- k - Variable in class gov.sandia.cognition.math.Combinations.AbstractCombinationsIterator
-
Number of objects to choose from the universe set.
- KalmanFilter - Class in gov.sandia.cognition.statistics.bayesian
-
A Kalman filter estimates the state of a dynamical system corrupted with
white Gaussian noise with observations that are corrupted with white
Gaussian noise.
- KalmanFilter() - Constructor for class gov.sandia.cognition.statistics.bayesian.KalmanFilter
-
Creates a new instance of KalmanFilter
- KalmanFilter(int) - Constructor for class gov.sandia.cognition.statistics.bayesian.KalmanFilter
-
Creates an autonomous, fully observable linear dynamical system
with the given dimensionality
- KalmanFilter(LinearDynamicalSystem, Matrix, Matrix) - Constructor for class gov.sandia.cognition.statistics.bayesian.KalmanFilter
-
Creates a new instance of LinearUpdater
- kappa - Variable in class gov.sandia.cognition.learning.function.kernel.SigmoidKernel
-
The kappa value to multiply times the dot product.
- KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> - Class in gov.sandia.cognition.math.geometry
-
Implementation of a kd-tree.
- KDTree() - Constructor for class gov.sandia.cognition.math.geometry.KDTree
-
Default constructor
- KDTree(Collection<? extends PairType>) - Constructor for class gov.sandia.cognition.math.geometry.KDTree
-
Creates a balanced KDTree from the given points.
- KDTree(PairType, KDTree.PairFirstVectorizableIndexComparator, KDTree<VectorType, DataType, PairType>) - Constructor for class gov.sandia.cognition.math.geometry.KDTree
-
Creates a KDTree subtree for recursion purposes.
- KDTree(ArrayList<? extends PairType>, KDTree.PairFirstVectorizableIndexComparator, int, KDTree<VectorType, DataType, PairType>) - Constructor for class gov.sandia.cognition.math.geometry.KDTree
-
Creates a balanced KDTree subtree for recursion purposes from the given
ArrayList of points.
- KDTree.InOrderKDTreeIterator<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> - Class in gov.sandia.cognition.math.geometry
-
Iterates through the KDTree using "inorder", also known as "symmetric
traversal", of the tree.
- KDTree.Neighborhood<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> - Class in gov.sandia.cognition.math.geometry
-
A Collection of nearby pairs.
- KDTree.Neighborhood.Neighbor<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> - Class in gov.sandia.cognition.math.geometry
-
Holds neighbor information used during the evaluate method and is put
into a priority queue.
- KDTree.Neighborhood.NeighborhoodIterator - Class in gov.sandia.cognition.math.geometry
-
Iterator for the Neighborhood.
- KDTree.PairFirstVectorizableIndexComparator - Class in gov.sandia.cognition.math.geometry
-
Comparator for Pairs that have a Vectorizable as its first parameter.
- keepGoing - Variable in class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
-
Indicates whether or not the learner should make another step.
- kernel - Variable in class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner
-
The kernel to use.
- kernel - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
-
The kernel to use.
- kernel - Variable in class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
-
The internal kernel.
- kernel - Variable in class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer
-
The internal kernel.
- Kernel<InputType> - Interface in gov.sandia.cognition.learning.function.kernel
-
The Kernel interface the functionality required from an object
that implements a kernel function.
- KernelAdatron<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
-
The KernelAdatron class implements an online version of the Support
Vector Machine learning algorithm.
- KernelAdatron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
-
Creates a new instance of KernelAdatron.
- KernelAdatron(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
-
Creates a new KernelAdatron with the given kernel.
- KernelAdatron(Kernel<? super InputType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron
-
Creates a new KernelAdatron with the given kernel and maximum number
of iterations.
- KernelBasedIterativeRegression<InputType> - Class in gov.sandia.cognition.learning.algorithm.regression
-
The KernelBasedIterativeRegression class implements an online version of
the Support Vector Regression algorithm.
- KernelBasedIterativeRegression() - Constructor for class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
-
Creates a new instance of KernelBasedIterativeRegression.
- KernelBasedIterativeRegression(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
-
Creates a new KernelBasedIterativeRegression with the given kernel.
- KernelBasedIterativeRegression(Kernel<? super InputType>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
-
Creates a new KernelBasedIterativeRegression with the given kernel.
- KernelBasedIterativeRegression(Kernel<? super InputType>, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression
-
Creates a new KernelBasedIterativeRegression with the given kernel and
maximum number of iterations.
- KernelBinaryCategorizer<InputType,EntryType extends WeightedValue<? extends InputType>> - Class in gov.sandia.cognition.learning.function.categorization
-
The KernelBinaryCategorizer class implements a binary
categorizer that uses a kernel to do its categorization.
- KernelBinaryCategorizer() - Constructor for class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
-
Creates a new instance of KernelBinaryCategorizer.
- KernelBinaryCategorizer(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
-
Creates a new instance of KernelBinaryCategorizer with the given kernel.
- KernelBinaryCategorizer(Kernel<? super InputType>, Collection<EntryType>, double) - Constructor for class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
-
Creates a new instance of KernelBinaryCategorizer with the given kernel,
weighted examples, and bias.
- KernelBinaryCategorizer(KernelBinaryCategorizer<InputType, ? extends EntryType>) - Constructor for class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer
-
Creates a new copy of a KernelBinaryCategorizer.
- KernelBinaryCategorizerOnlineLearnerAdapter<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
-
A wrapper class for a KernelizableBinaryCategorizerOnlineLearner
that allows it to be used as a batch or incremental learner over the
input type directly, rather than using utility methods.
- KernelBinaryCategorizerOnlineLearnerAdapter() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelBinaryCategorizerOnlineLearnerAdapter
-
Creates a new KernelBinaryCategorizerOnlineLearnerAdapter with
a null learner.
- KernelBinaryCategorizerOnlineLearnerAdapter(Kernel<? super InputType>, KernelizableBinaryCategorizerOnlineLearner) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelBinaryCategorizerOnlineLearnerAdapter
-
Creates a new KernelBinaryCategorizerOnlineLearnerAdapter with
the given kernel and learner.
- KernelContainer<InputType> - Interface in gov.sandia.cognition.learning.function.kernel
-
Defines an object that contains a Kernel.
- KernelDistanceMetric<InputType> - Class in gov.sandia.cognition.learning.function.kernel
-
The KernelDistanceMetric class implements a distance metric that
utilizes an underlying Kernel for computing the distance.
- KernelDistanceMetric() - Constructor for class gov.sandia.cognition.learning.function.kernel.KernelDistanceMetric
-
Creates a new instance of KernelDistanceMetric.
- KernelDistanceMetric(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.function.kernel.KernelDistanceMetric
-
Creates a new instance of KernelDistanceMetric using the given kernel.
- KernelDistanceMetric(KernelDistanceMetric<InputType>) - Constructor for class gov.sandia.cognition.learning.function.kernel.KernelDistanceMetric
-
Creates a new copy of a KernelDistanceMetric.
- KernelizableBinaryCategorizerOnlineLearner - Interface in gov.sandia.cognition.learning.algorithm.perceptron
-
Interface for an online learner of a linear binary categorizer that can also
be used with a kernel function.
- kernelMatrix - Variable in class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function
-
The kernel matrix for all the data the KPCA was done over.
- KernelPerceptron<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
-
The KernelPerceptron class implements the kernel version of
the Perceptron algorithm.
- KernelPerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
-
Creates a new instance of KernelPerceptron.
- KernelPerceptron(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
-
Creates a new KernelPerceptron with the given kernel.
- KernelPerceptron(Kernel<? super InputType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
-
Creates a new KernelPerceptron with the given kernel and maximum number
of iterations.
- KernelPerceptron(Kernel<? super InputType>, int, double, double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron
-
Creates a new KernelPerceptron with the given parameters.
- KernelPrincipalComponentsAnalysis<DataType> - Class in gov.sandia.cognition.learning.algorithm.pca
-
An implementation of the Kernel Principal Components Analysis (KPCA)
algorithm.
- KernelPrincipalComponentsAnalysis() - Constructor for class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
-
Creates a new Kernel Principal Components Analysis with a null kernel
and a default component count.
- KernelPrincipalComponentsAnalysis(Kernel<? super DataType>, int) - Constructor for class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
-
Creates a new Kernel Principal Components Analysis with the given
kernel and component count.
- KernelPrincipalComponentsAnalysis(Kernel<? super DataType>, int, boolean) - Constructor for class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis
-
Creates a new Kernel Principal Components Analysis with the given
kernel and component count.
- KernelPrincipalComponentsAnalysis.Function<DataType> - Class in gov.sandia.cognition.learning.algorithm.pca
-
The resulting transformation function learned by Kernel Principal
Components Analysis.
- kernels - Variable in class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer
-
The collection of kernels in the container.
- KernelScalarFunction<InputType> - Class in gov.sandia.cognition.learning.function.scalar
-
The KernelScalarFunction class implements a scalar function that
uses a kernel to compute its output value.
- KernelScalarFunction() - Constructor for class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction
-
Creates a new instance of KernelScalarFunction.
- KernelScalarFunction(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction
-
Creates a new instance of KernelScalarFunction with the given kernel.
- KernelScalarFunction(Kernel<? super InputType>, Collection<? extends WeightedValue<? extends InputType>>, double) - Constructor for class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction
-
Creates a new instance of KernelScalarFunction with the given kernel,
weighted examples, and bias.
- KernelScalarFunction(KernelScalarFunction<InputType>) - Constructor for class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction
-
Creates a new copy of a KernelScalarFunction.
- KernelUtil - Class in gov.sandia.cognition.learning.function.kernel
-
A utility class for dealing with kernels.
- KernelUtil() - Constructor for class gov.sandia.cognition.learning.function.kernel.KernelUtil
-
- KernelWeightedRobustRegression<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.regression
-
KernelWeightedRobustRegression takes a supervised learning algorithm that
operates on a weighted collection of InputOutputPairs and modifies the
weight of a sample based on the dataset output and its corresponding
estimate from the Evaluator from the supervised learning algorithm at each
iteration.
- KernelWeightedRobustRegression(SupervisedBatchLearner<InputType, OutputType, ?>, Kernel<? super OutputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
-
Creates a new instance of RobustRegression
- KernelWeightedRobustRegression(SupervisedBatchLearner<InputType, OutputType, ?>, Kernel<? super OutputType>, int, double) - Constructor for class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression
-
Creates a new instance of RobustRegression
- key - Variable in class gov.sandia.cognition.collection.AbstractLogNumberMap.SimpleEntry
-
Key associated with this entry
- key - Variable in class gov.sandia.cognition.collection.AbstractMutableDoubleMap.SimpleEntry
-
Key associated with this entry
- key - Variable in class gov.sandia.cognition.util.DefaultKeyValuePair
-
The key part in the pair, which is the first element.
- keySet() - Method in class gov.sandia.cognition.collection.AbstractScalarMap
-
- keySet() - Method in class gov.sandia.cognition.collection.DynamicArrayMap
-
- keySet() - Method in interface gov.sandia.cognition.collection.NumericMap
-
Gets the set of unique keys in the map.
- KeyValuePair<KeyType,ValueType> - Interface in gov.sandia.cognition.util
-
Represents a key-value pair.
- KMeansClusterer<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering
-
The KMeansClusterer class implements the standard k-means
(k-centroids) clustering algorithm.
- KMeansClusterer() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
-
Creates a new instance of KMeansClusterer with default
parameters.
- KMeansClusterer(int, int, FixedClusterInitializer<ClusterType, DataType>, ClusterDivergenceFunction<? super ClusterType, ? super DataType>, ClusterCreator<ClusterType, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer
-
Creates a new instance of KMeansClusterer using the given parameters.
- KMeansClustererWithRemoval<DataType,ClusterType extends Cluster<DataType>> - Class in gov.sandia.cognition.learning.algorithm.clustering
-
Creates a k-means clustering algorithm that removes clusters that do
not have sufficient membership to pass a simple statistical significance
test.
- KMeansClustererWithRemoval() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.KMeansClustererWithRemoval
-
Default constructor
- KMeansClustererWithRemoval(int, int, FixedClusterInitializer<ClusterType, DataType>, ClusterDivergenceFunction<ClusterType, DataType>, ClusterCreator<ClusterType, DataType>, double) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.KMeansClustererWithRemoval
-
Creates a new instance of KMeansClusterer using the given parameters.
- KMeansFactory - Class in gov.sandia.cognition.learning.algorithm.clustering
-
Creates a parallelized version of the k-means clustering algorithm for the
typical use: clustering vector data with a Euclidean distance metric.
- KMeansFactory() - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
-
Creates a new instance of KMeansFactory
- KMeansFactory(int) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
-
Creates a new instance of KMeansFactory.
- KMeansFactory(int, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory
-
Creates a new instance of KMeansFactory.
- KNearestNeighbor<InputType,OutputType> - Interface in gov.sandia.cognition.learning.algorithm.nearest
-
A generic k-nearest-neighbor classifier.
- KNearestNeighborExhaustive<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.nearest
-
A generic k-nearest-neighbor classifier.
- KNearestNeighborExhaustive() - Constructor for class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive
-
Creates a new instance of KNearestNeighborExhaustive.
- KNearestNeighborExhaustive(int, Collection<? extends InputOutputPair<? extends InputType, OutputType>>, DivergenceFunction<? super InputType, ? super InputType>, Summarizer<? super OutputType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive
-
Creates a new instance of KNearestNeighborExhaustive
- KNearestNeighborExhaustive.Learner<InputType,OutputType> - Class in gov.sandia.cognition.learning.algorithm.nearest
-
This is a BatchLearner interface for creating a new KNearestNeighborExhaustive
from a given dataset, simply a pass-through to the constructor of
KNearestNeighborExhaustive
- KNearestNeighborExhaustive.Neighbor - Class in gov.sandia.cognition.learning.algorithm.nearest
-
Holds neighbor information used during the evaluate method and is put
into a priority queue.
- KNearestNeighborKDTree<InputType extends Vectorizable,OutputType> - Class in gov.sandia.cognition.learning.algorithm.nearest
-
A KDTree-based implementation of the k-nearest neighbor algorithm.
- KNearestNeighborKDTree() - Constructor for class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree
-
Creates a new instance of KNearestNeighborKDTree
- KNearestNeighborKDTree(int, KDTree<InputType, OutputType, InputOutputPair<? extends InputType, OutputType>>, Metric<? super InputType>, Summarizer<? super OutputType, ? extends OutputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree
-
Creates a new instance of KNearestNeighborKDTree
- KNearestNeighborKDTree.Learner<InputType extends Vectorizable,OutputType> - Class in gov.sandia.cognition.learning.algorithm.nearest
-
This is a BatchLearner interface for creating a new KNearestNeighbor
from a given dataset, simply a pass-through to the constructor of
KNearestNeighbor
- knownTwoCharacterEdits(Iterable<String>) - Method in class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector
-
Creates the set of known two character edits for a given list of one
character edits.
- KolmogorovDistribution - Class in gov.sandia.cognition.statistics.distribution
-
Contains the Cumulative Distribution Function description for the "D"
statistic used within the Kolmogorov-Smirnov test.
- KolmogorovDistribution() - Constructor for class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution
-
Creates a new instance of CumulativeDistribution
- KolmogorovDistribution.CDF - Class in gov.sandia.cognition.statistics.distribution
-
Contains the Cumulative Distribution Function description for the "D"
statistic used within the Kolmogorov-Smirnov test.
- KolmogorovSmirnovConfidence - Class in gov.sandia.cognition.statistics.method
-
Performs a Kolmogorov-Smirnov Confidence Test.
- KolmogorovSmirnovConfidence() - Constructor for class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence
-
Creates a new instance of KolmogorovSmirnovConfidence
- KolmogorovSmirnovConfidence.Statistic - Class in gov.sandia.cognition.statistics.method
-
Computes the ConfidenceStatistic associated with a K-S test
- KolmogorovSmirnovDivergence<DataType extends java.lang.Number> - Class in gov.sandia.cognition.learning.function.cost
-
CostFunction that induces a CDF that most-closely resembles the
target distribution according to the Kolmogorov-Smirnov (K-S) test.
- KolmogorovSmirnovDivergence() - Constructor for class gov.sandia.cognition.learning.function.cost.KolmogorovSmirnovDivergence
-
Default constructor
- KolmogorovSmirnovDivergence(Collection<? extends DataType>) - Constructor for class gov.sandia.cognition.learning.function.cost.KolmogorovSmirnovDivergence
-
Creates a new instance of KolmogorovSmirnovDivergence
- KolmogorovSmirnovEvaluator - Class in gov.sandia.cognition.learning.function.scalar
-
You can specify a particular CDF.
- KolmogorovSmirnovEvaluator() - Constructor for class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
-
Creates a new KolmogorovSmirnovEvaluator.
- KolmogorovSmirnovEvaluator(CumulativeDistributionFunction<Double>, int) - Constructor for class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator
-
Creates a new KolmogorovSmirnovEvaluator.
- KSsignificance(double, double) - Static method in class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence.Statistic
-
Computes the significance of the K-S test from the given degrees of
freedom and D-statistic.
- KullbackLeiblerDivergence<DomainType> - Class in gov.sandia.cognition.statistics
-
A class used for measuring how similar two distributions are using Kullback--Leibler Divergence.
- KullbackLeiblerDivergence(DiscreteDistribution<DomainType>, DiscreteDistribution<DomainType>) - Constructor for class gov.sandia.cognition.statistics.KullbackLeiblerDivergence
-
Basic constructor to find the Kullback--Leibler Divergence between the two supplied distributions.