.MutableInteger
 
scaleEquals(double) - Method in class gov.sandia.cognition.math.MutableLong
 
scaleEquals(double) - Method in interface gov.sandia.cognition.math.Ring
Inline element-wise scaling of this by scaleFactor
scaleEquals(double) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
 
scaleEquals(double) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
scaleSum(double) - Method in class gov.sandia.cognition.math.RingAccumulator
Returns the sum scaled by the given scale factor.
searchForBetter(EvaluatedGenome<GenomeType>, Collection<EvaluatedGenome<GenomeType>>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Searches the provided population of genomes for one whose cost is lower than the provided best so far genome.
SECOND - Static variable in class gov.sandia.cognition.time.DefaultDuration
A second in duration.
second - Variable in class gov.sandia.cognition.util.DefaultPair
The second object.
second - Variable in class gov.sandia.cognition.util.DefaultTriple
The second object.
secondChild - Variable in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.BinaryClusterHierarchyNode
The second child node.
secondLearner - Variable in class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
The second learner that is trained on the output of the evaluator created by the first learner.
SECONDS_PER_MINUTE - Static variable in class gov.sandia.cognition.time.DefaultDuration
There are 60 seconds per minute.
sectioningStep() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
 
sectioningStep() - Method in interface gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizer
Continues the sectioning phase of the algorihtm.
sectioningStep() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
 
sectioningStep() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased
 
sectioningStep() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeFree
 
seedScale - Variable in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
The standard deviation for initializing the factors.
seek(Date) - Method in interface gov.sandia.cognition.data.temporal.SeekableTemporalDataReadChannel
Seeks to the given time in the data.
SeekableTemporalDataReadChannel<DataType extends Temporal> - Interface in gov.sandia.cognition.data.temporal
The SeekableTemporalDataReadChannel interface extends the TemporalDataReadChannel interface to give the ability to seek around in the temporal data based on a time coordinate.
segmentCDF - Variable in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope
Cumulative sums of the normalized weights of the lines...
select(Collection<EvaluatedGenome<GenomeType>>) - Method in interface gov.sandia.cognition.learning.algorithm.genetic.selector.Selector
Selects and returns a portion of the given population.
select(Collection<EvaluatedGenome<GenomeType>>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.selector.TournamentSelector
Uses tournament selection to create a new population.
selectNextClusterIndex(double[], boolean[]) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
Select the index for the next cluster based on the given minimum distances and array indicating which clusters have already been selected.
selectNextClusterIndex(double[], boolean[]) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.DistanceSamplingClusterInitializer
 
selectNextClusterIndex(double[], boolean[]) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.GreedyClusterInitializer
 
Selector<GenomeType> - Interface in gov.sandia.cognition.learning.algorithm.genetic.selector
The Selector interface defines a type of reproducer that can select a portion of a population for reproduction.
selfKernel - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry
This is the value of the kernel applied to the example and itself.
SemanticIdentifier - Interface in gov.sandia.cognition.framework
The SemanticIdentifier class holds a SemanticLabel along with the unique integer that can be used to identify the SemanticLabel within a model.
semanticIdentifierAdded(SemanticIdentifierMapEvent) - Method in interface gov.sandia.cognition.framework.SemanticIdentifierMapListener
This event is triggered when a SemanticIdentifier has been added to the map.
semanticIdentifierMap - Variable in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelConverter
The SemanticIdentifierMap for the converter.
SemanticIdentifierMap - Interface in gov.sandia.cognition.framework
The SemanticIdentifierMap defines the functionality of a class that assigns identifiers to SemanticLabels and keeps track of them.
SemanticIdentifierMapEvent - Class in gov.sandia.cognition.framework
The SemanticIdentifierMapEvent class implements an event object for the SemanticIdentifierMapListener interface to make use of.
SemanticIdentifierMapEvent(SemanticIdentifierMap, SemanticIdentifierMapEventType, SemanticIdentifier) - Constructor for class gov.sandia.cognition.framework.SemanticIdentifierMapEvent
Creates a new instance of CognitiveModelStateChangeEvent.
SemanticIdentifierMapEventType - Enum in gov.sandia.cognition.framework
The SemanticIdentifierMapEventType
SemanticIdentifierMapListener - Interface in gov.sandia.cognition.framework
The SemanticIdentifierMapListener defines an EventListener for the SemanticIdentifierMap.
SemanticLabel - Interface in gov.sandia.cognition.framework
This interface defines what a semantic label should have.
SemanticMemory - Interface in gov.sandia.cognition.framework
The SemanticMemory interface defines the general functionality required of a module in the CognitiveModel that is a semantic memory.
SemanticNetwork - Interface in gov.sandia.cognition.framework
The SemanticNetwork interface defines the functionality required for a network that is used as part of the paramterization to a SemanticMemory.
Semimetric<InputType> - Interface in gov.sandia.cognition.math
A semimetric is a divergence function that takes inputs from the same set (domain) and is positive definite and symmetric.
sequenceGammas - Variable in class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm
The list of all gammas from each sequence
SequencePredictionLearner<DataType,LearnedType> - Class in gov.sandia.cognition.learning.algorithm
A wrapper learner that converts an unlabeled sequence of data into a sequence of prediction data using a fixed prediction horizon.
SequencePredictionLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner
Creates a new SequencePredictionLearner with default parameters.
SequencePredictionLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends DataType, DataType>>, ? extends LearnedType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner
Creates a new SequencePredictionLearner with the given learner and prediction horizon.
SequentialDataMultiPartitioner - Class in gov.sandia.cognition.learning.data
This partitioner splits a Collection of data into a pre-defined number of approximately equal sequential partitions, with the nonzero remainder elements going into the final partition.
SequentialDataMultiPartitioner() - Constructor for class gov.sandia.cognition.learning.data.SequentialDataMultiPartitioner
 
SequentialMinimalOptimization<InputType> - Class in gov.sandia.cognition.learning.algorithm.svm
An implementation of the Sequential Minimal Optimization (SMO) algorithm for training a Support Vector Machine (SVM), which is a kernel-based binary categorizer.
SequentialMinimalOptimization() - Constructor for class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Creates a new instance of Sequential Minimal Optimization.
SequentialMinimalOptimization(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Creates a new instance of Sequential Minimal Optimization with the given kernel.
SequentialMinimalOptimization(Kernel<? super InputType>, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Creates a new instance of Sequential Minimal Optimization with the given kernel and random number generator.
SequentialMinimalOptimization(Kernel<? super InputType>, double, double, double, int, int, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Creates a new instance of Sequential Minimal Optimization with the given kernel and random number generator.
serialize(String, DenseMemoryGraph<?>) - Static method in class gov.sandia.cognition.graph.DenseMemoryGraph
Helper method for serializing the input to file.
serialize(String, WeightedDenseMemoryGraph<?>) - Static method in class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
Helper method for serializing the input to file.
SerializedModelHandler - Class in gov.sandia.cognition.framework.io
The SerializedModelHandler class implements some utility methods for dealing with models that have been serialized using the Java serialization API.
SerializedModelHandler() - Constructor for class gov.sandia.cognition.framework.io.SerializedModelHandler
Creates a new instance of SerializedModelHandler
set(KeyType, double) - Method in class gov.sandia.cognition.collection.AbstractLogNumberMap
 
set(KeyType, double) - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap
 
set(int, double) - Method in class gov.sandia.cognition.collection.DoubleArrayList
Sets the element at idx
set(DataType) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer.InternalIterator
 
set(int, DataType) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
 
set(int, int) - Method in class gov.sandia.cognition.collection.IntArrayList
Sets the element at idx
set(KeyType, double) - Method in interface gov.sandia.cognition.collection.ScalarMap
Sets the value associated with a given key.
set(int, int, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
set(int, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
set(int, int, double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
set(int, int, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Sets the value of the element of the matrix at the zero-based row and column indices.
set(int, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
set(int, int, double) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Sets the value of the element of the matrix at the zero-based row and column indices.
set(int, int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
set(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
 
set(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
 
set(int, double) - Method in interface gov.sandia.cognition.math.matrix.Vector
Sets the value for an element at the zero-based index from the vector.
set(KeyType, double) - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution
 
setA(Matrix) - Method in class gov.sandia.cognition.math.signals.LinearDynamicalSystem
Setter for A.
setAccessedDate(long) - Method in class gov.sandia.cognition.text.document.DefaultDocument
Sets the last accessed date of the document.
setAccessedDate(Date) - Method in class gov.sandia.cognition.text.document.DefaultDocument
Sets the last accessed date of the document.
setActivated(boolean) - Method in class gov.sandia.cognition.framework.lite.BooleanActivatableCogxel
Sets a boolean indicating whether the cogxel is activated.
setActivation(double) - Method in interface gov.sandia.cognition.framework.Cogxel
Sets the activation level of the Cogxel.
setActivation(double) - Method in class gov.sandia.cognition.framework.DefaultCogxel
Sets the activation level of the Cogxel.
setActualCommand(String) - Method in class gov.sandia.cognition.io.ProcessLauncher
Setter for actualCommand
setAggressiveness(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin
Sets the aggressiveness parameter (C), which is the trade-off between aggressive updating to meet an incorrect example and keeping history around.
setAlgorithm(InternalAlgorithm) - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
Sets the underlying algorithm.
setAll(Iterable<? extends KeyType>, double) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
setAll(ScalarMap<? extends KeyType>) - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
setAll(Iterable<? extends KeyType>, double) - Method in interface gov.sandia.cognition.collection.ScalarMap
Sets all the given keys to the given value.
setAll(ScalarMap<? extends KeyType>) - Method in interface gov.sandia.cognition.collection.ScalarMap
Sets all the given keys to the given value.
setAllowedTerms(Set<Term>) - Method in class gov.sandia.cognition.text.term.filter.DictionaryFilter
Sets the set of allowed terms.
setAlpha(double) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
Setter for alpha
setAlpha(double) - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution
Setter for alpha
setAlpha(double) - Method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Setter for alpha.
setAlpha(double) - Method in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment
Setter for alpha
setAlpha(double) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
Sets the alpha parameter controlling the Dirichlet distribution for the document-topic probabilities.
setAlphabet(char[]) - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector.Learner
Sets the alphabet of lower-case characters that can be used for replaces and inserts.
setAlphabet(char[]) - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Sets the alphabet of lower-case characters that can be used for replaces and inserts.
setAmplitude(double) - Method in class gov.sandia.cognition.learning.function.scalar.CosineFunction
Setter for amplitude
setAreaUnderCurve(double) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Setter for areaUnderCurve
setAssignment(int, int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Sets the assignment of the given element to the new cluster index, updating the cluster counts as well.
setAssignments(int[]) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the assignments of examples to exemplars (clusters).
setAssociation(SemanticLabel, SemanticLabel, double) - Method in class gov.sandia.cognition.framework.DefaultSemanticNetwork
Sets the association between two nodes in the network.
setAssociation(SemanticLabel, SemanticLabel, double) - Method in interface gov.sandia.cognition.framework.lite.MutablePatternRecognizerLite
Sets the association between nodes in the recognizer.
setAssociation(SemanticLabel, SemanticLabel, double) - Method in class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLite
Sets the association between nodes in the recognizer.
setAssociation(SemanticLabel, SemanticLabel, double) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Sets the association between nodes in the recognizer.
setAuthor(String) - Method in class gov.sandia.cognition.text.document.DefaultDocument
Sets the author field of the document to the given string.
setAutoregressiveCoefficients(Vector) - Method in class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
Setter for autoregressiveCoefficients
setAvailabilities(double[][]) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the availability values.
setAverager(Summarizer<? super OutputType, ? extends OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor
Setter for averager
setAverager(Summarizer<? super OutputType, ? extends OutputType>) - Method in interface gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighbor
Setter for averager.
setB(Matrix) - Method in class gov.sandia.cognition.math.signals.LinearDynamicalSystem
Setter for B.
setBag(ArrayList<InputOutputPair<? extends InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Sets the most recently created bag.
setBaseHandler(StreamSerializationHandler<SerializedType>) - Method in class gov.sandia.cognition.io.serialization.GZIPSerializationHandler
Sets the base handler whose output is serialized.
setBasisFunctions(ArrayList<? extends Evaluator<? super InputType, ? extends OutputType>>) - Method in class gov.sandia.cognition.learning.function.LinearCombinationFunction
Setter for basisFunctions
setBasisFunctions(Collection<? extends Evaluator<? super InputType, Double>>) - Method in class gov.sandia.cognition.learning.function.vector.ScalarBasisSet
Setter for basisFunctions
setBestSoFar(AnnealedType) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the best state found so far.
setBestSoFar(EvaluatedGenome<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Sets the best genome found so far.
setBestSoFarScore(double) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the score for the best state found so far.
setBeta(double) - Method in class gov.sandia.cognition.statistics.distribution.BetaDistribution
Setter for beta
setBeta(double) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
Sets the beta parameter controlling the Dirichlet distribution for the topic-term probabilities.
setBias(double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AdditiveEnsemble
Sets the initial offset value (bias) to which the output of the ensemble members are added when computing a result.
setBias(double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAdditiveEnsemble
Sets the initial offset value (bias) to which the output of the ensemble members are added when computing a result.
setBias(double) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
Sets the bias value.
setBias(double) - Method in class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
Sets the bias term.
setBias(double) - Method in class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer
Sets the bias term.
setBias(double) - Method in class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction
Sets the bias term.
setBias(double) - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminantWithBias
Setter for bias.
setBias(double) - Method in class gov.sandia.cognition.learning.function.scalar.LinearVectorScalarFunction
Sets the bias term.
setBias(Vector) - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminantWithBias
Setter for bias
setBiasEnabled(boolean) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
Sets whether or not the bias term is enabled.
setBiasRegularization(double) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
Sets the value for the parameter controlling the bias regularization.
setBlockExperimentComparison(BlockExperimentComparison<Number>) - Method in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment
Setter for blockExperimentComparison
setBody(String) - Method in class gov.sandia.cognition.text.document.DefaultDocument
Sets the body field of the document to the given string.
setBooleanConverter(DataToVectorEncoder<Boolean>) - Method in class gov.sandia.cognition.data.convert.vector.UniqueBooleanVectorEncoder
Sets the boolean converter used to encode the equality comparison between each of the unique values and a given input.
setBounds(Rectangle2D.Double) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the bounding box of the region represented by this node.
setBracket(LineBracket) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Setter for bracket
setBracket(LineBracket) - Method in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
Setter for bracket.
setBracketer(RootBracketer) - Method in class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder
Gets the root-bracketing algorithm that will be used to initially bracket the root.
setBudget(int) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineBudgetedKernelBinaryCategorizerLearner
Sets the budget.
setBudget(int) - Method in interface gov.sandia.cognition.learning.algorithm.perceptron.kernel.BudgetedKernelBinaryCategorizerLearner
Sets the budget.
setBufferedReader(BufferedReader) - Method in class gov.sandia.cognition.io.ReaderTokenizer
Setter for bufferedReader
setBurnInIterations(int) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
 
setBurnInIterations(int) - Method in interface gov.sandia.cognition.statistics.bayesian.MarkovChainMonteCarlo
Sets the number of iterations that must transpire before the algorithm begins collection the samples.
setBurnInIterations(int) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
Sets he number of burn-in iterations for the Markov Chain Monte Carlo algorithm to run before sampling begins.
setC(Matrix) - Method in class gov.sandia.cognition.math.signals.LinearDynamicalSystem
Setter for C.
setCapacity(int) - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
Sets the capacity of the buffer, which is the maximum number of elements that can be stored in it.
setCapacity(int) - Method in class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
Setter for capacity
setCategories(Set<OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTree
Sets the possible output categories.
setCategories(Set<CategoryType>) - Method in class gov.sandia.cognition.learning.function.categorization.AbstractCategorizer
Sets the Set of possible categories, which are the output values.
setCategories(Set<CategoryType>) - Method in class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter
 
setCategories(Set<CategoryType>) - Method in class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer
 
setCategorizedVector(Vector) - Method in class gov.sandia.cognition.statistics.ChiSquaredSimilarity
Basic setter for the categorized vector.
setCategorizer(Categorizer<? super IntermediateType, ? extends CategoryType>) - Method in class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer
Sets the categorizer, which takes the output of the preprocessor and categorizes it.
setCategorizers(Collection<BinaryCategorizer<? super InputType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BinaryCategorizerSelector
Gets the collection of categorizers that the learner selects from.
setCategoryPairsToEvaluatorMap(Map<Pair<CategoryType, CategoryType>, Evaluator<? super InputType, Boolean>>) - Method in class gov.sandia.cognition.learning.function.categorization.BinaryVersusCategorizer
Sets the mapping of false-true category pairs to the binary categorizer that distinguishes them.
setCategoryPriors(Map<OutputType, Double>) - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
Set prior category probabilities.
setCDF(CumulativeDistributionFunction<Double>) - Method in class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
Setter for cdf
setCenterData(boolean) - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
Sets whether or not the data needs to be centered in the kernel space before applying the function.
setCenterData(boolean) - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
Sets whether or not the data needs to be centered in the kernel space before applying the algorithm.
setCentralValue(double) - Method in class gov.sandia.cognition.statistics.method.ConfidenceInterval
Setter for centralValue
setCentroid(ClusterType) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster
Sets the centroid of the cluster.
setChangedCount(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the number of cluster assignments that have changed in the most recent iteration.
setChildMap(Map<InteriorType, DecisionTreeNode<InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
Sets the mapping of decision values to child nodes.
setChildren(List<ClusterHierarchyNode<DataType, ClusterType>>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode
Sets the children of this node.
setChildren(ClusterHierarchyNode<DataType, ClusterType>, ClusterHierarchyNode<DataType, ClusterType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode
Sets the children of this node.
setChildren(ArrayList<Quadtree<DataType>.Node>) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the list of child nodes of this node.
setChildrenDivergence(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer.HierarchyNode
Sets the divergence between the two children.
setChiSquare(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter for chiSquare
setClassifier(ScalarThresholdBinaryCategorizer) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.DataPoint
Setter for classifier
setCluster(ClusterType) - Method in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.AbstractClusterHierarchyNode
Sets the cluster associated with the node.
setClusterCount(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the number of clusters.
setClusters(HashMap<Integer, CentroidCluster<DataType>>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the current clusters, which is a sparse mapping of exemplar identifier to cluster object.
setClusters(ArrayList<ClusterType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Sets the clusters.
setClusters(ArrayList<ClusterType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the current clusters, which is a sparse mapping of exemplar identifier to cluster object.
setClusters(ArrayList<ClusterType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Sets the clusters.
setClusters(ArrayList<ClusterType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the clusters cache to the provided value.
setClusters(ArrayList<DirichletProcessMixtureModel.DPMMCluster<ObservationType>>) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
Setter for clusters
setClustersHierarchy(ArrayList<AgglomerativeClusterer.HierarchyNode<DataType, ClusterType>>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Sets the hierarchy of clusters.
setClustersHierarchy(ArrayList<BinaryClusterHierarchyNode<DataType, ClusterType>>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the hierarchy of clusters.
setCoefficients(Vector) - Method in class gov.sandia.cognition.learning.function.LinearCombinationFunction
Setter for coefficients
setCognitiveState(CognitiveModelLiteState) - Method in class gov.sandia.cognition.framework.lite.AbstractCognitiveModelLite
Sets the cognitive state to the given state.
setCogxelFactory(CogxelFactory) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
Gets the CogxelFactory used to create the cogxels used by the converter.
setCogxelFactory(CogxelFactory) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Gets the CogxelFactory used to create the Cogxels used by the converter.
setCogxelFactory(CogxelFactory) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Gets the CogxelFactory used to create the Cogxels used by the converter.
setCogxelFactory(CogxelFactory) - Method in class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModule
Sets the cogxel factory to use.
setCogxelFactory(CogxelFactory) - Method in class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModule
Setter for cogxelFactory
setCogxelFactory(CogxelFactory) - Method in class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModuleFactory
Setter for cogxelFactory
setCogxels(CogxelStateLite) - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Setter for cogxels
setCogxelVectorConverters(Collection<CogxelVectorConverter>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter
Setter for cogxelVectorConverters
setColumn(int, Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
setColumn(int, Vector) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Sets the specified column from the given columnVector
setColumn(int, SparseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix
Sets the column of the matrix using the given SparseVector, using MTJ's internal routine to speed things up
setColumnConverters(ArrayList<CogxelVectorConverter>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter
Setter for columnConverters
setColumnIndex(int) - Method in interface gov.sandia.cognition.math.matrix.MatrixEntry
Sets the column index to which the entry points
setColumnIndex(int) - Method in class gov.sandia.cognition.math.matrix.mtj.TwoMatrixEntryMTJ
Setter for columnIndex.
setColumnIndex(int) - Method in interface gov.sandia.cognition.math.matrix.TwoMatrixEntry
Sets the column index to which the entry points
setComponentCount(int) - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
Gets the number of components the analysis attempts to find.
setComponents(Matrix) - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
Sets the matrix of components from the analysis.
setConditionalDistribution(ConditionalType) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter
Setter for conditionalDistribution
setConditionalDistribution(ConditionalType) - Method in class gov.sandia.cognition.statistics.DefaultDistributionParameter
Setter for conditionalDistribution
setConditionalLearner(BatchLearner<Collection<? extends ObservationType>, ? extends ComputableDistribution<ObservationType>>) - Method in class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer.Learner
Setter for conditionalLearner
setConditionals(Map<CategoryType, List<DistributionType>>) - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer
Sets the conditional distributions, which is a mapping of category to the list of probability density functions, one for each dimension of the vector.
setConfidence(double) - Method in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
Gets the confidence to use for updating.
setConfidence(double) - Method in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
Gets the confidence to use for updating.
setConfidence(ConfidenceStatistic) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment.Result
Sets the confidence statistic for the learners.
setConfidence(ConfidenceStatistic) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
Sets the confidence statistic that the two learners are different.
setConfidence(double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Setter for confidence
setConfidence(double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval.Summary
Sets the confidence for created the interval.
setConfidence(double) - Method in class gov.sandia.cognition.statistics.method.ConfidenceInterval
Setter for confidence
setConfidence(double) - Method in class gov.sandia.cognition.statistics.method.StudentTConfidence.Summary
Sets the confidence for created the interval.
setConfusionMatrix(DefaultBinaryConfusionMatrix) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.DataPoint
Setter for confusionMatrix
setConjuctive(BayesianParameter<ParameterType, ? extends ProbabilityFunction<ObservationType>, ? extends ProbabilityFunction<ParameterType>>) - Method in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater
Setter for conjunctive
setConjuctive(BayesianParameter<ParameterType, ? extends ProbabilityFunction<ObservationType>, ? extends ProbabilityFunction<ParameterType>>) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Setter for conjunctive
setConstant(double) - Method in class gov.sandia.cognition.learning.function.kernel.PolynomialKernel
Gets the constant of the polynomial.
setConstant(double) - Method in class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
Sets the constant inside of the sigmoid kernel.
setConstantValue(double) - Method in class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction
Sets the constant value.
setConstantWeight(double) - Method in class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction
Sets the constant weight.
setConstructor(Constructor<? extends CreatedType>) - Method in class gov.sandia.cognition.factory.ConstructorBasedFactory
Sets the constructor to use to create new objects.
setConverter(DataConverter<? super InputType, ? extends Number>) - Method in class gov.sandia.cognition.data.convert.vector.NumberConverterToVectorAdapter
Sets the number converter being adapted to work with vectors.
setConverter(SingleTextualConverter<? super InputType, ? extends OutputType>) - Method in class gov.sandia.cognition.text.convert.SingleToMultiTextualConverterAdapter
Sets the internal single textual converter being wrapped.
setConvexHull(ArrayList<ReceiverOperatingCharacteristic.DataPoint>) - Method in class gov.sandia.cognition.statistics.method.ConvexReceiverOperatingCharacteristic
Setter for convexHull
setCoolingFactor(double) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the cooling factor.
setCost(double) - Method in class gov.sandia.cognition.learning.algorithm.genetic.EvaluatedGenome
Sets the cost of the genome.
setCostFunction(CostFunction<? super AnnealedType, ? super CostParametersType>) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the cost function.
setCostFunction(CostFunction<? super GenomeType, ? super CostParametersType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Sets the cost function.
setCostFunction(SupervisedCostFunction<Vector, Vector>) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
Setter for costFunction
setCostFunction(CostFunctionType) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Setter for costFunction
setCostFunction(ParallelizableCostFunction) - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer
Setter for costFunction
setCostParameters(CostParametersType) - Method in class gov.sandia.cognition.learning.function.cost.AbstractCostFunction
 
setCostParameters(Collection<? extends InputOutputPair<? extends InputType, TargetType>>) - Method in class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction
 
setCostParameters(ClusterDivergenceFunction<? super ClusterType, ? super DataType>) - Method in class gov.sandia.cognition.learning.function.cost.ClusterDistortionMeasure
 
setCostParameters(CostParametersType) - Method in interface gov.sandia.cognition.learning.function.cost.CostFunction
Sets the parameters of the cost function used to evaluate the cost of a target.
setCostParameters(Vectorizable) - Method in class gov.sandia.cognition.learning.function.cost.EuclideanDistanceCostFunction
 
setCostParameters(Collection<? extends InputOutputPair<? extends Vector, Vector>>) - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer
 
setCount(long) - Method in class gov.sandia.cognition.statistics.AbstractSufficientStatistic
Setter for count
setCounterFactory(Factory<? extends DataDistribution<CategoryType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Sets the factory used for creating the object for counting the votes of the learned ensemble members.
setCovariance(Matrix) - Method in class gov.sandia.cognition.learning.algorithm.annealing.VectorizablePerturber
Sets the covariance of the perturber.
setCovariance(Matrix) - Method in class gov.sandia.cognition.learning.function.categorization.DefaultConfidenceWeightedBinaryCategorizer
Sets the covariance matrix.
setCovariance(Matrix) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Sets the covariance matrix.
setCovariance(Matrix, double) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Sets the covariance matrix.
setCovarianceDivisor(double) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
Setter for covarianceDivisor
setCovarianceInverse(Matrix) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Sets the covariance inverse
setCovarianceInverse(Matrix, double) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Sets the covariance inverse
setCovarianceSqrt(Matrix) - Method in class gov.sandia.cognition.learning.algorithm.annealing.VectorizablePerturber
Sets the covariance square root matrix.
setCreatedClass(Class<? extends CreatedType>) - Method in class gov.sandia.cognition.factory.DefaultFactory
Sets the class whose default constructor is used to create new objects.
setCreator(ClusterCreator<ClusterType, DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Sets the cluster creator.
setCreator(ClusterCreator<ClusterType, DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the cluster creator.
setCreator(KDTree<DataType, Double, InputOutputPair<DataType, Double>>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the spatial index.
setCreator(ClusterCreator<ClusterType, DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
Sets the cluster creator used to create the initial clusters.
setCreator(ClusterCreator<ClusterType, DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Sets the cluster creator.
setCreator(IncrementalClusterCreator<ClusterType, DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the cluster creator.
setCrossoverFunction(CrossoverFunction<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.CrossoverReproducer
Sets the CrossoverFunction.
setCurrent(AnnealedType) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the current state of the system.
setCurrentInput(Vector) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
Setter for currentInput
setCurrentLine(String) - Method in class gov.sandia.cognition.io.ProcessLauncherEvent
Setter for currentLine
setCurrentParameter(ParameterType) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
Setter for currentParameter.
setCurrentScore(double) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the score of the current state.
setCurvatureCondition(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions
Setter for curvatureCondition
setD(double) - Method in class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence.Statistic
Setter for D
setDampingFactor(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the damping factor.
setDampingFactor(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
Setter for dampingFactor
setDampingFactorDivisor(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
Setter for dampingFactorDivisor
setDampingFactorDivisor(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
Setter for dampingFactorDivisor
setData(DataType) - Method in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
Gets the data to use for learning.
setData(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
 
setData(Collection<? extends Vector>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
Set the data to be clustered.
setData(EvaluatorType) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
 
setData(Collection<InputOutputPair<? extends InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive
Setter for data
setData(KDTree<InputType, OutputType, InputOutputPair<? extends InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree
Setter for data
setData(LinkedList<InputOutputPair<? extends InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborExhaustive
Sets the data that the object performs nearest-neighbor lookup on.
setData(KDTree<InputType, OutputType, InputOutputPair<? extends InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree
Setter for data
setData(List<? extends DataType>) - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
Sets the data that was used in the analysis.
setDataInBag(int[]) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Sets the array of counts of the number of samples of each example in the current bag.
setDataList(ArrayList<? extends InputOutputPair<? extends InputType, OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Sets the data the learner is using as an array list.
setDate(Date) - Method in class gov.sandia.cognition.text.document.DefaultDateField
Sets the date stored in the field.
setDecider(Categorizer<? super InputType, ? extends InteriorType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
Sets the decider used at this node.
setDeciderLearner(DeciderLearner<? super InputType, OutputType, ?, ?>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner
Sets the learner for the decision function.
setDefaultCovariance(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianClusterCreator
Setter for defaultCovariance
setDefaultCovariance(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.NeighborhoodGaussianClusterInitializer
Setter for defaultCovariance
setDefaultCovariance(double) - Method in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.DiagonalCovarianceLearner
Sets the default covariance value.
setDefaultCovariance(double) - Method in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.FullCovarianceLearner
Sets the default covariance value.
setDefaultCovariance(double) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator
Setter for defaultCovariance
setDefaultCovariance(double) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
Setter for defaultCovariance
setDefaultCovariance(double) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
Setter for defaultCovarianceInverse
setDefaultCovarianceInverse(double) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimatorCovarianceInverse
Setter for defaultCovarianceInverse
setDefaultNumThreads(int) - Static method in class gov.sandia.cognition.algorithm.ParallelUtil
Sets the current default number of threads to use when calling the default createThreadPool() method
setDefaultVariance(double) - Method in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation
Sets the default variance, which the diagonal of the covariance matrix is initialized to.
setDefaultVariance(double) - Method in class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance
Sets the default variance, which the diagonal of the covariance matrix is initialized to.
setDefaultVariance(double) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.IncrementalEstimator
Sets the default variance, which is the amount added to the variance.
setDefaultVariance(double) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.MaximumLikelihoodEstimator
Sets the default variance, which is the amount added to the variance.
setDegree(int) - Method in class gov.sandia.cognition.learning.function.kernel.PolynomialKernel
Sets the degree of the polynomial.
setDegreesOfFreedom(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter for degreesOfFreedom
setDegreesOfFreedom(double) - Method in class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution
Setter for degrees of freedom
setDegreesOfFreedom(int) - Method in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
Setter for degreesOfFreedom
setDegreesOfFreedom(double) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
Setter for degreesOfFreedom
setDegreesOfFreedom(double) - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Setter for degreesOfFreedom
setDegreesOfFreedom(double) - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Setter for degreesOfFreedom
setDegreesOfFreedom(double) - Method in class gov.sandia.cognition.statistics.method.StudentTConfidence.Statistic
Setter for degreesOfFreedom
setDelaySamples(int) - Method in class gov.sandia.cognition.learning.data.feature.DelayFunction
Setter for delaySamples
setDelta(double) - Method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator
Setter for delta
setDeltaSize(double) - Method in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
Setter for deltaSize
setDemoteToZero(boolean) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
Sets whether or not the algorithm will demote features involved in an incorrect categorization to zero (Winnow1).
setDepth(int) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the depth in the tree of this node.
setDerivativeGain(double) - Method in class gov.sandia.cognition.math.signals.PIDController
Setter for derivativeGain
setDFbetween(double) - Method in class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay.Statistic
Setter for DFbetween
setDFwithin(double) - Method in class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay.Statistic
Setter for DFwithin
setDimensionReducer(MultivariateDiscriminant) - Method in class gov.sandia.cognition.learning.algorithm.pca.PrincipalComponentsAnalysisFunction
Setter for dimensionReducer
setDimensionsToConsider(int...) - Method in interface gov.sandia.cognition.learning.algorithm.DimensionFilterableLearner
Gets the dimensions that the learner is to consider.
setDimensionsToConsider(int...) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
 
setDimensionsToConsider(int...) - Method in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
 
setDimensionsToConsider(int...) - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdVarianceLearner
 
setDirection(Vector) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
Setter for direction
setDiscriminant(DiscriminantType) - Method in class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair
Sets the discriminant.
setDiscriminant(LinearDiscriminant) - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionLinearDiscriminant
Setter for discriminant
setDiscriminant(MultivariateDiscriminant) - Method in class gov.sandia.cognition.learning.function.vector.GeneralizedLinearModel
Setter for discriminant
setDiscriminant(Matrix) - Method in class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant
Setter for discriminant
setDistribution(UnivariateDistribution<? extends Number>) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
Setter for distribution
setDistributionEstimator(DistributionEstimator<? super Double, ? extends DistributionType>) - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.Learner
Sets the estimation method for the distribution of each dimension of each category.
setDistributionLearner(IncrementalLearner<? super Double, DistributionType>) - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.OnlineLearner
Sets the learner used for the distribution representing each dimension.
setDistributionLearner(BatchLearner<Collection<? extends WeightedValue<? extends ObservationType>>, ? extends ComputableDistribution<ObservationType>>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
Setter for distributionLearner
setDistributions(ArrayList<? extends DistributionType>) - Method in class gov.sandia.cognition.statistics.distribution.LinearMixtureModel
Setter for distributions
setDistributions(Collection<? extends ClosedFormComputableDistribution<DataType>>) - Method in class gov.sandia.cognition.statistics.method.MaximumLikelihoodDistributionEstimator
Setter for distributions
setDivergence(DivergenceFunction<? super DataType, ? super DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the divergence function used by the algorithm.
setDivergenceFunction(ClusterToClusterDivergenceFunction<? super ClusterType, ? super DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Sets the divergence function.
setDivergenceFunction(ClusterDivergenceFunction<? super ClusterType, ? super DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Sets the divergence function.
setDivergenceFunction(DivergenceFunction<? super ClusterType, ? super DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Use a metric between a cluster and a point to update the metric on clusters.
setDivergenceFunction(DivergenceFunction<? super InputType, ? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree
 
setDivergenceFunction(Metric<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree
Sets the Metric to use.
setDivergenceFunction(DivergenceFunction<? super InputType, ? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree
 
setDivergenceFunction(Metric<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree
Sets the Metric to use.
setDivergenceFunction(DivergenceFunction<? super FirstType, ? super SecondType>) - Method in class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer
Sets the divergence function used by this object.
setDivergenceFunction(DivergenceFunction<? super ValueType, ? super InputType>) - Method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator.Learner
Sets the divergence function to use from the values to the inputs.
setDivergenceFunction(DivergenceFunction<? super ValueType, ? super InputType>) - Method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
Sets the divergence function to use from the values to the inputs.
setDocumentCount(int) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
Sets the document count.
setDocumentTopicProbabilities(double[][]) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler.Result
Sets the topic-term probabilities, which are the often called the phi model parameters.
setDominance(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.DominanceGlobalTermWeighter
Sets the cached dominance weight vector.
setDPrime(double) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Setter for dPrime
setEffectiveZero(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Sets the effective value for zero to use in the computation to deal with numerical imprecision.
setEffectiveZero(double) - Method in class gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator
Sets the value to treat as zero.
setEigenDecomposition(ComplexNumber[], Matrix, Matrix, boolean) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
Sets the eigen decomposition for this
setEigenValues(ComplexNumber[]) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
setter for eigenValues
setEigenVectorsImaginaryPart(Matrix) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
setter for the imaginary part of the eienvector, where the ith eigenvector is the ith column
setEigenVectorsRealPart(Matrix) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
setter for eigenVectorsRealPart, where the ith eigenvector is the ith column
setElement(int, int, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
setElement(int, double) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
setElement(int, int, double) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
Set the value stored at the input locations to the input value
setElement(int, int, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Sets the Matrix element at the specified zero-based indices throws ArrayIndexOutOfBoundsException if either rowIndex or columnIndex are less than 0, or greater than the number of rows (columns) minus one (0 <= index <= num-1)
setElement(int, double) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
setElement(int, double) - Method in interface gov.sandia.cognition.math.matrix.DiagonalMatrix
Sets the zero-based index diagonal element into the diagonal matrix
setElement(int, int, double) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Sets the Matrix element at the specified zero-based indices throws ArrayIndexOutOfBoundsException if either rowIndex or columnIndex are less than 0, or greater than the number of rows (columns) minus one (0 <= index <= num-1)
setElement(int, int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
setElement(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
 
setElement(int, int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix
 
setElement(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
 
setElement(int, int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
setElement(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
setElement(int, double) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
 
setElement(int, double) - Method in interface gov.sandia.cognition.math.matrix.Vector
Sets the zero-based indexed element in the Vector from the specified value
setElements(Quaternion) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets the elements of this quaternion equal to the elements of the given quaternion.
setElementsScore(int, int, double, double) - Method in class gov.sandia.cognition.learning.algorithm.semisupervised.valence.MultipartiteValenceMatrix
Sets elements of the group with their score (+1/-1 or similar) and how much to trust that weight.
setEmissionFunctions(Collection<? extends ComputableDistribution<ObservationType>>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Setter for emissionFunctions.
setEnsemble(EnsembleType) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Sets the ensemble created by this learner.
setEnsemble(WeightedBinaryEnsemble<InputType, Evaluator<? super InputType, ? extends Boolean>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
Sets the ensemble created by this learner.
setEnsembleSize(int) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
Sets the size of the ensemble to create.
setEntries(ArrayList<SuccessiveOverrelaxation<InputType>.Entry>) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Gets the data that the algorithm keeps for each training instance.
setEntropy(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.EntropyGlobalTermWeighter
Sets the cached entropy weight vector.
setErrorCount(int) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
Sets the error count of the most recent iteration.
setErrorCount(long) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Result
Sets the error count.
setErrorCount(int) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
Sets the error count of the most recent iteration.
setErrorCount(int) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
Sets the error count of the most recent iteration.
setErrorCount(long) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron.LinearResult
Sets the error count.
setErrorCount(int) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
Sets the error count of the most recent iteration.
setErrorCount(int) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
Sets the error count of the most recent iteration.
setErrorTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Sets the error tolerance for the algorithm.
setErrSum(double) - Method in class gov.sandia.cognition.math.signals.PIDController.State
Setter for errSum
setEstimate(EstimateType) - Method in class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
Sets the estimate, which is the prediction or guess.
setEstimateConverter(CogxelConverter<EstimateType>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter
Sets the converter for the estimate value.
setEta(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron
Sets the eta parameter that controls how many supports are allowed.
setEvaluator(Evaluator<? super InputType, ? extends OutputType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleSettings
Sets the evaluator to be used by the module.
setEvaluator(Evaluator<? super InputType, ? extends CategoryType>) - Method in class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter
Sets the evaluator that is to be adapted to be a categorizer.
setEvaluator(Evaluator<? super InputType, Double>) - Method in class gov.sandia.cognition.learning.function.categorization.ScalarFunctionToBinaryCategorizerAdapter
Sets the scalar function that the adapter wraps.
setEvaluator(Evaluator<? super InputType, ? extends Vectorizable>) - Method in class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer
Sets the wrapped evaluator.
setEvaluator(Evaluator<String, String>) - Method in class gov.sandia.cognition.text.term.filter.StringEvaluatorSingleTermFilter
Sets the evaluator being used as a filter.
setEvaluators(Collection<? extends Evaluator<?, ?>>) - Method in class gov.sandia.cognition.evaluator.CompositeEvaluatorList
Sets the list of evaluators to compose together.
setEvaluators(Evaluator<?, ?>...) - Method in class gov.sandia.cognition.evaluator.CompositeEvaluatorList
Sets the array of evaluators to compose together.
setEventType(SemanticIdentifierMapEventType) - Method in class gov.sandia.cognition.framework.SemanticIdentifierMapEvent
Sets the type of the event.
setExamples(ArrayList<DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the array list of examples to cluster.
setExamples(Collection<EntryType>) - Method in class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
Sets the list of weighted examples that categorizer is using.
setExamples(Collection<? extends WeightedValue<? extends InputType>>) - Method in class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction
Sets the list of weighted examples that categorizer is using.
setExponent(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction
Setter for exponent
setF(double) - Method in class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay.Statistic
Setter for F
setFactorCount(int) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
Sets the number of factors.
setFactorRegularization(double) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
Sets the value for the parameter controlling the factor matrix regularization.
setFactors(Matrix) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
Sets the matrix of factors.
setFactory(Factory<? extends ConfusionMatrix<CategoryType>>) - Method in class gov.sandia.cognition.learning.performance.categorization.ConfusionMatrixPerformanceEvaluator
Sets the factory for the confusion matrix the evaluator creates.
setFalseNegativesCount(double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Sets the number of false negatives in the matrix.
setFalseNegativesRate(ConfidenceInterval) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Setter for falseNegativesRate
setFalsePositivesCount(double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Sets the number of false positives in the matrix.
setFalsePositivesRate(ConfidenceInterval) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Setter for falsePositivesRate
setFalseValue(Number) - Method in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
Sets the number that represents a falue value.
setField(Field) - Method in class gov.sandia.cognition.statistics.method.FieldConfidenceInterval
Setter for field
setFieldMap(HashMap<String, Field>) - Method in class gov.sandia.cognition.text.document.AbstractDocument
Sets the mapping of field name to the field.
setFieldName(String) - Method in class gov.sandia.cognition.text.convert.DocumentSingleFieldConverter
Sets the name of the field to extract.
setFieldNames(List<String>) - Method in class gov.sandia.cognition.text.convert.DocumentFieldConcatenator
Sets the list of field names whose text are to be concatenated together.
setFieldSeparator(String) - Method in class gov.sandia.cognition.text.convert.DocumentFieldConcatenator
Sets the string used as a separator between field text values.
setFirst(FirstType) - Method in class gov.sandia.cognition.util.DefaultPair
Sets the first object.
setFirst(FirstType) - Method in class gov.sandia.cognition.util.DefaultTriple
Sets the first object.
setFirstChild(ClusterHierarchyNode<DataType, ClusterType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.BinaryClusterHierarchyNode
Sets the first child node.
setFirstConverter(CogxelConverter<FirstType>) - Method in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
Setter for firstConverter
setFirstInternalEntry(MatrixEntry) - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
setter for firstInternalEntry
setFirstInternalEntry(VectorEntry) - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
setter for firstInternalEntry
setFirstIterator(Iterator<MatrixEntry>) - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
setter for firstInterator
setFirstIterator(Iterator<VectorEntry>) - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
setter for firstIterator
setFirstLearner(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends IntermediateType>>) - Method in class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
Sets the first learner that is applied to the input data.
setFirstMatrix(AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.TwoMatrixEntryMTJ
Setter for firstMatrix.
setFirstValue(double) - Method in class gov.sandia.cognition.math.matrix.DefaultTwoVectorEntry
Sets the entry value to the first underlying vector.
setFirstValue(double) - Method in class gov.sandia.cognition.math.matrix.mtj.TwoMatrixEntryMTJ
Sets the first value of the entry into the first underlying matrix.
setFirstValue(double) - Method in interface gov.sandia.cognition.math.matrix.TwoMatrixEntry
Sets the first value to which this entry points
setFirstValue(double) - Method in interface gov.sandia.cognition.math.matrix.TwoVectorEntry
Sets the first value to which this entry points
setFirstVector(Vector) - Method in class gov.sandia.cognition.math.matrix.DefaultTwoVectorEntry
Setter for firstVector.
setFoldCreator(ValidationFoldCreator<InputDataType, FoldDataType>) - Method in class gov.sandia.cognition.learning.experiment.AbstractValidationFoldExperiment
Sets the fold creator.
setForward(ForwardType) - Method in class gov.sandia.cognition.evaluator.ForwardReverseEvaluatorPair
Sets the forward evaluator that maps input type to output type.
setFractionValue(double) - Method in class gov.sandia.cognition.math.LentzMethod
Setter for fractionValue
setFrequency(double) - Method in class gov.sandia.cognition.learning.function.scalar.CosineFunction
Setter for frequency
setFunction(VectorizableVectorFunction) - Method in class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator
Setter for function
setFunction(Evaluator<? super InputType, Double>) - Method in class gov.sandia.cognition.learning.function.kernel.ScalarFunctionKernel
Sets the scalar function for the kernel to use.
setFunction(VectorFunction) - Method in class gov.sandia.cognition.learning.function.kernel.VectorFunctionKernel
Sets the vector function for the kernel to use.
setFunction(EvaluatorType) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LogEvaluator
Setter for function
setGammas(ArrayList<Vector>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask
Sets the gamma samples pointer.
setGaussian(MultivariateGaussian.PDF) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianCluster
Sets the Gaussian representing the cluster.
setGaussian(MultivariateGaussian) - Method in class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator
Sets the underlying multivariate Gaussian.
setGaussian(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
Setter for gaussian
setGaussian(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
Setter for gaussian
setGaussianMixture(MixtureOfGaussians.PDF) - Method in class gov.sandia.cognition.learning.function.vector.GaussianContextRecognizer
Setter for gaussianMixture
setGenome(GenomeType) - Method in class gov.sandia.cognition.learning.algorithm.genetic.EvaluatedGenome
Sets the genome.
setGeometricDecrease(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
Setter for geometricDecrease
setGlobalWeighter(GlobalTermWeighter) - Method in class gov.sandia.cognition.text.term.vector.weighter.CompositeLocalGlobalTermWeighter
Sets the weighting scheme for the global weights.
setGoldenInterpolator(LineBracketInterpolatorGoldenSection) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorBrent
Setter for goldenInterpolator
setHashFunction(HashFunction) - Method in class gov.sandia.cognition.learning.data.feature.FeatureHashing
Gets the hash function to use.
setHiddenDimensionality(int) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Sets the number of hidden units, not including the bias term, by re-initializing the neural net's weights.
setHighValue(double) - Method in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Setter for highValue
setIdentifier(SemanticIdentifier) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
Gets the semantic identifier of the cogxel to convert.
setIdentifier(SemanticIdentifier) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Gets the semantic identifier of the Cogxel to convert.
setIdentifier(SemanticIdentifier) - Method in class gov.sandia.cognition.framework.SemanticIdentifierMapEvent
Sets the SemanticIdentifier involved in the event.
setIdentifier(IdentifierType) - Method in class gov.sandia.cognition.util.DefaultIdentifiedValue
Sets the identifier.
setIdentifierCounter(int) - Method in class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap
Setter for identifier Counter.
setIdentifiers(ArrayList<SemanticIdentifier>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Sets the list of cached SemanticIdentifiers.
setIdentifiers(SemanticIdentifier[]) - Method in class gov.sandia.cognition.framework.lite.VectorBasedCognitiveModelInput
Setter for identifiers
setIdentifierToIndexMap(HashMap<SemanticIdentifier, Integer>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Sets the cached mapping of SemanticIdentifier to vector index.
setImaginaryPart(double) - Method in class gov.sandia.cognition.math.ComplexNumber
Sets the imaginary portion of the complex number
setImportanceDistribution(ProbabilityFunction<DataType>) - Method in class gov.sandia.cognition.statistics.montecarlo.ImportanceSampler
Setter for importanceDistribution.
setIncomingValue(Object) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
Sets the incoming value for the node.
setIndex(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster
Sets the index of the cluster.
setIndex(int) - Method in class gov.sandia.cognition.learning.function.categorization.VectorElementThresholdCategorizer
Sets the vector index that the threshold is being applied to.
setIndex(int) - Method in class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction
Sets the index into the vector that the function gets the value for.
setIndex(int) - Method in class gov.sandia.cognition.math.matrix.DefaultTwoVectorEntry
Sets the current index into the underlying vectors.
setIndex(int) - Method in interface gov.sandia.cognition.math.matrix.TwoVectorEntry
Sets the current index into the Vector to which this entry points
setIndex(int) - Method in interface gov.sandia.cognition.math.matrix.VectorEntry
Sets the current index into the Vector to which this entry points
setIndex(int) - Method in class gov.sandia.cognition.math.matrix.VectorizableIndexComparator
Setter for index.
setIndex(int) - Method in class gov.sandia.cognition.text.term.DefaultIndexedTerm
Sets the index of the term.
setIndexComparator(EntryIndexComparator<MatrixEntry>) - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
Sets the index comparator.
setInitialAlpha(double) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Setter for initialAlpha
setInitialDomainCapacity(int) - Method in class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.DefaultFactory
Sets the initial domain capacity.
setInitialGuess(HiddenMarkovModel<ObservationType>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
Setter for initialGuess.
setInitialGuess(InputType) - Method in class gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer
Setter for initialGuess
setInitialGuess(InputType) - Method in interface gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizer
Sets the initial guess of the minimization routine
setInitialGuess(Double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
 
setInitialGuess(Vector) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
Sets the initial guess ("x0")
setInitialGuess(double) - Method in class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder
 
setInitialGuess(double) - Method in class gov.sandia.cognition.learning.algorithm.root.MinimizerBasedRootFinder
 
setInitialGuess(double) - Method in interface gov.sandia.cognition.learning.algorithm.root.RootBracketer
Sets the initial guess of the root location.
setInitialGuess(double) - Method in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
 
setInitialGuess(double) - Method in interface gov.sandia.cognition.learning.algorithm.root.RootFinder
Sets the initial guess of the root (zero-crossing), which is supplied as input to the function to find the zero-crossings of.
setInitialGuessFunctionValue(Double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Setter for initialGuessFunctionValue
setInitialGuessSlope(Double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Setter for initialGuessSlope
setInitializationRange(double) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Setter for initializationRange
setInitialized(boolean) - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Sets whether or not this state has been initialized.
setInitializer(FixedClusterInitializer<ClusterType, DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Sets the cluster initializer.
setInitialPopulation(Collection<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Setter for initialPopulation.
setInitialProbability(Vector) - Method in class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain
Setter for initialProbability
setInput(CognitiveModelInput) - Method in interface gov.sandia.cognition.framework.CognitiveModelState
Sets the input for this model state.
setInput(CognitiveModelInput) - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Sets the input for this model state.
setInput(InputType) - Method in class gov.sandia.cognition.learning.data.DefaultInputOutputPair
Sets the input.
setInputConverter(CogxelConverter<InputType>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter
Sets the input converter
setInputConverter(CogxelConverter<InputType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner
Sets the CogxelConverter used to convert from a CogxelState to InputType.
setInputConverter(CogxelConverter<InputType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleSettings
Sets the CogxelConverter used to convert from a CogxelState to InputType.
setInputDimensionality(int) - Method in class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer
Setter for inputDimensionality.
setInputDimensionality(int) - Method in class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator
Sets the expected input dimensionality.
setInputDimensionality(int) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Sets the number of input units, not counting the bias term, by re-initializing the neural net's parameters.
setInputLearner(BatchLearner<? super Collection<? extends InputType>, ? extends Evaluator<? super InputType, ? extends TransformedInputType>>) - Method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Sets the unsupervised learning algorithm for creating the input transformation.
setInputToVectorMap(Evaluator<? super InputType, Vector>) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearBasisRegression
Setter for inputToVectorMap
setIntegralGain(double) - Method in class gov.sandia.cognition.math.signals.PIDController
Setter for integralGain
setInternalEntry(TwoMatrixEntry) - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
setter for internalEntry
setInternalEntry(TwoVectorEntry) - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
setter for internalEntry
setInternalFunction(Evaluator<Double, Double>) - Method in class gov.sandia.cognition.learning.algorithm.root.SolverFunction
Setter for internalFunction.
setInternalFunction(Evaluator<? super InputType, OutputType>) - Method in class gov.sandia.cognition.math.matrix.NumericalDifferentiator
Setter for internalFunction
setInternalMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
Setter for internalMatrix
setInternalMatrix(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
setInternalReader(VectorReader) - Method in class gov.sandia.cognition.math.matrix.MatrixReader
Setter for internalReader
setInternalState(CloneableSerializable) - Method in class gov.sandia.cognition.framework.lite.CognitiveModuleStateWrapper
Sets the internal state object.
setInternalVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
Setter for internalVector
setInternalVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
 
setInternalVector(DenseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
Sets the internalVector using MTJ's DenseVector
setInternalVector(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
 
setInternalVector(SparseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
Setter for the internal MTJ vector.
setInterpolator(LineBracketInterpolator<? super EvaluatorType>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Setter for interpolator
setInverseDocumentFrequency(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.InverseDocumentFrequencyGlobalTermWeighter
Sets the cached inverse-document-frequency (IDF) global weight values.
setInverseGamma(InverseGammaDistribution) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution
Setter for inverseGamma
setInverseScale(Matrix) - Method in class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution
Setter for inverseScale
setInverseWishart(InverseWishartDistribution) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
Setter for inverseWishart
setIteration(int) - Method in class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
Sets the current iteration number.
setIterationLearner(SupervisedBatchLearner<InputType, OutputType, ?>) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
 
setIterationsPerSample(int) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
 
setIterationsPerSample(int) - Method in interface gov.sandia.cognition.statistics.bayesian.MarkovChainMonteCarlo
Sets the number of iterations that must transpire between capturing samples from the distribution.
setIterationsPerSample(int) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
Sets the number of iterations to the Markov Chain Monte Carlo algorithm between samples (after the burn-in iterations).
setIterationsWithoutImprovement(int) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the current number of iterations without improvement.
setIterationsWithoutImprovement(int) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Sets the current number of iterations without improvement.
setIterationsWithoutImprovement(int) - Method in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
Setter for iterationsWithoutImprovement
setIterativeSolverTolerance(double) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
The tolerance that between-iteration error must be below before considering the iterative solver "done".
setK(int) - Method in class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor
Setter for k
setK(int) - Method in interface gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighbor
Setter for k
setKappa(double) - Method in class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
Sets kappa, the value multiplied by the dot product of the two vectors before it is passed to the hyperbolic tangent function.
setKeepGoing(boolean) - Method in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
Sets the keep going value, which indicates if the algorithm should continue on to another step.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner
Sets the kernel used by this learner.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
Sets the kernel to use.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
Sets the kernel to use.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
Sets the kernel to use.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.regression.LocallyWeightedFunction.Learner
Setter for kernel
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.regression.LocallyWeightedFunction
Setter for kernel
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Sets the kernel to use in training the SVM.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Sets the kernel to use.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
Sets the internal kernel.
setKernel(Kernel<? super InputType>) - Method in class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer
Sets the internal kernel.
setKernelCacheSize(int) - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Sets the size of the kernel cache or 0 if no kernel cache is to be used.
setKernelMatrix(Matrix) - Method in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
Sets the kernel matrix for the data that the analysis was done over.
setKernels(Collection<? extends Kernel<? super InputType>>) - Method in class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer
Sets the collection of kernels.
setKernelWeightingFunction(Kernel<? super OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
Getter for kernelWeightingFunction
setKey(KeyType) - Method in class gov.sandia.cognition.util.DefaultKeyValuePair
Sets the key element of the pair.
setKnownCovarianceInverse(Matrix) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator
Setter for knownCovarianceInverse.
setKnownVariance(double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator
Setter for knownVariance.
setLabel(SemanticLabel) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter
Sets the label of the cogxel to convert.
setLabel(SemanticLabel) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Sets the label of the Cogxel to convert.
setLabel(NodeNameType, LabelType) - Method in class gov.sandia.cognition.graph.inference.CostSpeedupEnergyFunction
 
setLabel(NodeNameType, LabelType) - Method in class gov.sandia.cognition.graph.inference.EdgeMergingEnergyFunction
 
setLabel(NodeNameType, LabelType) - Method in class gov.sandia.cognition.graph.inference.GraphWrappingEnergyFunction
 
setLabel(NodeNameType, LabelType) - Method in interface gov.sandia.cognition.graph.inference.NodeNameAwareEnergyFunction
Set the label for the input node
setLabels(HashMap<String, DefaultSemanticLabel>) - Method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Sets the label mapping.
setLabels(ArrayList<SemanticLabel>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Sets the labels to be used by the converter, each one corresponding to one dimension in the converted Vector.
setLabels(Collection<SemanticLabel>) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState
Sets the labels for the state to keep as the labels of the dimensions of the state.
setLambda(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
Sets the lambda parameter, which controls how much shifting and decay there is in the weight vector.
setLastErr(double) - Method in class gov.sandia.cognition.math.signals.PIDController.State
Setter for lastErr
setLastGradient(InputOutputPair<Vector, Vector>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToDifferentiableScalarFunction
Setter for lastGradient
setLastModifiedDate(long) - Method in class gov.sandia.cognition.text.document.DefaultDocument
Sets the last modified date of the document.
setLastModifiedDate(Date) - Method in class gov.sandia.cognition.text.document.DefaultDocument
Sets the last modified date of the document.
setLastTokenNum(int) - Method in class gov.sandia.cognition.io.ReaderTokenizer
Setter for lastTokenNum
setLayers(ArrayList<? extends GeneralizedLinearModel>) - Method in class gov.sandia.cognition.learning.function.vector.FeedforwardNeuralNetwork
Setter for layers
setLeafCountThreshold(int) - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
Sets the leaf count threshold, which determines the number of elements at which to make an element into a leaf.
setLeafCountThreshold(int) - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner
Sets the leaf count threshold, which determines the number of elements at which to learn a regression function.
setLeakage(double) - Method in class gov.sandia.cognition.learning.function.scalar.LeakyRectifiedLinearFunction
Sets the leakage, which is the multiplier for the value when it is less than zero.
setLearned(KernelBinaryCategorizer<InputType, DefaultWeightedValue<InputType>>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
Sets the object currently being result.
setLearned(Evaluator<InputType, OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
Getter for result
setLearner(BatchLearner<? super Collection<LearningDataType>, ? extends Evaluator<? super InputType, ? extends OutputType>>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner
Sets the learner used to create the Evaluator for the module.
setLearner(LearnerType) - Method in class gov.sandia.cognition.learning.algorithm.AbstractBatchLearnerContainer
Sets the wrapped learner.
setLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, OutputType>>, ? extends MemberType>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Sets the learner used to learn each ensemble member.
setLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Sets the learner used to learn each ensemble member.
setLearner(IncrementalLearner<? super InputOutputPair<? extends InputType, CategoryType>, MemberType>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
Sets the incremental (online) learning algorithm to use to learn all of the ensemble members.
setLearner(KernelizableBinaryCategorizerOnlineLearner) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelBinaryCategorizerOnlineLearnerAdapter
Sets the kernelizable learner that this adapter is wrapping.
setLearner(SupervisedBatchLearner<InputType, OutputType, ?>) - Method in class gov.sandia.cognition.learning.algorithm.regression.LocallyWeightedFunction.Learner
Setter for learner
setLearner(SupervisedBatchLearner<InputType, OutputType, ?>) - Method in class gov.sandia.cognition.learning.algorithm.regression.LocallyWeightedFunction
Setter for learner
setLearner(BatchLearner<? super Collection<? extends InputDataType>, ? extends LearnedType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
Sets the learner the experiment is being run on.
setLearner(BatchLearner<? super Collection<? extends FoldDataType>, ? extends LearnedType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
Sets the learner the experiment is being run on.
setLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>) - Method in class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter.Learner
Sets the learner whose output is to be adapted to be a categorizer.
setLearners(Pair<BatchLearner<? super Collection<? extends FoldDataType>, ? extends LearnedType>, BatchLearner<? super Collection<? extends FoldDataType>, ? extends LearnedType>>) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
Sets the learners the experiment is being run on.
setLearners(Collection<? extends DistributionWeightedEstimator<Double, ? extends SmoothUnivariateDistribution>>) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
Setter for learners
setLearningDataConverter(CogxelConverter<LearningDataType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner
Sets the CogxelConverter used to convert from a CogxelState to LearningDataType.
setLearningRate(double) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineStochasticGradient
Gets the learning rate.
setLearningRate(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Setter for learningRate
setLearningRate(double) - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
Setter for learningRate
setLength(int) - Method in class gov.sandia.cognition.text.AbstractOccurrenceInText
Sets the length of the occurrence.
setLineMinimizer(LineMinimizer<?>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
Setter for lineMinimizer
setLineMinimizer(LineMinimizer<?>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell
Setter for lineMinimizer
setLineMinimizer(LineMinimizer<?>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton
Setter for lineMinimizer
setLineMinimizer(LineMinimizer<?>) - Method in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
Setter for lineMinimizer
setLineMinimizer(LineMinimizer<?>) - Method in class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm
Setter for lineMinimizer
setListeners(LinkedList<IterativeAlgorithmListener>) - Method in class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
Sets the list of listeners for this algorithm.
setListeners(LinkedList<LearningExperimentListener>) - Method in class gov.sandia.cognition.learning.experiment.AbstractLearningExperiment
Sets the listeners for this experiment.
setLocalApproximator(Evaluator<? super InputType, ? extends OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.regression.LocallyWeightedFunction
Setter for localApproximator
setLocalItems(LinkedList<DataType>) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Gets the list of items stored locally at the node in the tree.
setLocalWeighter(LocalTermWeighter) - Method in class gov.sandia.cognition.text.term.vector.weighter.CompositeLocalGlobalTermWeighter
Sets the weighting scheme for the local weights.
setLocation(double) - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Setter for location
setLocation(double) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Setter for location.
setLog(KeyType, LogNumber) - Method in class gov.sandia.cognition.collection.AbstractLogNumberMap
Sets the LogNumber at the given key
setLogFunction(AdaptiveRejectionSampling.LogEvaluator<?>) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Setter for logFunction
setLogNormalMean(double) - Method in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
Setter for logNormalMean
setLogNormalVariance(double) - Method in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
Setter for logNormalVariance
setLogValue(double) - Method in class gov.sandia.cognition.math.LogNumber
Sets the log of the value represented by this object, which is what is stored in the object.
setLogValue(double) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
Sets the log of the value represented by this object, which is what is stored in the object.
setLowerBound(InputOutputSlopeTriplet) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineBracket
Setter for lowerBound
setLowerBound(double) - Method in class gov.sandia.cognition.statistics.method.ConfidenceInterval
Setter for lowerBound
setLowerLeft(Quadtree<DataType>.Node) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the lower-left child.
setLowerRight(Quadtree<DataType>.Node) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the lower-right child.
setLowValue(double) - Method in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Setter for lowValue
setMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.SemanticIdentifierMapEvent
Sets the SemanticIdentifierMap that the event happened in.
setMapping(LinkedHashMap<SemanticLabel, SemanticIdentifier>) - Method in class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap
Sets the mapping used by the object.
setMargin(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
Sets both the positive and negative margin to the same value.
setMargin(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
Sets both the positive and negative margin to the same value.
setMarginNegative(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
Sets the negative margin that is enforced.
setMarginNegative(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
Sets the negative margin that is enforced.
setMarginPositive(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
Sets the positive margin that is enforced.
setMarginPositive(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
Sets the positive margin that is enforced.
setMatrix(Matrix) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Sets the underlying matrix.
setMatrixFactory(MatrixFactory<? extends Matrix>) - Method in class gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator
Sets the matrix factory to create the matrix that backs the similarity network.
setMatrixFactory(MatrixFactory<? extends Matrix>) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
Sets the matrix factory to use.
setMaxBufferSize(int) - Method in class gov.sandia.cognition.learning.data.feature.LinearRegressionCoefficientExtractor
Setter for maxBufferSize
setMaxCriterionDecrease(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the maximum decrease in the training criterion allowed following a bisection.
setMaxDepth(int) - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner
Sets the maximum depth to grow the tree.
setMaxDepth(int) - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner
Sets the maximum depth to grow the tree.
setMaxDistance(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The maximum distance between clusters that is allowed for the two clusters to be merged.
setMaximum(DataType) - Method in class gov.sandia.cognition.evaluator.ValueClamper
Sets the maximum value to allow.
setMaximumLength(Integer) - Method in class gov.sandia.cognition.text.term.filter.TermLengthFilter
Gets the maximum length allowed for a term (inclusive).
setMaxIterations(int) - Method in class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm
 
setMaxIterations(int) - Method in interface gov.sandia.cognition.algorithm.AnytimeAlgorithm
Sets the maximum number of total iterations before stopping.
setMaxIterations(int) - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
 
setMaxIterations(int) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
Sets the maximum number of iterations before this will stop iterating.
setMaxIterationsWithoutImprovement(int) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the maximum number of iterations to go without improvement before stopping.
setMaxIterationsWithoutImprovement(int) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Sets the maximum number of iterations to go without improvement before stopping.
setMaxIterationsWithoutImprovement(int) - Method in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
Setter for maxIterationsWithoutImprovement
setMaxMagnitude(double) - Method in class gov.sandia.cognition.learning.function.scalar.AtanFunction
Setter for maxMagnitude.
setMaxMinDistance(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Deprecated.
Use setMaxDistance
setMaxNumPoints(int) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Setter for maxNumPoints
setMaxPenalty(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
Sets the maximum penalty parameter for the algorithm, which is also known as C in the paper and in other related literature.
setMaxSupport(double) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Setter for maxSupport
setMaxSupport(double) - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution
Setter for maxSupport
setMaxSupport(int) - Method in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
Sets the maximum support.
setMaxValue(int) - Method in class gov.sandia.cognition.collection.IntegerSpan
Setter for maxValue
setMaxWeight(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Sets the maximum weight allowed on an instance (support vector).
setMean(Vector) - Method in class gov.sandia.cognition.learning.algorithm.pca.PrincipalComponentsAnalysisFunction
Setter for mean
setMean(double) - Method in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
Sets the mean.
setMean(Vector) - Method in class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer
Sets the mean of the categorizer, which is the weight vector.
setMean(double) - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
Setter for mean
setMean(double) - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
Setter for mean
setMean(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateGaussian
Sets the mean vector.
setMean(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
Setter for mean
setMean(double) - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Setter for mean
setMean(double) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
Setter for mean
setMeanL1Error(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter for meanL1Error
setMeasurementCovariance(Matrix) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
Setter for measurementCovariance
setMembers(List<MemberType>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractUnweightedEnsemble
Sets the list of ensemble members.
setMembers(List<WeightedValue<MemberType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble
Sets the members of the ensemble.
setMembers(List<MemberType>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.VotingCategorizerEnsemble
Sets the list of ensemble members.
setMembers(List<WeightedValue<MemberType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble
Sets the members of the ensemble.
setMembers(List<WeightedValue<MemberType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble
Sets the members of the ensemble.
setMetric(Semimetric<? super DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the distance metric the clustering uses.
setMinChange(double) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
Sets the minimum change allowed in an iteration.
setMinChange(double) - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
Setter for minChange
setMinChange(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Sets the minimum total weight change allowed for the algorithm to continue.
setMinClusters(ArrayList<Integer>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Sets the index of the closest cluster.
setMinClusterSize(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the minimum number of elements per cluster to allow.
setMinDenominator(double) - Method in class gov.sandia.cognition.math.LentzMethod
Setter for minDenominator
setMinDistances(ArrayList<Double>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
Sets the minimum distances for each clusters.
setMinFunctionValue(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased
Setter for minFunctionValue
setMinibatchSize(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
Set the size of the mini-batches.
setMinimum(DataType) - Method in class gov.sandia.cognition.evaluator.ValueClamper
Gets the minimum value to allow.
setMinimumChange(double) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
Sets the minimum change in log-likelihood to allow before stopping the algorithm.
setMinimumLength(Integer) - Method in class gov.sandia.cognition.text.term.filter.TermLengthFilter
Gets the minimum length allowed for a term (inclusive).
setMinMargin(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
Gets the minimum margin to enforce.
setMinMargin(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
Gets the minimum margin to enforce.
setMinMargin(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.ProportionalUpdate
 
setMinMargin(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron
Gets the minimum margin to enforce.
setMinNumClusters(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
The minimum number of clusters to allow.
setMinSamples(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the minimum number of samples.
setMinSensitivity(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
Sets the minimum sensitivity that an example can have on the result function.
setMinSplitSize(int) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner
Sets the minimum split size.
setMinSplitSize(int) - Method in class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdVarianceLearner
Sets the minimum split size.
setMinSupport(double) - Method in class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling
Setter for minSupport
setMinSupport(double) - Method in class gov.sandia.cognition.statistics.distribution.UniformDistribution
Setter for minSupport
setMinSupport(int) - Method in class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution
Sets the minimum support.
setMinValue(int) - Method in class gov.sandia.cognition.collection.IntegerSpan
Setter for minValue
setModel(CognitiveModel) - Method in class gov.sandia.cognition.framework.CognitiveModelStateChangeEvent
Sets the model that changed.
setModel(LinearDynamicalSystem) - Method in class gov.sandia.cognition.statistics.bayesian.KalmanFilter
Setter for model
setModelCovariance(Matrix) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter
Setter for modelCovariance
setModuleFactories(ArrayList<CognitiveModuleFactory>) - Method in class gov.sandia.cognition.framework.AbstractCognitiveModelFactory
Sets the list of module factories to use.
setModuleStatesArray(CognitiveModuleState[]) - Method in class gov.sandia.cognition.framework.lite.CognitiveModelLiteState
Sets the array of module states.
setMomentum(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Getter for momentum
setMotionModel(StatefulEvaluator<Vector, Vector, Vector>) - Method in class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter
Setter for motionModel
setMovingAverageCoefficients(Vector) - Method in class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter
Setter for movingAverageCoefficients
setMovingAverageCoefficients(Vector) - Method in class gov.sandia.cognition.math.signals.MovingAverageFilter
Setter for movingAverageCoefficients
setN(int) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator
Sets the number of samples in the experiment
setN(int) - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Setter for n
setN(int) - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
Setter for N
setN1(int) - Method in class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Setter for N1
setN2(int) - Method in class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Setter for N2
setName(String) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule
Sets the name of the module
setName(String) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactory
Setter for name
setName(String) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner
Setter for name
setName(String) - Method in class gov.sandia.cognition.statistics.DefaultDistributionParameter
 
setName(String) - Method in class gov.sandia.cognition.util.AbstractNamed
Sets the name of this Object.
setName(String) - Method in class gov.sandia.cognition.util.DefaultNamedValue
 
setNe(double) - Method in class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence.Statistic
Setter for Ne
setNegative(boolean) - Method in class gov.sandia.cognition.math.LogNumber
Sets whether or not this value has a negative sign.
setNeighborhoodRadius(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the neighborhood radius.
setNetwork(DefaultSemanticNetwork) - Method in class gov.sandia.cognition.framework.io.CSVDefaultCognitiveModelLiteHandler
Set the network being parsed.
setNodes(ArrayList<SemanticLabel>) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Sets the nodes in the recognizer.
setNodeToIDMap(HashMap<SemanticLabel, Integer>) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Sets the mapping of nodes to their vector indices.
setNormalizedCentroid(ClusterType) - Method in class gov.sandia.cognition.learning.algorithm.clustering.cluster.NormalizedCentroidCluster
Sets the normalized centroid of the cluster.
setNormalizer(TermWeightNormalizer) - Method in class gov.sandia.cognition.text.term.vector.weighter.CompositeLocalGlobalTermWeighter
Sets the weight normalizer.
setNullHypothesisProbability(double) - Method in class gov.sandia.cognition.statistics.method.AbstractConfidenceStatistic
Setter for nullHypothesisProbability
setNullValue(Number) - Method in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
Sets the number that represents a null value.
setNumChanged(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Setter for numChanged
setNumClusters(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
Sets the number of clusters for the algorithm to attempt to create.
setNumComponents(int) - Method in class gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis
Setter for numComponents
setNumComponents(int) - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
Setter for numComponents
setNumCustomers(int) - Method in class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess
Setter for numCustomers
setNumDifferent(int) - Method in class gov.sandia.cognition.statistics.method.FisherSignConfidence.Statistic
Setter for numDifferent
setNumericalDerivative(boolean) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
Setter for numericalDerivative
setNumFolds(int) - Method in class gov.sandia.cognition.learning.experiment.CrossFoldCreator
Sets the number of folds to create.
setNumFolds(int) - Method in class gov.sandia.cognition.learning.experiment.RandomFoldCreator
Sets the number of folds to create.
setNumInitialClusters(int) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Getter for numInitialClusters
setNumNonZero(int) - Method in class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence.Statistic
Setter for numNonZero
setNumParameters(int) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter for numParameters
setNumParticles(int) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter
 
setNumParticles(int) - Method in interface gov.sandia.cognition.statistics.bayesian.ParticleFilter
Sets the number of particles
setNumPositiveSign(int) - Method in class gov.sandia.cognition.statistics.method.FisherSignConfidence.Statistic
Setter for numPositiveSign
setNumRequestedClusters(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Sets the number of requested clusters.
setNumRequestedClusters(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the number of clusters requested.
setNumSamples(int) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter for numSamples
setNumSamples(int) - Method in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling
Setter for numSamples
setNumSamples(int) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling
Setter for numSamples
setNumSamples(int) - Method in class gov.sandia.cognition.statistics.method.ConfidenceInterval
Setter for numSamples
setNumSamples(int) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
Setter for numSamples
setNumSplits(int) - Method in class gov.sandia.cognition.learning.experiment.RandomByTwoFoldCreator
Sets the number of splits to perform.
setNumThreads(int) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
Specifies how many threads to use in the matrix/vector multiplies in the iterative solver.
setNumTrials(int) - Method in class gov.sandia.cognition.learning.experiment.AbstractValidationFoldExperiment
Sets the number of trials in the experiment.
setNumTrials(int) - Method in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
Sets the number of trials for the experiment to repeatedly call the learning algorithm.
setNumTrials(int) - Method in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
Sets the number of trials.
setNumTrials(int) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator
Setter for numTrials
setNumTrials(int) - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
Setter for numTrials
setNumTrials(int) - Method in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
Setter for numTrials
setObjectToOptimize(FunctionType) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
Setter for objectToOptimize
setObjectToOptimize(ResultType) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
 
setObjectToOptimize(ResultType) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Setter for objectToOptimize
setObjectToOptimize(LogisticRegression.Function) - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
Setter for objectToOptimize
setObjectToOptimize(ResultType) - Method in interface gov.sandia.cognition.learning.algorithm.regression.ParameterCostMinimizer
Set the object to optimize
setObservationModel(Evaluator<Vector, Vector>) - Method in class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter
Setter for observationModel
setOffset(double) - Method in class gov.sandia.cognition.learning.function.scalar.LinearFunction
Sets the offset of the function, which is the b term in: f(x) = m*x + b.
setOptimalThreshold(ReceiverOperatingCharacteristic.DataPoint) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Setter for optimalThreshold
setOriginalPoint(InputOutputSlopeTriplet) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions
Setter for originalPoint
setOtherPoint(InputOutputSlopeTriplet) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineBracket
Setter for otherPoint
setOutlierPercent(double) - Method in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer.Learner
Sets the percentage of outliers to exclude from learning.
setOutput(OutputType) - Method in class gov.sandia.cognition.learning.data.DefaultInputOutputPair
Sets the output.
setOutputCategory(OutputType) - Method in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode
Sets the output category for the node.
setOutputConverter(CogxelConverter<OutputType>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter
Sets the output converter
setOutputConverter(CogxelConverter<OutputType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner
Sets the CogxelConverter used to convert OutputType to a CogxelState.
setOutputConverter(CogxelConverter<OutputType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleSettings
Sets the CogxelConverter used to convert OutputType to a CogxelState.
setOutputDimensionality(int) - Method in class gov.sandia.cognition.learning.data.feature.FeatureHashing
Sets the output dimensionality, which is the size of the output vector that the input is hashed into.
setOutputDimensionality(int) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Sets the output dimensionality of the neural net by re-initializing the weights.
setOutputLearner(BatchLearner<? super Collection<? extends OutputType>, ? extends ReversibleEvaluator<OutputType, TransformedOutputType, ?>>) - Method in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
Gets the unsupervised learning algorithm for creating the output transformation, which must be reversible for evaluation.
setOutputVariance(double) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
Setter for outputVariance
setOutputVariance(InverseGammaDistribution) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression
Setter for outputVariance
setOutputVariance(double) - Method in class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression
Getter for outputVariance
setOverrelaxation(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Gets the overrelaxation parameter for the algorithm.
setP(double) - Method in class gov.sandia.cognition.statistics.distribution.BernoulliDistribution
Setter for p
setP(double) - Method in class gov.sandia.cognition.statistics.distribution.BinomialDistribution
Setter for p
setP(double) - Method in class gov.sandia.cognition.statistics.distribution.GeometricDistribution
Setter for p
setP(double) - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
Setter for p
setPairConverter(CogxelInputOutputPairConverter<InputType, OutputType>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter
Setter for pairConverter
setPairwiseTest(NullHypothesisEvaluator<Collection<? extends Number>>) - Method in class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison
Setter for pairwiseTest
setParabolicInterpolator(LineBracketInterpolatorParabola) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorBrent
Setter for parabolicInterpolator
setParameter(BayesianParameter<ParameterType, ConditionalType, BeliefType>) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator
Setter for parameter
setParameterAdapters(LinkedList<ParameterAdapter<? super LearnerType, ? super DataType>>) - Method in class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper
Sets the list of parameter adapters for the learning algorithm.
setParameterPrior(PriorType) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter
Setter for parameterPrior
setParameterPrior(PriorType) - Method in class gov.sandia.cognition.statistics.bayesian.DefaultBayesianParameter
Sets the Distribution of values that the parameter is assumed to take.
setParameters(Object...) - Method in class gov.sandia.cognition.factory.ConstructorBasedFactory
Sets the parameters that are passed to the constructor to create new objects.
setParameters(Vector) - Method in class gov.sandia.cognition.statistics.distribution.CategoricalDistribution
Setter for parameters
setParameters(Vector) - Method in class gov.sandia.cognition.statistics.distribution.DirichletDistribution
Setter for parameters
setParameters(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution
Setter for parameters
setParameters(Vector) - Method in class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution
Setter for parameters
setParent(DecisionTreeNode<InputType, OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode
Sets the parent node for this node.
setParent(Quadtree<DataType>.Node) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the parent node of this node.
setParticlePctThreadhold(double) - Method in class gov.sandia.cognition.statistics.bayesian.SamplingImportanceResamplingParticleFilter
Setter for particlePctThreadhold
setPartitioner(RandomizedDataPartitioner<DataType>) - Method in class gov.sandia.cognition.learning.experiment.RandomFoldCreator
Sets the randomized partitioner to use.
setPercent(double) - Method in class gov.sandia.cognition.learning.algorithm.genetic.selector.TournamentSelector
Sets the percent of the population to select.
setPercentToSample(double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
Sets the percentage of the data to sample (with replacement) on each iteration.
setPercentToSample(double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Sets the percentage of the data to sample (with replacement) on each iteration.
setPercentToSample(double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
Sets the percent of the data to attempt to sample for each ensemble member.
setPercentToSample(double) - Method in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
Sets the percent of the dimensionality to sample.
setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType, ? super Collection<? extends FoldDataType>, ? extends StatisticType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
Sets the performance evaluator to apply to each fold.
setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType, ? super Collection<? extends InputDataType>, ? extends StatisticType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
Sets the performance evaluator to apply to each fold.
setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType, ? super Collection<? extends FoldDataType>, ? extends StatisticType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
Sets the performance evaluator to apply to each fold.
setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType, ? super Collection<? extends DataType>, ? extends StatisticType>) - Method in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
Sets the performance evaluator to apply to each fold.
setPerformanceEvaluator(PerformanceEvaluator<? super ObjectType, ? super DataType, ?>) - Method in class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
Sets the performance evaluator.
setPerturber(Perturber<AnnealedType>) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the perturber.
setPerturber(Perturber<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.MutationReproducer
Sets the perturber used for mutation.
setPhase(double) - Method in class gov.sandia.cognition.learning.function.scalar.CosineFunction
Setter for phase
setPoint(double) - Method in class gov.sandia.cognition.statistics.distribution.DeterministicDistribution
Setter for point
setPointIndex(int) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the point index.
setPoints(ArrayList<DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
Sets the list of points.
setPolynomials(ScalarBasisSet<Double>) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Regression
Setter for polynomials
setPopulation(Collection<EvaluatedGenome<GenomeType>>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Sets the population of genomes.
setPosteriorLogLikelihood(Double) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample
sets the posterior log-likelihood.
setPostHocTest(MultipleHypothesisComparison<Collection<? extends Number>>) - Method in class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment
Setter for postHocTest
setPower(double) - Method in class gov.sandia.cognition.learning.function.distance.MinkowskiDistanceMetric
Sets the power used for the distance.
setPrecision(Matrix) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution.PDF
 
setPrecision(Matrix) - Method in class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution
Setter for precision
setPrecision(double) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Setter for precision.
setPrecision(double) - Method in class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Setter for precision
setPrecision(double) - Method in class gov.sandia.cognition.text.evaluation.DefaultPrecisionRecallPair
Sets the precision.
setPredictionHorizon(int) - Method in class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner
Sets the prediction horizon, which is the number of samples ahead in time that the learner is to predict.
setPredictionHorizon(int) - Method in class gov.sandia.cognition.learning.algorithm.TimeSeriesPredictionLearner
Setter for predictionHorizon
setPreprocessor(Evaluator<? super InputType, ? extends IntermediateType>) - Method in class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer
Sets the preprocessor, which takes the input and produces an intermediate value that is then passed to the categorizer.
setPriors(DataDistribution<CategoryType>) - Method in class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer
Sets the prior distribution over the categories.
setPriorWeights(double[]) - Method in class gov.sandia.cognition.statistics.distribution.LinearMixtureModel
Getter for priorWeights
setProbabilityCrossover(double) - Method in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.VectorizableCrossoverFunction
Setter for probabilityCrossover.
setProbabilityFunction(ProbabilityFunction<? super ObservationType>) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMCluster
Setter for probabilityFunction
setProcess(Process) - Method in class gov.sandia.cognition.io.ProcessLauncher
Setter for process
setProcess(Process) - Method in class gov.sandia.cognition.io.ProcessLauncherEvent
Setter for process
setProportionalGain(double) - Method in class gov.sandia.cognition.math.signals.PIDController
Setter for proportionalGain
setProportionIncorrectInSample(double) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Sets the proportion of incorrect examples to place in each sample.
setProposals(int) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Setter for proposals
setPrototype(CreatedType) - Method in class gov.sandia.cognition.factory.PrototypeFactory
Sets the prototype object that is cloned to create new objects.
setPrototypes(Map<CategoryType, LinearBinaryCategorizer>) - Method in class gov.sandia.cognition.learning.function.categorization.LinearMultiCategorizer
Sets the mapping of categories to prototypes.
setQ(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Result
Gets the value Q updated by the algorithm.
setQ0(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear
Setter for q0
setQ1(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear
Setter for q1
setQ2(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Quadratic
Setter for q2
setQ3(double) - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic
Setter for q3
setR(double) - Method in class gov.sandia.cognition.learning.algorithm.confidence.AdaptiveRegularizationOfWeights
Sets the regularization parameter.
setR(DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.decomposition.CholeskyDecompositionMTJ
Setter for R
setR(double) - Method in class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution
Setter for r.
setRadius(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Ballseptron
Sets the radius parameter.
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the random number generator.
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.genetic.selector.TournamentSelector
Sets the random number generator to use.
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelRandomizedBudgetPerceptron
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
 
setRandom(Random) - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
 
setRandom(Random) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
 
setRandom(Random) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter
 
setRandom(Random) - Method in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner
 
setRandom(Random) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
 
setRandom(Random) - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
 
setRandom(Random) - Method in class gov.sandia.cognition.statistics.UnivariateRandomVariable
 
setRandom(Random) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
 
setRandom(Random) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
 
setRandom(Random) - Method in class gov.sandia.cognition.util.AbstractRandomized
 
setRandom(Random) - Method in interface gov.sandia.cognition.util.Randomized
Sets the random number generator used by this object.
setRandomRange(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.initializer.NeighborhoodGaussianClusterInitializer
Setter for randomRange
setRandomSet(long) - Method in class gov.sandia.cognition.graph.community.Louvain
Initialize the random number generator with the input seed.
setRandomSet(long) - Method in class gov.sandia.cognition.graph.community.PersonalizedPageRank
Initialize the random number generator with the input seed.
setRate(double) - Method in class gov.sandia.cognition.statistics.distribution.ExponentialDistribution
Setter for rate.
setRate(double) - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Sets the rate parameter, which is just the inverse of the scale parameter.
setRate(double) - Method in class gov.sandia.cognition.statistics.distribution.PoissonDistribution
Setter for rate
setRealPart(double) - Method in class gov.sandia.cognition.math.ComplexNumber
Sets the real part of the complex number
setRecall(double) - Method in class gov.sandia.cognition.text.evaluation.DefaultPrecisionRecallPair
Sets the recall.
setRecognizer(MutablePatternRecognizerLite) - Method in class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLiteFactory
Sets the settings used by the factory.
setReductionTest(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
Setter for reduction test.
setReestimateAlpha(boolean) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Setter for reestimateAlpha
setReestimateInitialProbabilities(boolean) - Method in class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm
Setter for reestimateInitialProbabilities
setReference(DocumentReference) - Method in class gov.sandia.cognition.text.document.AbstractDocument
Sets the reference to where the document can be found.
setRegressionLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, Double>>, ? extends Evaluator<? super InputType, Double>>) - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner
Sets the regression learner that is to be used to fit a function approximator to the values in the tree.
setRegularization(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
Setter for regularization
setRegularization(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression
Setter for regularization
setRegularization(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
Setter for regularization
setRegularization(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.MultivariateLinearRegression
Setter for regularization
setRegularizationWeight(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
Sets the regularization weight (lambda) assigned to the regularization term of the algorithm.
setRemovalThreshold(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClustererWithRemoval
Setter for removalThreshold
setReproducer(Reproducer<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
Sets the reproducer.
setReproducers(Collection<Reproducer<GenomeType>>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.MultiReproducer
Sets the reproducers to use for reproducing.
setRequestedRank(int) - Method in class gov.sandia.cognition.text.topic.LatentSemanticAnalysis
Sets the requested rank of the analysis.
setRequestedRank(int) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
Sets the requested rank to conduct the analysis for.
setResponsibilities(double[][]) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the responsibility values.
setResult(InputOutputPair<InputType, OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer
Setter for result
setResult(PrincipalComponentsAnalysisFunction) - Method in class gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis
Setter for result
setResult(PrincipalComponentsAnalysisFunction) - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
Setter for result
setResult(LinearMultiCategorizer<CategoryType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
Sets the result of the algorithm.
setResult(DefaultKernelBinaryCategorizer<InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
Sets the object currently being result.
setResult(LinearBinaryCategorizer) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
Sets the object currently being result.
setResult(ResultType) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer
Setter for result
setResult(ResultType) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Setter for result
setResult(KernelScalarFunction<InputType>) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
Sets the object currently being result.
setResult(LogisticRegression.Function) - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
Setter for result
setResult(KernelBinaryCategorizer<InputType, DefaultWeightedValue<InputType>>) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Sets the object currently being result.
setResult(DefaultDataDistribution<ParameterType>) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
Setter for result
setResultCost(Double) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Setter for resultCost
setReverse(ReverseType) - Method in class gov.sandia.cognition.evaluator.ForwardReverseEvaluatorPair
Sets the reverse evaluator that maps output type to input type.
setRootBracket(LineBracket) - Method in class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder
Setter for rootBracket.
setRootMeanSquaredError(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter fpr rootMeanSquaredError
setRootNode(DecisionTreeNode<InputType, OutputType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.DecisionTree
Sets the root node of the decision tree.
setRow(int, Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
setRow(int, Vector) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Sets the specified row from the given rowVector
setRow(int, SparseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix
Sets the specified row of the matrix using rowVector, using MTJ's internal routine to speed things up.
setRowIndex(int) - Method in interface gov.sandia.cognition.math.matrix.MatrixEntry
Sets the current row index to which this entry points
setRowIndex(int) - Method in class gov.sandia.cognition.math.matrix.mtj.TwoMatrixEntryMTJ
Setter for rowIndex.
setRowIndex(int) - Method in interface gov.sandia.cognition.math.matrix.TwoMatrixEntry
Sets the current row index to which this entry points
setS(Matrix) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition
setter for the singular values matrix
setSampler(ProbabilityFunction<ParameterType>) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Setter for sampler
setSampleSize(int) - Method in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
Sets the sample size, which is the number of examples sampled without replacement on each iteration of the algorithm.
setScalarFunction(Evaluator<? super InputType, Double>) - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeNode
Sets the scalar function applied to the input when the node is a leaf node.
setScalarFunction(UnivariateScalarFunction) - Method in class gov.sandia.cognition.learning.function.vector.ElementWiseDifferentiableVectorFunction
 
setScalarFunction(UnivariateScalarFunction) - Method in class gov.sandia.cognition.learning.function.vector.ElementWiseVectorFunction
Setter for scalarFunction
setScale(Double) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.CauchyDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.LaplaceDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.LogisticDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Setter for scale
setScale(double) - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Setter for scale
setScaleFactor(double) - Method in class gov.sandia.cognition.learning.function.vector.LinearVectorFunction
Sets the linear scale factor.
setSecond(SecondType) - Method in class gov.sandia.cognition.util.DefaultPair
Sets the second object.
setSecond(SecondType) - Method in class gov.sandia.cognition.util.DefaultTriple
Sets the second object.
setSecondChild(ClusterHierarchyNode<DataType, ClusterType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.BinaryClusterHierarchyNode
Sets the second child node.
setSecondConverter(CogxelConverter<SecondType>) - Method in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
Setter for secondConverter
setSecondInternalEntry(MatrixEntry) - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
setter for secondInternalEntry
setSecondInternalEntry(VectorEntry) - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
setter for secondInternalEntry
setSecondIterator(Iterator<MatrixEntry>) - Method in class gov.sandia.cognition.math.matrix.MatrixUnionIterator
setter for secondIterator
setSecondIterator(Iterator<VectorEntry>) - Method in class gov.sandia.cognition.math.matrix.VectorUnionIterator
setter for secondIterator
setSecondLearner(BatchLearner<? super Collection<? extends IntermediateType>, ? extends Evaluator<? super IntermediateType, ? extends OutputType>>) - Method in class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair
Sets the second learner that is applied to the output of the first learner.
setSecondMatrix(AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.TwoMatrixEntryMTJ
Setter for secondMatrix.
setSecondValue(double) - Method in class gov.sandia.cognition.math.matrix.DefaultTwoVectorEntry
Sets the entry value for the second underlying vector.
setSecondValue(double) - Method in class gov.sandia.cognition.math.matrix.mtj.TwoMatrixEntryMTJ
Sets the entry value from the second underlying matrix.
setSecondValue(double) - Method in interface gov.sandia.cognition.math.matrix.TwoMatrixEntry
Sets the second value to which this entry points
setSecondValue(double) - Method in interface gov.sandia.cognition.math.matrix.TwoVectorEntry
Sets the second value to which this entry points
setSecondVector(Vector) - Method in class gov.sandia.cognition.math.matrix.DefaultTwoVectorEntry
Setter for secondVector.
setSeedScale(double) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
Sets the seed initialization scale.
setSelector(Selector<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.CrossoverReproducer
Sets the selector.
setSelector(Selector<GenomeType>) - Method in class gov.sandia.cognition.learning.algorithm.genetic.reproducer.MutationReproducer
Sets the selector used to select the population.
setSelfDivergence(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the value used for self-divergence, which controls how many clusters are generated.
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelConverter
 
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter
 
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in interface gov.sandia.cognition.framework.learning.converter.CogxelConverter
Sets the SemanticIdentifierMap that the converter is to use.
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter
Sets the SemanticIdentifierMap that the converter is to use.
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter
Sets the SemanticIdentifierMap that the converter is to use.
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter
Sets the SemanticIdentifierMap that the converter is to use.
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter
Sets the SemanticIdentifierMap that the converter is to use.
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter
Sets the SemanticIdentifierMap that the converter is to use.
setSemanticIdentifierMap(DefaultSemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.lite.AbstractCognitiveModelLite
Sets the semantic identifier map.
setSemanticIdentifierMap(SemanticIdentifierMap) - Method in class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModule
Sets the semantic identifier map.
setSettings(EvaluatorBasedCognitiveModuleSettings<InputType, OutputType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule
Sets the settings of the module.
setSettings(EvaluatorBasedCognitiveModuleSettings<InputType, OutputType>) - Method in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactory
Sets the settings of the module created by the factory.
setShape(double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator
Sets the shape of the conditional distribution
setShape(double) - Method in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Setter for shape
setShape(double) - Method in class gov.sandia.cognition.statistics.distribution.GammaDistribution
Setter for shape
setShape(double) - Method in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
Setter for shape
setShape(double) - Method in class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution
Setter for shape
setShape(double) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Setter for shape
setShape(double) - Method in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Setter for shape
setShape(double) - Method in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
Setter for shape
setShift(double) - Method in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Setter for shift.
setSigma(double) - Method in class gov.sandia.cognition.learning.function.kernel.RadialBasisKernel
Sets the sigma value that controls the bandwidth of the kernel.
setSimilarities(double[][]) - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
Sets the array of similarities.
setSimilarities(Matrix) - Method in class gov.sandia.cognition.text.term.relation.MatrixBasedTermSimilarityNetwork
Gets the similarities between terms.
setSimilarity(double) - Method in class gov.sandia.cognition.text.term.relation.IndexedTermSimilarityRelation
Sets the similarity between the two terms.
setSimilarityFunction(SimilarityFunction<? super Vector, ? super Vector>) - Method in class gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator
Sets the similarity function between term vectors used to determine the similarity between two terms.
setSingularValues(Matrix) - Method in class gov.sandia.cognition.text.topic.LatentSemanticAnalysis.Transform
Sets the diagonal matrix of singular values.
setSize(int) - Method in class gov.sandia.cognition.learning.data.feature.RandomSubspace
Sets the size of the subspace that will be created.
setSize(int) - Method in class gov.sandia.cognition.text.term.filter.NGramFilter
Sets the size of the n-gram created by the filter.
setSlope(Double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.InputOutputSlopeTriplet
Setter for slope
setSlope(double) - Method in class gov.sandia.cognition.learning.function.scalar.LinearFunction
Sets the slope of the function, which is the m term in: f(x) = m*x + b.
setSlopeCondition(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions
Setter for slopeCondition
setSmoothingWindowSize(int) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
Sets the smoothing window size.
setSortedROCData(ArrayList<ReceiverOperatingCharacteristic.DataPoint>) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic
Setter for srtedROCData
setSource(SourceType) - Method in class gov.sandia.cognition.text.relation.AbstractRelation
Sets the source object of the relation.
setSplitThreshold(int) - Method in class gov.sandia.cognition.math.geometry.Quadtree
Sets the split threshold for the node.
setSquashingFunction(VectorFunction) - Method in class gov.sandia.cognition.learning.function.vector.GeneralizedLinearModel
Setter for squashingFunction
setSquashingFunction(DifferentiableUnivariateScalarFunction) - Method in class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork
Setter for squashingFunction
setStart(int) - Method in class gov.sandia.cognition.text.AbstractOccurrenceInText
Sets the starting point of the occurrence.
setStartNode(int) - Method in class gov.sandia.cognition.graph.GraphWalker
Sets the starting node (by id) for the next step (or series of steps)
setStartNode(NodeNameType) - Method in class gov.sandia.cognition.graph.GraphWalker
Sets the start node (by name) for the next step (or series of steps)
setState(StateType) - Method in class gov.sandia.cognition.evaluator.AbstractStatefulEvaluator
 
setState(StateType) - Method in interface gov.sandia.cognition.evaluator.StatefulEvaluator
Sets the current state of the evaluator.
setState(CognitiveModelState) - Method in class gov.sandia.cognition.framework.CognitiveModelStateChangeEvent
Sets the new state of the model.
setStateVector(Vector) - Method in class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState
Sets the state vector stored in the state object.
setStatisticalTest(NullHypothesisEvaluator<Collection<? extends StatisticType>>) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
Sets the statistical test to use to determine if the two learners are significantly different.
setStatistics(DefaultPair<ArrayList<StatisticType>, ArrayList<StatisticType>>) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
Sets the performance evaluations for the trials of the experiment.
setStatistics(ArrayList<StatisticType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
Sets the performance evaluations for the trials of the experiment.
setStatistics(ArrayList<StatisticType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
Sets the performance evaluations for the trials of the experiment.
setStatistics(ArrayList<StatisticType>) - Method in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
Sets the performance evaluations for the trials of the experiment.
setStopList(StopList) - Method in class gov.sandia.cognition.text.term.filter.StopListFilter
Sets the stop list for the filter to use.
setStoppingCriterion(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
Set the stopping criterion for this clusterer.
setSubIndices(int[]) - Method in class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator
Sets the array of sub-indices.
setSubLearner(DeciderLearner<Vectorizable, OutputType, Boolean, VectorElementThresholdCategorizer>) - Method in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
Sets the learner used to learn a threshold function over the subspace.
setSubMatrix(int, int, Matrix) - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
setSubMatrix(int, int, Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Sets the submatrix inside of the Matrix, specified by the zero-based indices.
setSufficientDecrease(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
Setter for sufficientDecrease
setSummaries(DefaultPair<SummaryType, SummaryType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment.Result
Sets the summary of performance for the learners.
setSummaries(DefaultPair<SummaryType, SummaryType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
Sets the summaries of the experiment.
setSummarizer(Summarizer<? super StatisticType, ? extends SummaryType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
Sets the summarizer of the performance evaluations.
setSummarizer(Summarizer<? super StatisticType, ? extends SummaryType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
Sets the summarizer of the performance evaluations.
setSummarizer(Summarizer<? super StatisticType, ? extends SummaryType>) - Method in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
Sets the summarizer of the performance evaluations.
setSummarizer(Summarizer<? super StatisticType, ? extends SummaryType>) - Method in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
Sets the summarizer of the performance evaluations.
setSummary(SummaryType) - Method in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
Sets the summary of the experiment.
setSummary(SummaryType) - Method in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
Sets the summary of the experiment.
setSummary(SummaryType) - Method in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
Sets the summary of the experiment.
setSupervisedLearner(SupervisedBatchLearner<InputType, OutputType, EvaluatorType>) - Method in class gov.sandia.cognition.learning.algorithm.TimeSeriesPredictionLearner
Setter for supervisedLearner
setSupportsMap(LinkedHashMap<InputOutputPair<? extends InputType, Boolean>, DefaultWeightedValue<InputType>>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
Gets the mapping of examples to weight objects (support vectors).
setSupportsMap(LinkedHashMap<InputOutputPair<? extends InputType, ? extends Boolean>, DefaultWeightedValue<InputType>>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
Gets the mapping of examples to weight objects (support vectors).
setSupportsMap(LinkedHashMap<InputOutputPair<? extends InputType, Double>, DefaultWeightedValue<InputType>>) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
Gets the mapping of examples to weight objects (support vectors).
setSupportsMap(LinkedHashMap<InputOutputPair<? extends InputType, ? extends Boolean>, SuccessiveOverrelaxation<InputType>.Entry>) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Gets the mapping of examples to weight objects (support vectors).
setSynonyms(Map<Term, Term>) - Method in class gov.sandia.cognition.text.term.filter.SynonymFilter
Sets the mapping of terms to their synonyms.
setT(double) - Method in class gov.sandia.cognition.statistics.method.StudentTConfidence.Statistic
Setter for t
setT(double) - Method in class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence.Statistic
Getter for T
setTarget(double) - Method in class gov.sandia.cognition.learning.algorithm.root.SolverFunction
Setter for target
setTarget(TargetType) - Method in class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair
Sets the target, which is the ground-truth or actual value.
setTarget(TargetType) - Method in class gov.sandia.cognition.text.relation.AbstractRelation
Sets the target object of the relation.
setTargetConverter(CogxelConverter<TargetType>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter
Sets the converter for the target value.
setTargetEstimateCorrelation(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter for targetEstimateCorrelation
setTargetInput(double) - Method in class gov.sandia.cognition.math.signals.PIDController
Setter for targetInput
setTemperature(double) - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Sets the current temperature of the system.
setTerm(Term) - Method in class gov.sandia.cognition.text.term.DefaultIndexedTerm
Sets the term.
setTerm(Term) - Method in class gov.sandia.cognition.text.term.DefaultTermOccurrence
Sets the term that occurred.
setTermBasis(Matrix) - Method in class gov.sandia.cognition.text.topic.LatentSemanticAnalysis.Transform
Sets the matrix of orthogonal term column vectors.
setTermDocumentFrequencies(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
Sets the vector containing the number of documents that each term appears in.
setTermEntropiesSum(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractEntropyBasedGlobalTermWeighter
Sets the vector containing the sum of the term entropies.
setTermGlobalFrequencies(Vector) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter
Gets the vector containing the number of times that each term appears.
setTermIndex(TermIndex) - Method in class gov.sandia.cognition.text.term.relation.MatrixBasedTermSimilarityNetwork
Sets the index of terms.
setTermIndex(TermIndex) - Method in class gov.sandia.cognition.text.term.vector.BagOfWordsTransform
Sets the term index that the transform is to use to map terms to their vector indices.
setTermList(List<DefaultIndexedTerm>) - Method in class gov.sandia.cognition.text.term.DefaultTermIndex
Gets the list of terms, ordered by index.
setTermMap(Map<Term, DefaultIndexedTerm>) - Method in class gov.sandia.cognition.text.term.DefaultTermIndex
Sets the mapping of terms to their indices.
setTerms(Term...) - Method in class gov.sandia.cognition.text.term.DefaultTermNGram
Sets the terms that make up the n-gram.
setTermToCountMap(HashMap<Term, Integer>) - Method in class gov.sandia.cognition.text.term.DefaultTermCounts
Gets the mapping of terms to their respective counts.
setTestingSet(Collection<DataType>) - Method in class gov.sandia.cognition.learning.data.DefaultPartitionedDataset
Sets the testing set.
setTestVector(Vector) - Method in class gov.sandia.cognition.statistics.ChiSquaredSimilarity
Basic setter for the test vector.
setText(String) - Method in class gov.sandia.cognition.text.DefaultTextual
Sets the text value in this object.
setText(String) - Method in class gov.sandia.cognition.text.document.DefaultTextField
Sets the text content for the field.
setText(String) - Method in class gov.sandia.cognition.text.term.DefaultTerm
Sets the text of the term.
setText(String) - Method in class gov.sandia.cognition.text.token.DefaultToken
Sets the text of the token.
setThird(ThirdType) - Method in class gov.sandia.cognition.util.DefaultTriple
Sets the third object.
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.algorithm.AbstractParallelAlgorithm
 
setThreadPool(ThreadPoolExecutor) - Method in interface gov.sandia.cognition.algorithm.ParallelAlgorithm
Sets the thread pool for the algorithm to use.
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm
Setter for threadPool
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.experiment.ParallelLearnerValidationExperiment
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.function.cost.ParallelClusterDistortionMeasure
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.learning.function.cost.ParallelNegativeLogLikelihood
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel
 
setThreadPool(ThreadPoolExecutor) - Method in class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler
 
setThreshold(double) - Method in class gov.sandia.cognition.learning.function.categorization.AbstractThresholdBinaryCategorizer
Setter for threshold
setThreshold(double) - Method in class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
Sets the threshold, which is the negative of the bias.
setThreshold(double) - Method in class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer
Sets the threshold, which is the negative of the bias.
setThreshold(double) - Method in interface gov.sandia.cognition.learning.function.categorization.ThresholdBinaryCategorizer
Sets the threshold between the two categories used in binary categorization.
setThreshold(double) - Method in class gov.sandia.cognition.learning.function.scalar.ThresholdFunction
Setter for threshold
setTime(Date) - Method in class gov.sandia.cognition.util.AbstractTemporal
Sets the time of the Temporal
setTitle(String) - Method in class gov.sandia.cognition.text.document.DefaultDocument
Sets the title field of the document to the given string.
setToJBlas() - Method in class gov.sandia.cognition.math.matrix.custom.NativeBlasHandler
Sets the BLAS library to use the Java version.
setTokenizer(ReaderTokenizer) - Method in class gov.sandia.cognition.math.matrix.VectorReader
Setter for tokenizer
setTolerance(double) - Method in class gov.sandia.cognition.graph.community.PersonalizedPageRank
Set the tolerance to a new value.
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the tolerance value.
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer
Setter for tolerance
setTolerance(double) - Method in interface gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizer
Sets the tolerance of the minimization algorithm
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolator
Setter for tolerance
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
Sets the minimum tolerance before iterations complete (must be non-negative).
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
Setter for tolerance
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer
Setter for tolerance
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
Setter for tolerance
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
Setter for tolerance
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder
 
setTolerance(double) - Method in class gov.sandia.cognition.learning.algorithm.root.MinimizerBasedRootFinder
 
setTolerance(double) - Method in interface gov.sandia.cognition.learning.algorithm.root.RootFinder
Sets the tolerance of the algorithm.
setTolerance(double) - Method in class gov.sandia.cognition.math.LentzMethod
Setter for tolerance
setTolerance(double) - Method in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner
Setter for tolerance
setTolerance(double) - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
Setter for tolerance
setToNativeBlas() - Method in class gov.sandia.cognition.math.matrix.custom.NativeBlasHandler
If native BLAS is available, this sets the BLAS library to use the native version.
setTopicCount(int) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
Sets the number of topics (k) created by the topic model.
setTopicTermProbabilities(double[][]) - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler.Result
Sets the document-topic probabilities, which are often called the theta model parameters.
setTotalChange(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Gets the total change in weight from the most recent step of the algorithm.
setTotalCount(int) - Method in class gov.sandia.cognition.text.term.DefaultTermCounts
Sets the total count.
setTournamentSize(int) - Method in class gov.sandia.cognition.learning.algorithm.genetic.selector.TournamentSelector
Sets the size for tournaments.
setTrainingPercent(double) - Method in class gov.sandia.cognition.learning.data.RandomDataPartitioner
Sets the percentage of data to put in the training partition.
setTrainingSet(Collection<DataType>) - Method in class gov.sandia.cognition.learning.data.DefaultPartitionedDataset
Sets the training set.
setTransform(Matrix) - Method in class gov.sandia.cognition.text.topic.LatentSemanticAnalysis.Transform
Gets the cached transform matrix.
setTransitionProbability(Matrix) - Method in class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain
Setter for transitionProbability.
setTreatmentCount(int) - Method in class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Setter for treatmentCount
setTrueNegativesCount(double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Sets the number of true negatives in the matrix.
setTrueNegativesRate(ConfidenceInterval) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Setter for trueNegativesRate
setTruePositivesCount(double) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix
Sets the number of true positives in the matrix.
setTruePositivesRate(ConfidenceInterval) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval
Setter for truePositivesRate
setTrueValue(Number) - Method in class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter
Sets the number that represents a true value.
setType(ProcessLauncherEvent.EventType) - Method in class gov.sandia.cognition.io.ProcessLauncherEvent
Setter for type
setU(Matrix) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition
setter for left singular vectors
setU(double) - Method in class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Setter for U
setUnlabeledWeight(double) - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry
Sets the unlabeled weight.
setUnpredictedErrorFraction(double) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Setter for unpredictedErrorFraction
setUnsortedEigenDecomposition(ComplexNumber[], Matrix, Matrix) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
Creates a new eigendecomposition using the given eigenvalues and eigenvectors...
setUpdateBias(boolean) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner
Sets whether or not the algorithm is updating the bias.
setUpdater(ParticleFilter.Updater<ObservationType, ParameterType>) - Method in class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter
Setter for updater
setUpdater(DirichletProcessMixtureModel.Updater<ObservationType>) - Method in class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel
Setter for updater
setUpdater(ImportanceSampling.Updater<ObservationType, ParameterType>) - Method in class gov.sandia.cognition.statistics.bayesian.ImportanceSampling
Setter for updater
setUpdater(MetropolisHastingsAlgorithm.Updater<ObservationType, ParameterType>) - Method in class gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm
Sets the object that makes proposal samples from the current location.
setUpdater(RejectionSampling.Updater<ObservationType, ParameterType>) - Method in class gov.sandia.cognition.statistics.bayesian.RejectionSampling
Setter for updater
setUpperBound(InputOutputSlopeTriplet) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.LineBracket
Setter for upperBound
setUpperBound(double) - Method in class gov.sandia.cognition.statistics.method.ConfidenceInterval
Setter for upperBound
setUpperLeft(Quadtree<DataType>.Node) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the upper-left child.
setUpperRight(Quadtree<DataType>.Node) - Method in class gov.sandia.cognition.math.geometry.Quadtree.Node
Sets the upper-right child.
setUsePseudoInverse(boolean) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearBasisRegression
Setter for usePseudoInverse
setUsePseudoInverse(boolean) - Method in class gov.sandia.cognition.learning.algorithm.regression.LinearRegression
Setter for usePseudoInverse
setUsePseudoInverse(boolean) - Method in class gov.sandia.cognition.learning.algorithm.regression.MultivariateLinearRegression
Setter for usePseudoInverse
setUtest(MannWhitneyUConfidence.Statistic) - Method in class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic
Setter for Utest
setV1(double) - Method in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
Setter for v1
setV2(double) - Method in class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
Setter for v2
setValid(boolean) - Method in class gov.sandia.cognition.io.ReaderTokenizer
Setter for valid
setValidationData(DataType) - Method in class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
Sets the validation dataset.
setValidBracket(boolean) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
Setter for validBracket
setValue(double) - Method in class gov.sandia.cognition.collection.AbstractLogNumberMap.SimpleEntry
 
setValue(double) - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntry
 
setValue(double) - Method in interface gov.sandia.cognition.collection.ScalarMap.Entry
Sets the value associated with the key.
setValue(ValueType) - Method in class gov.sandia.cognition.learning.algorithm.baseline.ConstantLearner
Sets the value that is the result of learning.
setValue(double) - Method in class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeNode
Sets the value stored at the node, which is usually the mean value.
setValue(ValueType) - Method in class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair
Sets the value.
setValue(OutputType) - Method in class gov.sandia.cognition.learning.function.ConstantEvaluator
Sets the constant output value for the evaluator.
setValue(double) - Method in class gov.sandia.cognition.math.LogNumber
Sets the value represented by the log number.
setValue(double) - Method in interface gov.sandia.cognition.math.matrix.MatrixEntry
Sets the value to which this entry points
setValue(double) - Method in interface gov.sandia.cognition.math.matrix.VectorSpace.Entry
Sets the value to which this entry points
setValue(double) - Method in class gov.sandia.cognition.math.MutableDouble
Sets the value stored in the object.
setValue(int) - Method in class gov.sandia.cognition.math.MutableInteger
Sets the value stored in the object.
setValue(long) - Method in class gov.sandia.cognition.math.MutableLong
Sets the value stored in the object.
setValue(double) - Method in class gov.sandia.cognition.math.UnsignedLogNumber
Sets the value represented by the log number.
setValue(Double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator.Parameter
 
setValue(Double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator.Parameter
 
setValue(Double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator.Parameter
 
setValue(Double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator.Parameter
 
setValue(Vector) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator.Parameter
 
setValue(Vector) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator.Parameter
 
setValue(Matrix) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator.Parameter
 
setValue(Double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator.Parameter
 
setValue(Double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator.Parameter
 
setValue(Double) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator.Parameter
 
setValue(Vector) - Method in class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator.Parameter
 
setValue(ParameterType) - Method in class gov.sandia.cognition.statistics.DefaultDistributionParameter
 
setValue(ParameterType) - Method in interface gov.sandia.cognition.statistics.DistributionParameter
Sets the value of the parameter.
setValue(ValueType) - Method in class gov.sandia.cognition.util.DefaultIdentifiedValue
Sets the value.
setValue(ValueType) - Method in class gov.sandia.cognition.util.DefaultKeyValuePair
Sets the value element of the pair.
setValue(ValueType) - Method in class gov.sandia.cognition.util.DefaultNamedValue
Sets the value stored in the name-value pair.
setValue(ValueType) - Method in class gov.sandia.cognition.util.DefaultTemporalValue
Sets the value.
setValue(ValueType) - Method in class gov.sandia.cognition.util.DefaultWeightedValue
Sets the value.
setValueMap(Map<InputType, OutputType>) - Method in class gov.sandia.cognition.evaluator.ValueMapper
Sets the map of input values to output values.
setValues(List<InputType>) - Method in class gov.sandia.cognition.data.convert.vector.UniqueBooleanVectorEncoder
Sets the list of unique values that the encoder is to use.
setValues(Vector) - Method in class gov.sandia.cognition.framework.lite.VectorBasedCognitiveModelInput
Setter for values
setValues(Collection<ValueType>) - Method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator
Sets the values that the divergence is computed from using the divergence function to the input.
setVariance(double) - Method in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
Sets the variance.
setVariance(Vector) - Method in class gov.sandia.cognition.learning.function.categorization.DiagonalConfidenceWeightedBinaryCategorizer
Sets the variance vector.
setVariance(double) - Method in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
Setter for variance
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.data.convert.vector.AbstractToVectorEncoder
Sets the vector factory used by this encoder.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.AbstractOnlineLinearBinaryCategorizerLearner
Sets the VectorFactory used to create the weight vector.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
Sets the VectorFactory used to create the weight vector.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron
Sets the VectorFactory used to create the weight vector.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.OnlineVotedPerceptron
Sets the VectorFactory used to create the weight vector.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
Sets the VectorFactory used to create the weight vector.
setVectorFactory(VectorFactory<? extends Vector>) - Method in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
Sets the vector factory.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.data.feature.FeatureHashing
Sets the vector factory to use.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.data.feature.RandomSubspace
Sets the vector factory to use.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer.Learner
Sets the vector factory.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator.Learner
Sets the vector factory to use.
setVectorFactory(VectorFactory<?>) - Method in class gov.sandia.cognition.learning.function.vector.VectorizableVectorConverterWithBias
Sets the vector factory used to create the vector with the bias.
setVectorFactory(VectorFactory<? extends Vector>) - Method in class gov.sandia.cognition.math.matrix.DefaultVectorFactoryContainer
Sets the vector factory for the object to use to create new vectors.
setVectorFactory(VectorFactory<? extends Vector>) - Method in class gov.sandia.cognition.text.term.vector.weighter.global.AbstractGlobalTermWeighter
Sets the vector factory.
setVectorFactory(VectorFactory<? extends Vector>) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
Sets the vector factory to use.
setVectorFunction(Evaluator<? super InputType, Vector>) - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionLinearDiscriminant
Setter for vectorFunction
setVectorFunction(Evaluator<? super InputType, ? extends Vectorizable>) - Method in class gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction
Sets the vector function with a one-dimensional output that is being converted to a scalar function.
setVectorOffset(Vector) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
Point to use as input to vectorFunction
setVectorScalarFunction(Evaluator<? super Vector, ? extends Double>) - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction
Setter for vectorScalarFunction
setVoteOutOfBagOnly(boolean) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
Sets whether during learning ensemble members can only vote on items that they are not in their bag (training set).
setVtranspose(Matrix) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractSingularValueDecomposition
sets the transpose of the right singular vectors matrix
setW(double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets the w component of the quaternion.
setWeakLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, Boolean>>, ? extends Evaluator<? super InputType, ? extends Boolean>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
Sets the weak learner that is passed the weighted training data on each step of the algorithm.
setWeakLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType, CategoryType>>, ? extends Evaluator<? super InputType, ? extends CategoryType>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost
Sets the weak learner that is passed the weighted training data on each step of the algorithm.
setWeight(double) - Method in class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair
Sets the weight for the pair.
setWeight(double) - Method in class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair
Sets the weight.
setWeight(double) - Method in class gov.sandia.cognition.learning.function.kernel.WeightedKernel
Sets the weight used to rescale the kernel's results.
setWeight(double) - Method in class gov.sandia.cognition.util.AbstractWeighted
Setter for weight
setWeight(double) - Method in class gov.sandia.cognition.util.DefaultWeightedPair
Gets the weight of the pair.
setWeightConverter(CogxelConverter<Double>) - Method in class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter
Setter for weightConverter
setWeightedData(ArrayList<DefaultWeightedInputOutputPair<InputType, Boolean>>) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
Sets the weighted version of the data.
setWeightPrior(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
Setter for weightPrior
setWeightPrior(MultivariateGaussian) - Method in class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression
Setter for weightPrior
setWeightRegularization(double) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
Sets the value for the parameter controlling the linear weight regularization.
setWeights(Vector) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine
Sets the weight vector.
setWeights(Vector) - Method in class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer
Sets the weight vector.
setWeights(Vector) - Method in class gov.sandia.cognition.learning.function.distance.WeightedEuclideanDistanceMetric
Sets the vector of weights for each dimension.
setWeights(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.LinearVectorScalarFunction
Sets the weight vector.
setWeightsEnabled(boolean) - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner
Sets whether or not the linear weight term is enabled.
setWeightUpdate(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Winnow
Sets the multiplicative weight update term.
setWeightVector(Vector) - Method in class gov.sandia.cognition.learning.function.scalar.LinearDiscriminant
Setter for weightVector
setWithinClusterDivergenceFunction(WithinClusterDivergence<? super ClusterType, ? super DataType>) - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
Sets the metric on clusters used for partitioning.
setWordCounts(DefaultDataDistribution<String>) - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Sets the dictionary of words counts.
setWords(Set<String>) - Method in class gov.sandia.cognition.text.term.filter.DefaultStopList
Sets the set of words in the stop list.
setWriter(Writer) - Method in class gov.sandia.cognition.math.matrix.MatrixWriter
Setter for writer
setWriter(Writer) - Method in class gov.sandia.cognition.math.matrix.VectorWriter
Setter for writer
setWXYZ(double, double, double, double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets all of the elements of the quaternion in w-x-y-z order.
setX(double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector1
 
setX(double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector2
 
setX(double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector3
 
setX(double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets the x component of the quaternion.
setX(double) - Method in interface gov.sandia.cognition.math.matrix.Vector1D
Sets the value of the first (and only) dimension (x).
setX(double) - Method in interface gov.sandia.cognition.math.matrix.Vector2D
Sets the value of the first dimension (x).
setX(double) - Method in interface gov.sandia.cognition.math.matrix.Vector3D
Sets the value of the first dimension (x).
setXY(double, double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector2
 
setXY(double, double) - Method in interface gov.sandia.cognition.math.matrix.Vector2D
Sets the value of both dimensions of the vector.
setXYZ(double, double, double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector3
 
setXYZ(double, double, double) - Method in interface gov.sandia.cognition.math.matrix.Vector3D
Sets the value of all three dimensions of this vector.
setXYZW(double, double, double, double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets all of the elements of the quaternion in x-y-z-w order.
setY(double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector2
 
setY(double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector3
 
setY(double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets the y component of the quaternion.
setY(double) - Method in interface gov.sandia.cognition.math.matrix.Vector2D
Sets the value of the second dimension (y).
setY(double) - Method in interface gov.sandia.cognition.math.matrix.Vector3D
Sets the value of the second dimension (y).
setZ(double) - Method in class gov.sandia.cognition.math.matrix.mtj.Vector3
 
setZ(double) - Method in interface gov.sandia.cognition.math.matrix.Quaternion
Sets the z component of the quaternion.
setZ(double) - Method in interface gov.sandia.cognition.math.matrix.Vector3D
Sets the value of the third dimension (z).
setZ(double) - Method in class gov.sandia.cognition.statistics.method.GaussianConfidence.Statistic
Getter for z
setZ(double) - Method in class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Setter for z
setZ(double) - Method in class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence.Statistic
Setter for z
SHA1Hash - Class in gov.sandia.cognition.hash
A Java implementation of the Secure Hash Algorithm, SHA-1, as defined in FIPS PUB 180-1.
SHA1Hash() - Constructor for class gov.sandia.cognition.hash.SHA1Hash
Default constructor
SHA256Hash - Class in gov.sandia.cognition.hash
The SHA-2, 256-bit (32 byte) hash function.
SHA256Hash() - Constructor for class gov.sandia.cognition.hash.SHA256Hash
Default constructor
SHA512Hash - Class in gov.sandia.cognition.hash
The SHA-2 512-bit (64-byte) hash function.
SHA512Hash() - Constructor for class gov.sandia.cognition.hash.SHA512Hash
Creates a new instance of SHA512Hash
ShafferStaticCorrection - Class in gov.sandia.cognition.statistics.method
The Shaffer Static Correction uses logical relationships to tighten up the Bonferroni/Sidak corrections when performing pairwise multiple hypothesis comparisons.
ShafferStaticCorrection() - Constructor for class gov.sandia.cognition.statistics.method.ShafferStaticCorrection
Default constructor
ShafferStaticCorrection(NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.ShafferStaticCorrection
Creates a new instance of BonferroniCorrection
ShafferStaticCorrection.Statistic - Class in gov.sandia.cognition.statistics.method
Test statistic from the Shaffer static multiple-comparison test
shape - Variable in class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution
Shape, similar to the beta parameter shape, must be greater than zero
shape - Variable in class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution
Shape parameter, must be greater than zero.
shape - Variable in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Scale parameter, must be greater than zero.
shape - Variable in class gov.sandia.cognition.statistics.distribution.WeibullDistribution
Shape parameter, must be greater than 0.0
shape - Variable in class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution
Shape parameter, must be greater than zero
ShareableCognitiveModuleSettings - Interface in gov.sandia.cognition.framework
The ShareableCognitiveModuleSettings is an interface for module settings that can be shared between two instances of a CognitiveModule.
SharedSemanticMemoryLite - Class in gov.sandia.cognition.framework.lite
The SharedSemanticMemoryLite class implements a semantic memory that uses a shared piece of memory to store the settings.
SharedSemanticMemoryLite(SemanticIdentifierMap, SharedSemanticMemoryLiteSettings) - Constructor for class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLite
Creates a new instance of SharedSemanticMemoryLite.
SharedSemanticMemoryLiteFactory - Class in gov.sandia.cognition.framework.lite
The SharedSemanticMemoryLiteFactory implements a CognitiveModuleFactory for SharedSemanticMemoryLite modules.
SharedSemanticMemoryLiteFactory(PatternRecognizerLite) - Constructor for class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteFactory
Creates a new instance of SharedSemanticMemoryLiteFactory.
SharedSemanticMemoryLiteSettings - Class in gov.sandia.cognition.framework.lite
The SharedSemanticMemoryLiteSettings class implements the settings for the SharedSemanticMemoryLite module.
SharedSemanticMemoryLiteSettings(PatternRecognizerLite) - Constructor for class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteSettings
Creates a new instance of SharedSemanticMemoryLiteSettings.
shift - Variable in class gov.sandia.cognition.statistics.distribution.ParetoDistribution
Amount to shift the distribution to the left.
shouldSplit(Quadtree<DataType>.Node) - Method in class gov.sandia.cognition.math.geometry.Quadtree
Determines if a given node should be split.
shouldStop - Variable in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
If set to true, the algorithm will stop after the current iteration completes.
shouldUpdate(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron.LinearSoftMargin
 
shouldUpdate(double) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron
Determine if an update should be made.
shrink(Forgetron.Result<InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Greedy
 
shrink(Forgetron.Result<InputType>) - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron
Apply the shrinking step of the algorithm.
SidakCorrection - Class in gov.sandia.cognition.statistics.method
The Sidak correction takes a pair-wise null-hypothesis test and generalizes it to multiple comparisons by adjusting the requisite p-value to find significance as alpha / NumComparisons.
SidakCorrection() - Constructor for class gov.sandia.cognition.statistics.method.SidakCorrection
Creates a new instance of SidakCorrection
SidakCorrection(NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.SidakCorrection
Creates a new instance of SidakCorrection
Sigma - Variable in class gov.sandia.cognition.math.matrix.custom.DenseMatrix.SVD
* The singular value diagonal matrix.
SigmoidFunction - Class in gov.sandia.cognition.learning.function.scalar
An implementation of a sigmoid squashing function.
SigmoidFunction() - Constructor for class gov.sandia.cognition.learning.function.scalar.SigmoidFunction
Creates a new instance of SigmoidFunction
SigmoidKernel - Class in gov.sandia.cognition.learning.function.kernel
The SigmoidKernel class implements a sigmoid kernel based on the hyperbolic tangent.
SigmoidKernel() - Constructor for class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
Creates a new instance of SigmoidKernel with default values of 1.0 for kappa and 0.0 for the constant.
SigmoidKernel(double, double) - Constructor for class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
Creates a new instance of SigmoidKernel from its two needed parameters: kappa and a constant.
SigmoidKernel(SigmoidKernel) - Constructor for class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
Creates a new copy of a SigmoidKernel.
similarities - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
The array of example-example similarities.
similarities - Variable in class gov.sandia.cognition.text.term.relation.MatrixBasedTermSimilarityNetwork
The similarities between terms.
similarity - Variable in class gov.sandia.cognition.text.term.relation.IndexedTermSimilarityRelation
The similarity between the two terms.
SimilarityFunction<FromType,ToType> - Interface in gov.sandia.cognition.text.relation
Defines the functionality of a similarity function that computes the similarity between two objects.
similarityFunction - Variable in class gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator
The similarity function between term vectors used to determine the similarity between two terms.
SimpleEntry(KeyType, LogNumber) - Constructor for class gov.sandia.cognition.collection.AbstractLogNumberMap.SimpleEntry
Creates a new instance of SimpleEntry
SimpleEntry(KeyType, MutableDouble) - Constructor for class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntry
Creates a new instance of SimpleEntry
SimpleEntrySet(Map<KeyType, LogNumber>) - Constructor for class gov.sandia.cognition.collection.AbstractLogNumberMap.SimpleEntrySet
Creates a new instance of SimpleEntrySet
SimpleEntrySet(Map<KeyType, MutableDouble>) - Constructor for class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntrySet
Creates a new instance of SimpleEntrySet
SimpleIterator(Iterator<? extends Map.Entry<KeyType, LogNumber>>) - Constructor for class gov.sandia.cognition.collection.AbstractLogNumberMap.SimpleIterator
Default constructor
SimpleIterator(Iterator<? extends Map.Entry<KeyType, MutableDouble>>) - Constructor for class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleIterator
Default constructor
SimpleIterator() - Constructor for class gov.sandia.cognition.math.matrix.DefaultInfiniteVector.SimpleIterator
Default constructor
SimplePatternRecognizer - Class in gov.sandia.cognition.framework.lite
The SimplePatternRecognizer class implements a simple version of the PatternRecognizerLite interface.
SimplePatternRecognizer() - Constructor for class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Creates a new, empty instance of SimplePatternRecognizer.
SimplePatternRecognizer(SemanticNetwork) - Constructor for class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Creates a new instance of SimplePatternRecognizer.
SimplePatternRecognizer(SimplePatternRecognizer) - Constructor for class gov.sandia.cognition.framework.lite.SimplePatternRecognizer
Creates a new instance of SimplePatternRecognizer.
SimplePatternRecognizerState - Class in gov.sandia.cognition.framework.lite
The SimplePatternRecognizerState class implements a CognitiveModuleState for the SimplePatternRecognizer.
SimplePatternRecognizerState(Collection<SemanticLabel>) - Constructor for class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState
Creates a new instance of SimplePatternRecognizerState.
SimplePatternRecognizerState(Collection<SemanticLabel>, Vector) - Constructor for class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState
Creats a new instance of SimplePatternRecognizerState.
SimplePatternRecognizerState(Collection<SemanticLabel>, Vector, boolean) - Constructor for class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState
Creats a new instance of SimplePatternRecognizerState.
SimplePatternRecognizerState(SimplePatternRecognizerState) - Constructor for class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState
Creats a new instance of SimplePatternRecognizerState.
SimpleStatisticalSpellingCorrector - Class in gov.sandia.cognition.text.spelling
A simple statistical spelling corrector based on word counts that looks at possible one and two-character edits.
SimpleStatisticalSpellingCorrector() - Constructor for class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Creates a new, default SimpleStatisticalSpellingCorrector with a default alphabet.
SimpleStatisticalSpellingCorrector(char[]) - Constructor for class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Creates a new SimpleStatisticalSpellingCorrector with a given alphabet.
SimpleStatisticalSpellingCorrector(DefaultDataDistribution<String>, char[]) - Constructor for class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
Creates a new SimpleStatisticalSpellingCorrector.
SimpleStatisticalSpellingCorrector.Learner - Class in gov.sandia.cognition.text.spelling
A learner for the SimpleStatisticalSpellingCorrector.
SimulatedAnnealer<CostParametersType,AnnealedType> - Class in gov.sandia.cognition.learning.algorithm.annealing
The SimulatedAnnealer class implements the simulated annealing algorithm using the provided cost function and perturbation function.
SimulatedAnnealer(AnnealedType, Perturber<AnnealedType>, CostFunction<? super AnnealedType, ? super CostParametersType>) - Constructor for class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Creates a new instance of SimulatedAnnealer.
SimulatedAnnealer(AnnealedType, Perturber<AnnealedType>, CostFunction<? super AnnealedType, ? super CostParametersType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Creates a new instance of SimulatedAnnealer.
SimulatedAnnealer(AnnealedType, Perturber<AnnealedType>, CostFunction<? super AnnealedType, ? super CostParametersType>, int, int) - Constructor for class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Creates a new instance of SimulatedAnnealer.
SingleDocumentExtractor - Interface in gov.sandia.cognition.text.document.extractor
Interface for a DocumentExtractor that only extracts a single document from a file.
SingleTermFilter - Interface in gov.sandia.cognition.text.term.filter
Interface for a term filter that looks at each term individually.
SingleTextualConverter<InputType,OutputType extends Textual> - Interface in gov.sandia.cognition.text.convert
Interface for an TextConverter that converts an input into a single output.
SingleToMultiTextualConverterAdapter<InputType,OutputType extends Textual> - Class in gov.sandia.cognition.text.convert
Adapts a SingleTextualConverter to work within the interface of an MultiTextualConverter.
SingleToMultiTextualConverterAdapter() - Constructor for class gov.sandia.cognition.text.convert.SingleToMultiTextualConverterAdapter
Creates a new SingleToMultiTextualConverterAdapter with no internal converter.
SingleToMultiTextualConverterAdapter(SingleTextualConverter<? super InputType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.text.convert.SingleToMultiTextualConverterAdapter
Creates a new SingleToMultiTextualConverterAdapter with the given internal converter.
SingularValueDecomposition - Interface in gov.sandia.cognition.math.matrix.decomposition
Interface that describes the operations of all SingularValueDecompositions
SingularValueDecompositionMTJ - Class in gov.sandia.cognition.math.matrix.mtj.decomposition
Full singular-value decomposition, based on MTJ's SVD.
singularValues - Variable in class gov.sandia.cognition.text.topic.LatentSemanticAnalysis.Transform
The diagonal matrix of singular values.
size() - Method in class gov.sandia.cognition.collection.AbstractLogNumberMap.SimpleEntrySet
 
size() - Method in class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntrySet
 
size() - Method in class gov.sandia.cognition.collection.AbstractScalarMap
 
size(Collection<?>) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Determines the size of the given collection, checking for null.
size(Iterable<?>) - Static method in class gov.sandia.cognition.collection.CollectionUtil
Determines the size of the given iterable.
size() - Method in class gov.sandia.cognition.collection.DefaultIndexer
 
size() - Method in class gov.sandia.cognition.collection.DefaultMultiCollection
 
size() - Method in class gov.sandia.cognition.collection.DynamicArrayMap
Runs in O(1).
size() - Method in class gov.sandia.cognition.collection.FiniteCapacityBuffer
 
size() - Method in interface gov.sandia.cognition.collection.Indexer
Gets the number of items in the index.
size() - Method in class gov.sandia.cognition.collection.IntegerSpan
 
size() - Method in interface gov.sandia.cognition.collection.NumericMap
Gets the number of items in the map.
size() - Method in class gov.sandia.cognition.collection.RangeExcludedArrayList
 
size - Variable in class gov.sandia.cognition.learning.data.feature.RandomSubspace
The size of the random subspace to create, which is the number of dimensions that are chosen.
size - Variable in class gov.sandia.cognition.math.Combinations.AbstractCombinationsIterator
 
size() - Method in class gov.sandia.cognition.math.Combinations
 
size() - Method in class gov.sandia.cognition.math.geometry.KDTree.Neighborhood
 
size() - Method in class gov.sandia.cognition.math.geometry.KDTree
 
size() - Method in class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.Domain
 
size - Variable in class gov.sandia.cognition.text.term.filter.NGramFilter
The size of the n-gram.
slope - Variable in class gov.sandia.cognition.learning.function.scalar.LinearFunction
The slope (m).
SmoothCumulativeDistributionFunction - Interface in gov.sandia.cognition.statistics
This defines a CDF that has an associated derivative, which is its PDF.
smoothedErrorRates - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
The smoothed out-of-bag error rates, per iteration.
smoothingBuffer - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
The buffer used for smoothing.
smoothingWindowSize - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
The size of window of data to look at to determine if learning has hit a minimum.
SmoothUnivariateDistribution - Interface in gov.sandia.cognition.statistics
A closed-form scalar distribution that is also smooth.
SnedecorFDistribution - Class in gov.sandia.cognition.statistics.distribution
CDF of the Snedecor F-distribution (also known as Fisher F-distribution, Fisher-Snedecor F-distribution, or just plain old F-distribution).
SnedecorFDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
Default constructor
SnedecorFDistribution(double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
Creates a new instance of CumulativeDistribution
SnedecorFDistribution(SnedecorFDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution
Copy Constructor
SnedecorFDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
CDF of the F-distribution.
SoftPlusFunction - Class in gov.sandia.cognition.learning.function.scalar
A smoothed approximation for rectified linear unit.
SoftPlusFunction() - Constructor for class gov.sandia.cognition.learning.function.scalar.SoftPlusFunction
Creates a new SoftPlusFunction.
SoftwareLicenseType - Enum in gov.sandia.cognition.annotation
An enumeration of common types of software licenses.
SoftwareReference - Annotation Type in gov.sandia.cognition.annotation
Describes a reference to software.
SoftwareReferences - Annotation Type in gov.sandia.cognition.annotation
The SoftwareReferences annotation defines a container for one or more references to a publication.
solve() - Method in interface gov.sandia.cognition.graph.inference.EnergyFunctionSolver
Solves for the energy function passed in during initialize, e.g., compute the beliefs.
solve() - Method in class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
 
solve(Matrix) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
solve(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
 
solve(Matrix) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
solve(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix
 
solve(Matrix) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Solves for "X" in the equation: this*X = B
solve(Vector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Solves for "x" in the equation: this*x = b
solve(Matrix) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Solves for "X" in the equation: this*X = B
solve(Vector) - Method in interface gov.sandia.cognition.math.matrix.Matrix
Solves for "x" in the equation: this*x = b
solve(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
solve(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
 
solve(AbstractMTJMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
Solves for "X" in the equation this * X = B, where X is a DenseMatrix, "this" and "B" will be converted to a DenseMatrix (if not already)
solve(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix
Solves for "x" in the equation: this*x = b
solve(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix
This sparse-vector solver performs iterative solving for "x" in the equation: this*x = b, and the AbstractSparseMatrix "this" can be unstructured (e.g., asymmetric, indefinite, etc.)
solve(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
solve(Matrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
solve(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ
 
solveCommunities() - Method in class gov.sandia.cognition.graph.community.Louvain
Solves for community detection of the graph passed in during the constructor.
solveCommunities() - Method in class gov.sandia.cognition.graph.community.Permanence
Performs the actual permanence-maximization computation and returns the resulting partitioning.
solveInto(DenseMatrix, DenseMatrix) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Solve for "X" in the equation: this*X = B
solveInto(DenseVector, DenseVector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseMatrix
Solve for "x" in the equation: this*x = b
SolverFunction - Class in gov.sandia.cognition.learning.algorithm.root
Evaluator that allows RootFinders to solve for nonzero values by setting a "target" parameter.
SolverFunction() - Constructor for class gov.sandia.cognition.learning.algorithm.root.SolverFunction
Creates a new instance of SolverFunction
SolverFunction(double, Evaluator<Double, Double>) - Constructor for class gov.sandia.cognition.learning.algorithm.root.SolverFunction
Creates a new instance of SolverFunction
sortAndSetEigenDecomposition(ComplexNumber[], Matrix, Matrix) - Method in class gov.sandia.cognition.math.matrix.decomposition.AbstractEigenDecomposition
Sorts the eigendecomposition in descending order of the value of the magnitudes of the eigenvalues
sortArrayAscending(double[]) - Static method in class gov.sandia.cognition.util.ArrayIndexSorter
Returns the indices of the array sorted in ascending order
sortArrayDescending(double[]) - Static method in class gov.sandia.cognition.util.ArrayIndexSorter
Returns the indices of the array sorted in ascending order.
Sorter() - Constructor for class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.DataPoint.Sorter
 
source - Variable in class gov.sandia.cognition.text.relation.AbstractRelation
The source object of the relation.
sourceVectorPrior - Variable in class gov.sandia.cognition.statistics.TransferEntropy.TransferEntropyDistributionObject
The prior for the source vector.
SparseColumnMatrix - Class in gov.sandia.cognition.math.matrix.mtj
A sparse matrix, represented as a collection of sparse column vectors.
SparseColumnMatrix(int, int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix
Creates a new empty instance of SparseColumnMatrix.
SparseColumnMatrix(SparseColumnMatrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix
Copy constructor for SparseColumnMatrix matrices.
SparseColumnMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix
Copy constructor for general matrices, copies over nonzero values.
SparseColumnMatrix(FlexCompColMatrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix
Creates a SparseColumnMatrix based on the appropriate MTJ matrix, does NOT create a copy of internalMatrix.
SparseMatrix - Class in gov.sandia.cognition.math.matrix.custom
A sparse matrix implementation.
SparseMatrix(int, int) - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Creates a new sparse matrix with the specified number of rows and columns.
SparseMatrix(SparseMatrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Creates a new sparse matrix with the same dimensions and data as m (performs a deep copy).
SparseMatrix(DenseMatrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Creates a new sparse matrix with the same dimensions and data as d (performs a deep copy).
SparseMatrix(DiagonalMatrix) - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseMatrix
Creates a new sparse matrix with the same dimensions and data as d (performs a deep copy).
SparseMatrix() - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseMatrix
This should never be called by anything or anyone other than Java's serialization code.
SparseMatrix - Class in gov.sandia.cognition.math.matrix.mtj
A sparse matrix, represented as a collection of sparse row vectors.
SparseMatrix(int, int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseMatrix
Creates a new empty instance of SparseMatrix.
SparseMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseMatrix
Converts the given matrix to a SparseMatrix.
SparseMatrixFactoryMTJ - Class in gov.sandia.cognition.math.matrix.mtj
Factory for MTJ's flexible sparse row matrix
SparseMatrixFactoryMTJ() - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ
Creates a new instance of SparseMatrixFactoryMTJ
SparseRowMatrix - Class in gov.sandia.cognition.math.matrix.mtj
A sparse matrix, represented as a collection of sparse row vectors.
SparseRowMatrix(int, int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix
Creates a new empty instance of SparseRowMatrix.
SparseRowMatrix(SparseRowMatrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix
Copy constructor for SparseRowMatrix matrices
SparseRowMatrix(Matrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix
Copy constructor for general matrices, copies over nonzero values.
SparseRowMatrix(FlexCompRowMatrix) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix
Creates a SparseRowMatrix based on the appropriate MTJ matrix, does NOT create a copy of internalMatrix.
SparseVector - Class in gov.sandia.cognition.math.matrix.custom
Our sparse vector implementation.
SparseVector(int) - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseVector
Create a new sparse vector.
SparseVector(SparseVector) - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseVector
Copy constructor -- creates a deep copy of the input sparse vector.
SparseVector(DenseVector) - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseVector
Copy constructor -- creates a deep copy of the input sparse vector.
SparseVector() - Constructor for class gov.sandia.cognition.math.matrix.custom.SparseVector
This should never be called by anything or anyone other than Java's serialization code.
SparseVector - Class in gov.sandia.cognition.math.matrix.mtj
A vector that only stores the nonzero elements, relies on MTJ's SparseVector.
SparseVector(int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseVector
Creates a new instance of SparseVector with no initial size.
SparseVector(int, int) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseVector
Creates a new instance of SparseVector with a specified initial size.
SparseVector(SparseVector) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseVector
Creates a new copy of SparseVector.
SparseVector(Vector) - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseVector
Creates a new copy of SparseVector.
SparseVectorFactory<VectorType extends Vector> - Class in gov.sandia.cognition.math.matrix
Abstract factory class for creating sparse vectors.
SparseVectorFactory() - Constructor for class gov.sandia.cognition.math.matrix.SparseVectorFactory
 
SparseVectorFactoryMTJ - Class in gov.sandia.cognition.math.matrix.mtj
Factory for MTJ's SparseVector
SparseVectorFactoryMTJ() - Constructor for class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ
Creates a new instance of SparseVectorFactoryMTJ
split(String, char) - Static method in class gov.sandia.cognition.io.CSVUtility
Splits the given line into the array of character-separated values.
split(Quadtree<DataType>.Node) - Method in class gov.sandia.cognition.math.geometry.Quadtree
Splits the given node.
splitCommas(String) - Static method in class gov.sandia.cognition.io.CSVUtility
Splits the given line into the array of comma-separated values.
splitData(Collection<? extends InputOutputPair<? extends InputType, OutputType>>, Categorizer<? super InputType, ? extends DecisionType>) - Method in class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner
Splits the data into new lists based on the given decision function.
splitDatasets(Collection<? extends InputOutputPair<? extends DataType, Boolean>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Splits a dataset of input-output pair into two datasets, one for the inputs that have a "true" output and another for the inputs that have a "false" output
splitOnOutput(Iterable<? extends InputOutputPair<? extends InputType, ? extends CategoryType>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Splits a dataset according to its output value (usually a category) so that all the inputs for that category are given in a list.
splitThreshold - Variable in class gov.sandia.cognition.math.geometry.Quadtree
The minimum number of items allowed in a leaf node.
spreadValence() - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
This method solves the system of equations to determine the valence for all documents input and for all terms in those documents.
spreadValence(int) - Method in class gov.sandia.cognition.text.algorithm.ValenceSpreader
This method solves the system of equations to determine the valence for all documents input and for all terms in those documents.
SQRT2 - Static variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian
Square root of 2.0, 0.707...
SQRT2PI - Static variable in class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
Constant value of Math.sqrt(2*Math.PI)
stack(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
 
stack(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
stack(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
stack(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
stack(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
stack(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
 
stack(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
 
stack(Vector) - Method in interface gov.sandia.cognition.math.matrix.Vector
Stacks "other" below "this" and returns the stacked Vector
standardDeviation - Variable in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
The cached value of the standard deviation for normalization.
StandardDistributionNormalizer - Class in gov.sandia.cognition.learning.data.feature
The StandardDistributionNormalizer class implements a normalization method where a real value is converted onto a standard distribution.
StandardDistributionNormalizer() - Constructor for class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
Creates a new instance of StandardNormalization with a mean of 0.0 and a variance of 1.0.
StandardDistributionNormalizer(double, double) - Constructor for class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
Creates a new instance of StandardDistributionNormalizer with the given mean and variance.
StandardDistributionNormalizer(UnivariateGaussian) - Constructor for class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
Creates a new instance of StandardDistributionNormalizer from the given Gaussian.
StandardDistributionNormalizer(StandardDistributionNormalizer) - Constructor for class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer
Creates a new copy of a StandardDistributionNormalizer.
StandardDistributionNormalizer.Learner - Class in gov.sandia.cognition.learning.data.feature
The Learner class implements a BatchLearner object for a StandardDistributionNormalizer.
standardErrors - Variable in class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic
Gets the standard errors in the experiment
start - Variable in class gov.sandia.cognition.text.AbstractOccurrenceInText
The starting point of the occurrence.
state - Variable in class gov.sandia.cognition.framework.lite.AbstractCognitiveModelLite
The current state of the model.
State() - Constructor for class gov.sandia.cognition.math.signals.PIDController.State
Default constructor.
State(double, double) - Constructor for class gov.sandia.cognition.math.signals.PIDController.State
Creates a new instance of State
state - Variable in class gov.sandia.cognition.statistics.TransferEntropy.TransferEntropyPartialSumObject
The state.
stateBeliefs(Collection<? extends ObservationType>) - Method in class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel
Computes the probability distribution over all states for each observation.
StatefulEvaluator<InputType,OutputType,StateType extends CloneableSerializable> - Interface in gov.sandia.cognition.evaluator
The StatefulEvaluator interface defines the functionality of an Evaluator that maintains an internal state.
StatefulEvaluatorBasedCognitiveModule<InputType,OutputType> - Class in gov.sandia.cognition.framework.learning
The StatefulEvaluatorBasedCognitiveModule implements a CognitiveModule that wraps a StatefulEvaluator object.
StatefulEvaluatorBasedCognitiveModule(CognitiveModel, EvaluatorBasedCognitiveModuleSettings<InputType, OutputType>, String) - Constructor for class gov.sandia.cognition.framework.learning.StatefulEvaluatorBasedCognitiveModule
Creates a new instance of StatefulEvaluatorBasedCognitiveModule.
StateObservationLikelihoodTask() - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.StateObservationLikelihoodTask
Default constructor.
stateObservationLikelihoodTasks - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
StateObservationLikelihoodTasks
stationaryPoints() - Method in interface gov.sandia.cognition.learning.function.scalar.PolynomialFunction.ClosedForm
Finds the real-valued stationary points (zero slope) maxima or minima of the polynomial
stationaryPoints() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic
 
stationaryPoints(double, double, double, double) - Static method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic
Finds the stationary point of the quadratic equation.
stationaryPoints() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear
 
stationaryPoints() - Method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Quadratic
Finds the real-valued stationary points (zero-derivatives) of the quadratic.
stationaryPoints(double, double, double) - Static method in class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Quadratic
Finds the stationary point of the quadratic equation.
Statistic(Collection<Double>, Collection<Double>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Creates a new instance of Statistic
Statistic(Collection<Double>, Collection<Double>, Collection<Double>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic
Creates a new instance of Statistic
Statistic() - Constructor for class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic
Default constructor
Statistic(Collection<? extends Collection<? extends Number>>, double, NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic
Creates a new instance of StudentizedMultipleComparisonStatistic
Statistic(double, double, double) - Constructor for class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay.Statistic
Creates a new instance of Statistic
Statistic(double, double) - Constructor for class gov.sandia.cognition.statistics.method.ChiSquareConfidence.Statistic
Creates a new instance of chiSquare
Statistic(int, int) - Constructor for class gov.sandia.cognition.statistics.method.FisherSignConfidence.Statistic
Creates a new instance of Statistic
Statistic(int, int, ArrayList<Double>) - Constructor for class gov.sandia.cognition.statistics.method.FriedmanConfidence.Statistic
Creates a new instance of Statistic
Statistic(int, int, ArrayList<Double>, double) - Constructor for class gov.sandia.cognition.statistics.method.FriedmanConfidence.Statistic
Creates a new instance of Statistic
Statistic(int, int, ArrayList<Double>, double, double) - Constructor for class gov.sandia.cognition.statistics.method.FriedmanConfidence.Statistic
Creates a new instance of Statistic
Statistic(double) - Constructor for class gov.sandia.cognition.statistics.method.GaussianConfidence.Statistic
Creates a new instance of Statistic
Statistic(Collection<? extends Collection<? extends Number>>, double, NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.HolmCorrection.Statistic
Creates a new instance of Statistic
Statistic(double, double) - Constructor for class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence.Statistic
Creates a new instance of Statistic
Statistic(double, int, double, int) - Constructor for class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Creates a new instance of Statistic
Statistic(MannWhitneyUConfidence.Statistic) - Constructor for class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic
Copy Constructor
Statistic(ConfidenceStatistic, MultipleHypothesisComparison.Statistic) - Constructor for class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment.Statistic
Creates a new instance of Statistic
Statistic(double, int, ArrayList<Double>, double) - Constructor for class gov.sandia.cognition.statistics.method.NemenyiConfidence.Statistic
Creates a new instance of StudentizedMultipleComparisonStatistic
Statistic(ReceiverOperatingCharacteristic) - Constructor for class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic
Creates a new instance of Statistic
Statistic(Collection<? extends Collection<? extends Number>>, double, NullHypothesisEvaluator<Collection<? extends Number>>) - Constructor for class gov.sandia.cognition.statistics.method.ShafferStaticCorrection.Statistic
Creates a new instance of Statistic
Statistic(double, double) - Constructor for class gov.sandia.cognition.statistics.method.StudentTConfidence.Statistic
Creates a new instance of Statistic
Statistic(StudentTConfidence.Statistic) - Constructor for class gov.sandia.cognition.statistics.method.StudentTConfidence.Statistic
Copy Constructor
Statistic(double, ArrayList<Integer>, ArrayList<Double>, double) - Constructor for class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic
Creates a new instance of Statistic
Statistic(double, int) - Constructor for class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence.Statistic
Creates a new instance of Statistic
statistics - Variable in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
The performance evaluations made during the experiment.
statistics - Variable in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
The performance evaluations made during the experiment.
statistics - Variable in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
The performance evaluations made during the experiment.
statistics - Variable in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
The performance evaluations made during the experiment.
StatusPrinter() - Constructor for class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.StatusPrinter
Creates a new StatusPrinter writing to System.out.
StatusPrinter(PrintStream) - Constructor for class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.StatusPrinter
Creates a new StatusPrinter writing to the given stream.
SteepestDescentMatrixSolver - Class in gov.sandia.cognition.learning.algorithm.minimization.matrix
Implements a basic Steepest Descent iterative solver for linear systems of equations.
SteepestDescentMatrixSolver(Vector, Vector) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver
Initializes a steepest-descent solver with the minimum values
SteepestDescentMatrixSolver(Vector, Vector, double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver
Initializes a steepest-descent solver with some additional parameters
SteepestDescentMatrixSolver(Vector, Vector, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver
Initializes a steepest-descent solver with all user-definable parameters
stem(String) - Static method in class gov.sandia.cognition.text.term.filter.stem.PorterEnglishStemmingFilter
Stems the given String according to the Porter stemming algorithm for English words.
step() - Method in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
Called to take a single step of the learning algorithm.
step() - Method in class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer
Takes one step in the Simulated Annealing process.
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
 
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer
 
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer
 
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
Do a step of the clustering algorithm.
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.KMeansClustererWithRemoval
 
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer
Do a step of the clustering algorithm.
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer
 
step() - Method in class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer
 
step() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner
 
step() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost
 
step() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner
 
step() - Method in class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost
 
step() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares
 
step() - Method in class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineStochasticGradient
 
step() - Method in class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm
 
step() - Method in class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm
 
step() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient
 
step() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell
 
step() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent
Called to take a single step of the learning algorithm.
step() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead
 
step() - Method in class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton
 
step() - Method in class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer
 
step(InputOutputPair<Double, Double>, InputOutputPair<Double, Double>, double) - Static method in class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorGoldenSection
Takes a Golden Section step between the two points
step() - Method in class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm
 
step() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron
 
step() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
 
step() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
 
step() - Method in class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron
 
step() - Method in class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation
 
step() - Method in class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm
 
step() - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
 
step() - Method in class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
 
step() - Method in class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation
 
step() - Method in class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression
 
step() - Method in class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander
 
step() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderBisectionMethod
 
step() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderFalsePositionMethod
 
step() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderNewtonsMethod
 
step() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderRiddersMethod
 
step() - Method in class gov.sandia.cognition.learning.algorithm.root.RootFinderSecantMethod
 
step() - Method in class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient
 
step() - Method in class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization
 
step() - Method in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
 
step() - Method in class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo
 
step() - Method in class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner
 
step() - Method in class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner
 
step() - Method in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
 
step() - Method in class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler
 
step(Vector, Matrix, Vector) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.Result
Take a step of the expectation-maximization algorithm for computing the probability of the query given each latent variable.
step() - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis
 
STEP_MAX - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking
Maximum step size allowed by a parabolic fit, 100.0
STEP_MAX - Static variable in class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeFree
Maximum step size allowed by a parabolic fit, 100.0.
STEP_MAX - Static variable in class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm
Maximum step norm allowed under a Gauss-Newton step, 100.0
stepEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
 
stepEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener
 
stepEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter
 
stepEnded(IterativeAlgorithm) - Method in interface gov.sandia.cognition.algorithm.IterativeAlgorithmListener
This method is called when the algorithm has ended a step of its execution.
stepEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
 
stepEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner.OutOfBagErrorStoppingCriteria
 
stepEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
 
stepEnded(IterativeAlgorithm) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.StatusPrinter
 
stepStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
 
stepStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener
 
stepStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.algorithm.event.IterationStartReporter
 
stepStarted(IterativeAlgorithm) - Method in interface gov.sandia.cognition.algorithm.IterativeAlgorithmListener
This method is called when the algorithm has started a step in its execution.
stepStarted(IterativeAlgorithm) - Method in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.StatusPrinter
 
stop() - Method in class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper
 
stop() - Method in interface gov.sandia.cognition.algorithm.StoppableAlgorithm
Requests that the algorithm stop at the next appropriate point.
stop() - Method in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
 
stop() - Method in class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver
Execution will stop after the current iteration completes.
stop() - Method in class gov.sandia.cognition.math.LentzMethod
 
StopList - Interface in gov.sandia.cognition.text.term.filter
Interface for a list of stop words.
stopList - Variable in class gov.sandia.cognition.text.term.filter.StopListFilter
The stop list for the filter to use.
StopListFilter - Class in gov.sandia.cognition.text.term.filter
A term filter that rejects any term that appears in a given stop list.
StopListFilter() - Constructor for class gov.sandia.cognition.text.term.filter.StopListFilter
Creates a new StopListFilter.
StopListFilter(StopList) - Constructor for class gov.sandia.cognition.text.term.filter.StopListFilter
Creates a new StopListFilter with the given stop list.
StoppableAlgorithm - Interface in gov.sandia.cognition.algorithm
Defines methods for an algorithm that can be stopped early during its execution.
stopProcess() - Method in class gov.sandia.cognition.io.ProcessLauncher
Stops the process.
Stoptron<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
An online, budgeted, kernel version of the Perceptron algorithm that stops learning once it has reached its budget.
Stoptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Stoptron
Creates a new Stoptron with default parameters and a null kernel.
Stoptron(Kernel<? super InputType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Stoptron
Creates a new Stoptron with the given parameters.
StreamSerializationHandler<SerializedType> - Interface in gov.sandia.cognition.io.serialization
Interface for an object that can be used to serialize and deserialize objects.
StringEvaluatorSingleTermFilter - Class in gov.sandia.cognition.text.term.filter
Adapts an evaluator from string to string to be a term filter on individual terms.
StringEvaluatorSingleTermFilter() - Constructor for class gov.sandia.cognition.text.term.filter.StringEvaluatorSingleTermFilter
Creates a new StringEvaluatorSingleTermFilter with a null evaluator.
StringEvaluatorSingleTermFilter(Evaluator<String, String>) - Constructor for class gov.sandia.cognition.text.term.filter.StringEvaluatorSingleTermFilter
Creates a new StringEvaluatorSingleTermFilter with a given evaluator.
StringToDoubleConverter - Class in gov.sandia.cognition.data.convert.number
Converts a String to a Double using the Double.valueOf method.
StringToDoubleConverter() - Constructor for class gov.sandia.cognition.data.convert.number.StringToDoubleConverter
Creates a new StringToDoubleConverter.
StringToIntegerConverter - Class in gov.sandia.cognition.data.convert.number
Converts a String to a Integer using the Integer.valueOf method.
StringToIntegerConverter() - Constructor for class gov.sandia.cognition.data.convert.number.StringToIntegerConverter
Creates a new StringToIntegerConverter.
StringUtil - Class in gov.sandia.cognition.util
The Strings class implements static utility methods for dealing with String objects.
StringUtil() - Constructor for class gov.sandia.cognition.util.StringUtil
 
StudentizedRangeDistribution - Class in gov.sandia.cognition.statistics.distribution
Implementation of the Studentized Range distribution, which defines the population correction factor when performing multiple comparisons.
StudentizedRangeDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Default constructor
StudentizedRangeDistribution(int, double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Creates a new instance of StudentizedRangeDistribution
StudentizedRangeDistribution(StudentizedRangeDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution
Copy constructor
StudentizedRangeDistribution.APStat - Class in gov.sandia.cognition.statistics.distribution
This is a translation of Fortran code taken from http://lib.stat.cmu.edu/apstat/, and the comments on the individual functions in this class are taken directly from the original.
StudentizedRangeDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
CDF of the StudentizedRangeDistribution
StudentizedRangeDistribution.SampleRange - Class in gov.sandia.cognition.statistics.distribution
Computes the estimate of the Studentized Range for a single sample
StudentTConfidence - Class in gov.sandia.cognition.statistics.method
This class implements Student's t-tests for different uses.
StudentTConfidence() - Constructor for class gov.sandia.cognition.statistics.method.StudentTConfidence
Creates a new instance of StudentTConfidence
StudentTConfidence.Statistic - Class in gov.sandia.cognition.statistics.method
Confidence statistics for a Student-t test
StudentTConfidence.Summary - Class in gov.sandia.cognition.statistics.method
An implementation of the Summarizer interface for creating a ConfidenceInterval
StudentTDistribution - Class in gov.sandia.cognition.statistics.distribution
Defines a noncentral Student-t Distribution.
StudentTDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Default degrees of freedom.
StudentTDistribution(double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Creates a new instance of StudentTDistribution
StudentTDistribution(double, double, double) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Creates a new instance of StudentTDistribution
StudentTDistribution(StudentTDistribution) - Constructor for class gov.sandia.cognition.statistics.distribution.StudentTDistribution
Copy constructor
StudentTDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
Evaluator that computes the Cumulative Distribution Function (CDF) of a Student-t distribution with a fixed number of degrees of freedom
StudentTDistribution.MaximumLikelihoodEstimator - Class in gov.sandia.cognition.statistics.distribution
Estimates the parameters of the Student-t distribution from the given data, where the degrees of freedom are estimated from the Kurtosis of the sample data.
StudentTDistribution.PDF - Class in gov.sandia.cognition.statistics.distribution
Evaluator that computes the Probability Density Function (CDF) of a Student-t distribution with a fixed number of degrees of freedom
StudentTDistribution.WeightedMaximumLikelihoodEstimator - Class in gov.sandia.cognition.statistics.distribution
Creates a UnivariateGaussian from weighted data
subCollections() - Method in class gov.sandia.cognition.collection.DefaultMultiCollection
 
subCollections() - Method in interface gov.sandia.cognition.collection.MultiCollection
Returns the sub-collections of the multi-collection.
subCollections() - Method in class gov.sandia.cognition.collection.RangeExcludedArrayList
 
SubCostEvaluate(ParallelizableCostFunction, Evaluator<? super Vector, ? extends Vector>) - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer.SubCostEvaluate
Creates a new instance of SubCostEvaluate
SubCostGradient(ParallelizableCostFunction, GradientDescendable) - Constructor for class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer.SubCostGradient
Creates a new instance of SubCostGradient
subIndices - Variable in class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator
The indices to pull out of an input vector to create a new vector from.
subjectCounts - Variable in class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic
Number of subjects in each treatment
subLearner - Variable in class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner
The decider learner for the subspace.
SubsetIterator(int, int, ArrayList<ClassType>) - Constructor for class gov.sandia.cognition.math.Combinations.SubsetIterator
Creates a new instance of SubsetIterator
subtract(double, double) - Static method in class gov.sandia.cognition.math.LogMath
Subtracts two log-domain values.
subVector(int, int) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
subVector(int, int) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
subVector(int, int) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
Gets a subvector of "this", specified by the inclusive indices
subVector(int, int) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
 
subVector(int, int) - Method in interface gov.sandia.cognition.math.matrix.Vector
Gets a subvector of "this", specified by the inclusive indices
SubVectorEvaluator - Class in gov.sandia.cognition.learning.function.vector
Extracts the given set of indices from an input vector to create a new vector containing the input vector's elements at those indices.
SubVectorEvaluator() - Constructor for class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator
Creates a new SubVectorEvaluator.
SubVectorEvaluator(int, int[]) - Constructor for class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator
Creates a new SubVectorEvaluator with the given parameters.
SubVectorEvaluator(int, int[], VectorFactory<? extends Vector>) - Constructor for class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator
Creates a new SubVectorEvaluator with the given parameters.
SuccessiveOverrelaxation<InputType> - Class in gov.sandia.cognition.learning.algorithm.svm
The SuccessiveOverrelaxation class implements the Successive Overrelaxation (SOR) algorithm for learning a Support Vector Machine (SVM).
SuccessiveOverrelaxation() - Constructor for class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Creates a new instance of SuccessiveOverrelaxation.
SuccessiveOverrelaxation(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Creates a new instance of SuccessiveOverrelaxation.
SuccessiveOverrelaxation(Kernel<? super InputType>, double, double, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
Creates a new instance of SuccessiveOverrelaxation.
SuccessiveOverrelaxation.Entry - Class in gov.sandia.cognition.learning.algorithm.svm
The Entry class represents the data that the algorithm keeps about each training example.
successorIds(int) - Method in class gov.sandia.cognition.graph.GraphMetrics
Returns the id for all direct successors for the input node.
successorIds(NodeNameType) - Method in class gov.sandia.cognition.graph.GraphMetrics
Returns the ids of the direct successors for the input node.
successors(int) - Method in class gov.sandia.cognition.graph.GraphMetrics
Returns the node names for all direct successors to the input node.
successors(NodeNameType) - Method in class gov.sandia.cognition.graph.GraphMetrics
Returs the node names for all direct successors to the input node.
SufficientStatistic(MultivariateGaussian) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator.SufficientStatistic
Creates a new instance of SufficientStatistic
SufficientStatistic(MultivariateGaussianInverseGammaDistribution) - Constructor for class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator.SufficientStatistic
Creates a new instance of SufficientStatistic
SufficientStatistic() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
Default constructor
SufficientStatistic(double) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic
Creates a new instance of SufficientStatistic
SufficientStatistic() - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic
Creates a new, empty SufficientStatistic.
SufficientStatistic(double) - Constructor for class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic
Creates a new SufficientStatistic with the given value to initialize the variance.
SufficientStatistic<DataType,DistributionType> - Interface in gov.sandia.cognition.statistics
Sufficient statistics are the data which are sufficient to store all information to create an underlying parameter, such as a Distribution.
SufficientStatisticCovarianceInverse() - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
Default constructor
SufficientStatisticCovarianceInverse(double) - Constructor for class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse
Creates a new instance of SufficientStatisticCovarianceInverse
sum() - Method in class gov.sandia.cognition.math.matrix.AbstractVectorSpace
 
sum() - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
 
sum() - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
 
sum() - Method in class gov.sandia.cognition.math.matrix.DefaultInfiniteVector
 
sum() - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
 
sum() - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
 
sum() - Method in interface gov.sandia.cognition.math.matrix.VectorSpace
Computes the sum of the elements in the vector.
SumKernel<InputType> - Class in gov.sandia.cognition.learning.function.kernel
The SumKernel class implements a kernel that adds together the result of applying multiple kernels to the same pair of inputs.
SumKernel() - Constructor for class gov.sandia.cognition.learning.function.kernel.SumKernel
Creates a new instance of SumKernel.
SumKernel(Collection<? extends Kernel<? super InputType>>) - Constructor for class gov.sandia.cognition.learning.function.kernel.SumKernel
Creates a new instance of SumKernel with the given collection of kernels.
summaries - Variable in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
The summaries of performance.
summarize(Collection<? extends TargetEstimatePair<? extends TargetType, ? extends TargetType>>) - Method in class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction
 
summarize(Collection<? extends DataType>) - Method in class gov.sandia.cognition.learning.function.summarizer.MostFrequentSummarizer
Summarizes the given data by returning the most frequent value.
summarize(Collection<? extends TargetEstimatePair<? extends TargetType, ? extends EstimateType>>) - Method in class gov.sandia.cognition.learning.performance.AbstractSupervisedPerformanceEvaluator
 
summarize(Collection<? extends Pair<? extends Boolean, ? extends Boolean>>) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer
 
summarize(Collection<? extends ConfusionMatrix<Boolean>>) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.CombineSummarizer
 
summarize(Collection<? extends DefaultBinaryConfusionMatrix>) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval.Summary
 
summarize(Collection<? extends Pair<? extends CategoryType, ? extends CategoryType>>) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.ActualPredictedPairSummarizer
 
summarize(Collection<? extends ConfusionMatrix<CategoryType>>) - Method in class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.CombineSummarizer
 
summarize(Collection<? extends Number>) - Method in class gov.sandia.cognition.math.NumberAverager
Returns the average (arithmetic mean) of a Collection of Numbers, or null if the collection of Numbers are null
summarize(Collection<? extends RingType>) - Method in class gov.sandia.cognition.math.RingAverager
 
summarize(Collection<? extends WeightedValue<? extends Number>>) - Method in class gov.sandia.cognition.math.WeightedNumberAverager
 
summarize(Collection<? extends WeightedValue<RingType>>) - Method in class gov.sandia.cognition.math.WeightedRingAverager
 
summarize(Collection<? extends Number>) - Method in class gov.sandia.cognition.statistics.method.StudentTConfidence.Summary
 
summarize(Collection<? extends DataType>) - Method in interface gov.sandia.cognition.util.Summarizer
Creates a summary of the given collection of data.
summarizer - Variable in class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment
The summarizer for summarizing the result of the performance evaluator from all the folds.
summarizer - Variable in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
The summarizer for summarizing the result of the performance evaluator from all the folds.
summarizer - Variable in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
The summarizer for summarizing the result of the performance evaluator from all the folds.
summarizer - Variable in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
The summarizer for summarizing the result of the performance evaluator from all the folds.
Summarizer<DataType,SummaryType> - Interface in gov.sandia.cognition.util
The Summarizer interface defines the functionality of an object that can take a collection of some data and return a summary of that data.
summary - Variable in class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment
The summary of the performance evaluations made at the end of the experiment.
summary - Variable in class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment
The summary of the performance evaluations made at the end of the experiment.
summary - Variable in class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
The summary of the performance evaluations made at the end of the experiment.
Summary(double) - Constructor for class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval.Summary
Creates a new Summarizer.
Summary(double) - Constructor for class gov.sandia.cognition.statistics.method.StudentTConfidence.Summary
Creates a new Summarizer.
sumOfColumns() - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
sumOfColumns() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
 
sumOfColumns() - Method in interface gov.sandia.cognition.math.matrix.Matrix
Returns a new vector containing the sum across the columns.
sumOfRows() - Method in class gov.sandia.cognition.math.matrix.AbstractMatrix
 
sumOfRows() - Method in class gov.sandia.cognition.math.matrix.custom.SparseMatrix
 
sumOfRows() - Method in interface gov.sandia.cognition.math.matrix.Matrix
Returns a new vector containing the sum across the rows.
SumProductBeliefPropagation<LabelType> - Class in gov.sandia.cognition.graph.inference
This class implements the sum-product belief propagation algorithm for arbitrary energy functions.
SumProductBeliefPropagation(int, double, int) - Constructor for class gov.sandia.cognition.graph.inference.SumProductBeliefPropagation
Creates a new BP solver with the specified settings.
SumProductBeliefPropagation(int) - Constructor for class gov.sandia.cognition.graph.inference.SumProductBeliefPropagation
Creates a new BP solver with the default settings excepting max number of iterations.
SumProductBeliefPropagation() - Constructor for class gov.sandia.cognition.graph.inference.SumProductBeliefPropagation
Creates a new BP solver with the default settings.
SumProductDirectedPropagation<LabelType> - Class in gov.sandia.cognition.graph.inference
This class implements a Bayes Net -- but only allowing for pairwise influence along edges.
SumProductDirectedPropagation(int, double, int) - Constructor for class gov.sandia.cognition.graph.inference.SumProductDirectedPropagation
Creates a new pairwise Bayes Net solver with the specified settings.
SumProductDirectedPropagation(int) - Constructor for class gov.sandia.cognition.graph.inference.SumProductDirectedPropagation
Creates a new pairwise Bayes Net solver with the default settings excepting max number of iterations.
SumProductDirectedPropagation() - Constructor for class gov.sandia.cognition.graph.inference.SumProductDirectedPropagation
Creates a new pairwise Bayes Net solver with the default settings.
SumProductInferencingAlgorithm<LabelType> - Class in gov.sandia.cognition.graph.inference
Base class for Sum-Product inferencing algorithms on graphs/energy functions
SumProductInferencingAlgorithm(int, double, int) - Constructor for class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
Creates a new solver with the specified settings.
SumProductInferencingAlgorithm(int) - Constructor for class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
Creates a new solver with the default settings excepting max number of iterations.
SumProductInferencingAlgorithm() - Constructor for class gov.sandia.cognition.graph.inference.SumProductInferencingAlgorithm
Creates a new solver with the default settings.
sumSquaredDifferences - Variable in class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic
This is the sum-squared differences
SumSquaredErrorCostFunction - Class in gov.sandia.cognition.learning.function.cost
This is the sum-squared error cost function
SumSquaredErrorCostFunction() - Constructor for class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction
Creates a new instance of SumSquaredErrorCostFunction
SumSquaredErrorCostFunction(Collection<? extends InputOutputPair<? extends Vector, Vector>>) - Constructor for class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction
Creates a new instance of MeanSquaredErrorCostFunction
SumSquaredErrorCostFunction.Cache - Class in gov.sandia.cognition.learning.function.cost
Caches often-used values for the Cost Function
SumSquaredErrorCostFunction.GradientPartialSSE - Class in gov.sandia.cognition.learning.function.cost
Partial result from the SSE gradient computation
sumWeights(Collection<? extends InputOutputPair<?, ?>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
Gets the sum of the weights of the weights of the elements of the dataset.
SupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> - Interface in gov.sandia.cognition.learning.algorithm
Interface for a class that is a supervised learning algorithm that can be used both batch and incremental contexts.
SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> - Interface in gov.sandia.cognition.learning.algorithm
The BatchSupervisedLearner interface is an extension of the BatchLearner interface that contains the typical generic definition conventions for a batch, supervised learning algorithm.
SupervisedCostFunction<InputType,TargetType> - Interface in gov.sandia.cognition.learning.function.cost
A type of CostFunction normally used in supervised-learning applications.
SupervisedIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> - Interface in gov.sandia.cognition.learning.algorithm
Interface for supervised incremental learning algorithms.
SupervisedLearnerComparisonExperiment<InputType,OutputType,StatisticType,SummaryType> - Class in gov.sandia.cognition.learning.experiment
A comparison experiment for supervised learners.
SupervisedLearnerComparisonExperiment() - Constructor for class gov.sandia.cognition.learning.experiment.SupervisedLearnerComparisonExperiment
Creates a new instance of SupervisedLearnerComparisonExperiment.
SupervisedLearnerComparisonExperiment(ValidationFoldCreator<InputOutputPair<InputType, OutputType>, InputOutputPair<InputType, OutputType>>, PerformanceEvaluator<? super Evaluator<? super InputType, OutputType>, ? super Collection<? extends InputOutputPair<InputType, OutputType>>, ? extends StatisticType>, NullHypothesisEvaluator<Collection<? extends StatisticType>>, Summarizer<? super StatisticType, ? extends SummaryType>) - Constructor for class gov.sandia.cognition.learning.experiment.SupervisedLearnerComparisonExperiment
Creates a new instance of SupervisedLearnerComparisonExperiment.
SupervisedLearnerValidationExperiment<InputType,OutputType,StatisticType,SummaryType> - Class in gov.sandia.cognition.learning.experiment
The SupervisedLearnerValidationExperiment class extends the LearnerValidationExperiment class to provide a easy way to create a learner validation experiment for supervised learning.
SupervisedLearnerValidationExperiment() - Constructor for class gov.sandia.cognition.learning.experiment.SupervisedLearnerValidationExperiment
Creates a new instance of SupervisedLearnerValidationExperiment.
SupervisedLearnerValidationExperiment(ValidationFoldCreator<InputOutputPair<InputType, OutputType>, InputOutputPair<InputType, OutputType>>, PerformanceEvaluator<? super Evaluator<? super InputType, ? extends OutputType>, ? super Collection<? extends InputOutputPair<InputType, OutputType>>, ? extends StatisticType>, Summarizer<? super StatisticType, ? extends SummaryType>) - Constructor for class gov.sandia.cognition.learning.experiment.SupervisedLearnerValidationExperiment
Creates a new instance of SupervisedLearnerValidationExperiment.
SupervisedPerformanceEvaluator<InputType,TargetType,EstimateType,ResultType> - Interface in gov.sandia.cognition.learning.performance
The SupervisedPerformanceEvaluator interface extends the PerformanceEvaluator interface for performance evaluations of supervised machine learning algorithms where the target type is evaluated against the estimated type produced by the evaluator.
supportInserted - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry
Indicates if the support vector has been inserted into the map of support vectors or not.
supportsMap - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
The mapping of weight objects to non-zero weighted examples (support vectors).
svdDecompose() - Method in class gov.sandia.cognition.math.matrix.custom.DenseMatrix
Leverages LAPACK to compute the Singular Value Decomposition (SVD) of this.
swap(int, int) - Method in class gov.sandia.cognition.collection.DoubleArrayList
Swaps the values stored at p1 and p2.
swap(int, int) - Method in class gov.sandia.cognition.collection.IntArrayList
Swaps the values stored at p1 and p2.
swap(int, int) - Method in class gov.sandia.cognition.graph.DenseMemoryGraph
Helper that swaps the values at i and j in the edge list (handles the fact that the edge list is 2 values in a row for each edge).
swap(int, int) - Method in class gov.sandia.cognition.graph.WeightedDenseMemoryGraph
Overrides the parent's version to ensure the weights swap at the same time the edges do
SynonymFilter - Class in gov.sandia.cognition.text.term.filter
A term filter that uses a mapping of synonyms to replace a word with its synonym.
SynonymFilter() - Constructor for class gov.sandia.cognition.text.term.filter.SynonymFilter
Creates a new, empty SynonymFilter.
SynonymFilter(Map<Term, Term>) - Constructor for class gov.sandia.cognition.text.term.filter.SynonymFilter
Creates a new SynonymFilter with the given synonyms.
synonyms - Variable in class gov.sandia.cognition.text.term.filter.SynonymFilter
The mapping of terms to the synonym to replace them with.
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