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

K

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.EM

Holds the value of EM.K_PARAM.

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.KMeans

Holds the value of KMeans.K_PARAM.

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.ProjectedClustering

Holds the value of ProjectedClustering.K_PARAM.

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.KNNDistanceOrder

Holds the value of KNNDistanceOrder.K_PARAM.

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.KNNJoin

The k parameter

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.ABOD

k parameter

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LOF

Holds the value of LOF.K_PARAM.

k - Variable in class de.lmu.ifi.dbs.elki.application.visualization.KNNExplorer.ExplorerWindow

k - Variable in class de.lmu.ifi.dbs.elki.data.KNNList

The maximum size of this list.

k - Variable in class de.lmu.ifi.dbs.elki.parser.meta.RandomProjectionParser

Holds the desired cardinality of the subset of attributes selected for projection.

k - Variable in class de.lmu.ifi.dbs.elki.preprocessing.HiSCPreprocessor

The number of nearest neighbors considered to determine the preference vector.

k - Variable in class de.lmu.ifi.dbs.elki.preprocessing.KnnQueryBasedHiCOPreprocessor

Holds the value of parameter k.

k - Variable in class de.lmu.ifi.dbs.elki.preprocessing.MaterializeKNNPreprocessor

Holds the value of MaterializeKNNPreprocessor.K_PARAM.

k_0 - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ApproximationLine

The start value for k.

k_i - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.ProjectedClustering

Holds the value of ProjectedClustering.K_I_PARAM.

K_I_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.ProjectedClustering

OptionID for ProjectedClustering.K_I_PARAM

K_I_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.ProjectedClustering

Parameter to specify the multiplier for the initial number of seeds, must be an integer greater than 0.

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.EM

OptionID for EM.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.KMeans

OptionID for KMeans.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.ProjectedClustering

OptionID for ProjectedClustering.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.KNNDistanceOrder

OptionID for KNNDistanceOrder.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.KNNJoin

OptionID for KNNJoin.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.ABOD

OptionID for ABOD.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LOF

OptionID for LOF.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree

OptionID for MkAppTree.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree

OptionID for MkCoPTree.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree

OptionID for RdKNNTree.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.HiSCPreprocessor

OptionID for HiSCPreprocessor.K_PARAM

K_ID - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.MaterializeKNNPreprocessor

OptionID for MaterializeKNNPreprocessor.K_PARAM

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTree

Holds the value of parameter AbstractMkTree.K_MAX_PARAM.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree

Parameter k.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree

Parameter k.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabDirectoryEntry

The maximal number of knn distances to be stored.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabLeafEntry

The maximal number of knn distances to be stored.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.MkTreeHeader

The maximum number k of reverse kNN queries to be supported.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree

Parameter k.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTreeHeader

The maximum number k of reverse kNN queries to be supported.

K_MAX_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTree

OptionID for AbstractMkTree.K_MAX_PARAM.

K_MAX_PARAM - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTree

Parameter specifying the maximal number k of reverse k nearest neighbors to be supported, must be an integer greater than 0.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.EM

Parameter to specify the number of clusters to find, must be an integer greater than 0.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.KMeans

Parameter to specify the number of clusters to find, must be an integer greater than 0.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.ProjectedClustering

Parameter to specify the number of clusters to find, must be an integer greater than 0.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.KNNDistanceOrder

Parameter to specify the distance of the k-distant object to be assessed, must be an integer greater than 0.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.KNNJoin

Parameter that specifies the k-nearest neighbors to be assigned, must be an integer greater than 0.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.ABOD

Parameter for k, the number of neighbors used in kNN queries.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LOF

Parameter to specify the number of nearest neighbors of an object to be considered for computing its LOF_SCORE, must be an integer greater than 1.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree

Parameter for k

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree

Parameter for k

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree

Parameter for k

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.preprocessing.HiSCPreprocessor

k Parameter

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.preprocessing.KnnQueryBasedHiCOPreprocessor

Optional parameter to specify the number of nearest neighbors considered in the PCA, must be an integer greater than 0.

K_PARAM - Variable in class de.lmu.ifi.dbs.elki.preprocessing.MaterializeKNNPreprocessor

Parameter to specify the number of nearest neighbors of an object to be materialized. must be an integer greater than 1.

kappa - Variable in class de.lmu.ifi.dbs.elki.preprocessing.PreDeConPreprocessor

The kappa value for generating the variance vector.

KDDTask<O extends DatabaseObject> - Class in de.lmu.ifi.dbs.elki

Provides a KDDTask that can be used to perform any algorithm implementing Algorithm using any DatabaseConnection implementing DatabaseConnection.

KDDTask() - Constructor for class de.lmu.ifi.dbs.elki.KDDTask

Provides a KDDTask.

kernel - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix

The kernel matrix

KERNEL_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.ABOD

OptionID for ABOD.KERNEL_FUNCTION_PARAM

KERNEL_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.KernelBasedLocallyWeightedDistanceFunction

OptionID for KernelBasedLocallyWeightedDistanceFunction.KERNEL_FUNCTION_PARAM

KERNEL_FUNCTION_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.ABOD

Parameter for Kernel function.

KERNEL_FUNCTION_PARAM - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.KernelBasedLocallyWeightedDistanceFunction

Parameter for the kernel function

KERNEL_MATRIX - Static variable in class de.lmu.ifi.dbs.elki.database.AssociationID

The association id to associate a kernel matrix.

KernelBasedLocallyWeightedDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction

Provides a kernel based locally weighted distance function.

KernelBasedLocallyWeightedDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.KernelBasedLocallyWeightedDistanceFunction

Provides a kernel based locally weighted distance function.

KernelCovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>> - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca

Kernel Covariance Matrix Builder.

KernelCovarianceMatrixBuilder() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.KernelCovarianceMatrixBuilder

KernelDensityEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics

Estimate density given an array of points.

KernelDensityEstimator(double[], double, double, KernelDensityEstimator.Kernel, int) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.KernelDensityEstimator

Initialize and execute kernel density estimation.

KernelDensityEstimator(double[], KernelDensityEstimator.Kernel) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.KernelDensityEstimator

Process an array of data

KernelDensityEstimator.Kernel - Enum in de.lmu.ifi.dbs.elki.math.statistics

Supported kernel functions

KernelDensityEstimator.Kernel() - Constructor for enum de.lmu.ifi.dbs.elki.math.statistics.KernelDensityEstimator.Kernel

kernelFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.ABOD

Store the configured Kernel version

kernelFunction - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.KernelBasedLocallyWeightedDistanceFunction

The kernel function that is used.

KernelFunction<O extends DatabaseObject,D extends Distance<D>> - Interface in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Interface Kernel describes the requirements of any kernel function.

kernelMatrix - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.KernelBasedLocallyWeightedDistanceFunction

The global precomputed kernel matrix

kernelMatrix - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.ArbitraryKernelFunctionWrapper

The global kernel Matrix.

KernelMatrix<O extends RealVector<O,?>> - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Provides a class for storing the kernel matrix and several extraction methods for convenience.

KernelMatrix(double[][]) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix

Wraps the matrixArray in a KernelMatrix

KernelMatrix(KernelFunction<O, DoubleDistance>, Database<O>) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix

Provides a new kernel matrix.

KernelMatrix(KernelFunction<O, DoubleDistance>, Database<O>, List<Integer>) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix

Provides a new kernel matrix.

KernelMatrix(Matrix) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix

Makes a new kernel matrix from matrix.

key - Variable in class de.lmu.ifi.dbs.elki.utilities.heap.DefaultHeapNode

The key of this heap node.

keySet() - Method in class de.lmu.ifi.dbs.elki.database.AssociationMaps

Provides the set of all association ids pointing to mappings from object ids to objects within this AssociationMaps.

keySet() - Method in class de.lmu.ifi.dbs.elki.database.Associations

Provides the set of all association ids pointing to objects within this Associations.

KMeans<D extends Distance<D>,V extends RealVector<V,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering

Provides the k-means algorithm.

KMeans() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.KMeans

Provides the k-means algorithm, adding parameter KMeans.K_PARAM to the option handler additionally to parameters of super class.

knn - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.SOD

Holds the value of SOD.KNN_PARAM.

KNN_HICO_PREPROCESSOR_K - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.KnnQueryBasedHiCOPreprocessor

OptionID for KnnQueryBasedHiCOPreprocessor.K_PARAM

KNN_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.SOD

OptionID for SOD.KNN_PARAM

KNN_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.SOD

Parameter to specify the number of shared nearest neighbors to be considered for learning the subspace properties., must be an integer greater than 0.

knnDistance - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxDirectoryEntry

The aggregated k-nearest neighbor distance of the underlying MkMax-Tree node.

knnDistance - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxLeafEntry

The k-nearest neighbor distance of the underlying data object.

kNNDistance(DistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeNode

Determines and returns the k-nearest neighbor distance of this node as the maximum of the k-nearest neighbor distances of all entries.

knnDistance - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNDirectoryEntry

The aggregated knn distance of this entry.

knnDistance - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNLeafEntry

The knn distance of the underlying data object.

kNNDistance() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNNode

Computes and returns the aggregated knn distance of this node

kNNdistanceAdjustment(E, Map<Integer, KNNList<D>>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTree

Performs a distance adjustment in the subtree of the specified root entry.

kNNdistanceAdjustment(MkMaxEntry<D>, Map<Integer, KNNList<D>>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTree

Adjusts the knn distance in the subtree of the specified root entry.

kNNdistanceAdjustment(MkTabEntry<D>, Map<Integer, KNNList<D>>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree

knnDistanceApproximation() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeNode

Determines and returns the polynomial approximation for the knn distances of this node as the maximum of the polynomial approximations of all entries.

KNNDistanceOrder<O extends DatabaseObject,D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.algorithm

Provides an order of the kNN-distances for all objects within the database.

KNNDistanceOrder() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.KNNDistanceOrder

Provides an algorithm to order the kNN-distances for all objects of the database, adding parameters KNNDistanceOrder.K_PARAM and KNNDistanceOrder.PERCENTAGE_PARAM to the option handler additionally to parameters of super class.

KNNDistanceOrderResult<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.result

Wraps a list containing the knn distances.

KNNDistanceOrderResult(List<D>) - Constructor for class de.lmu.ifi.dbs.elki.result.KNNDistanceOrderResult

Construct result

knnDistances - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabDirectoryEntry

The aggregated knn distances of the underlying node.

knnDistances - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabLeafEntry

The knn distances of the underlying data object.

knnDistances(Integer) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree

Returns the knn distance of the object with the specified id.

kNNDistances(DistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeNode

Determines and returns the knn distance of this node as the maximum knn distance of all entries.

knnDistances - Variable in class de.lmu.ifi.dbs.elki.result.KNNDistanceOrderResult

Store the kNN Distances

KNNExplorer<O extends NumberVector<O,?>,N extends NumberDistance<N,D>,D extends Number> - Class in de.lmu.ifi.dbs.elki.application.visualization

User application to explore the k Nearest Neighbors for a given data set and distance function.

KNNExplorer() - Constructor for class de.lmu.ifi.dbs.elki.application.visualization.KNNExplorer

KNNExplorer.ExplorerWindow - Class in de.lmu.ifi.dbs.elki.application.visualization

KNNExplorer.ExplorerWindow() - Constructor for class de.lmu.ifi.dbs.elki.application.visualization.KNNExplorer.ExplorerWindow

KNNExplorer.ExplorerWindow.SeriesLabelRenderer - Class in de.lmu.ifi.dbs.elki.application.visualization

KNNExplorer.ExplorerWindow.SeriesLabelRenderer() - Constructor for class de.lmu.ifi.dbs.elki.application.visualization.KNNExplorer.ExplorerWindow.SeriesLabelRenderer

Constructor.

knnJoin - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu

Holds the knnJoin algorithm.

KNNJoin<V extends NumberVector<V,?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> - Class in de.lmu.ifi.dbs.elki.algorithm

Joins in a given spatial database to each object its k-nearest neighbors.

KNNJoin() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.KNNJoin

Provides a KNN-Join, adding parameter KNNJoin.K_PARAM to the option handler additionally to parameters of super class.

KNNLIST - Static variable in class de.lmu.ifi.dbs.elki.algorithm.KNNJoin

Association ID for KNNLists.

KNNList<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.data

A wrapper class for storing the k most similar comparable objects.

KNNList(int, D) - Constructor for class de.lmu.ifi.dbs.elki.data.KNNList

Creates a new KNNList with the specified parameters.

kNNQuery(O, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.MetricalIndex

Performs a k-nearest neighbor query for the given object with the given parameter k and the according distance function.

kNNQuery(O, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree

kNNQuery(O, int, SpatialDistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree

Performs a k-nearest neighbor query for the given NumberVector with the given parameter k and the according distance function.

kNNQuery(O, int, SpatialDistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.SpatialIndex

Performs a k-nearest neighbor query for the given object with the given parameter k and the according distance function.

KnnQueryBasedHiCOPreprocessor<V extends RealVector<V,?>> - Class in de.lmu.ifi.dbs.elki.preprocessing

Computes the HiCO correlation dimension of objects of a certain database.

KnnQueryBasedHiCOPreprocessor() - Constructor for class de.lmu.ifi.dbs.elki.preprocessing.KnnQueryBasedHiCOPreprocessor

Provides a new Preprocessor that computes the correlation dimension of objects of a certain database based on a k nearest neighbor query.

kNNQueryForID(Integer, int, DistanceFunction<O, D>) - Method in interface de.lmu.ifi.dbs.elki.database.Database

Performs a k-nearest neighbor query for the given object ID.

kNNQueryForID(Integer, int, DistanceFunction<O, T>) - Method in class de.lmu.ifi.dbs.elki.database.MetricalIndexDatabase

kNNQueryForID(Integer, int, DistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.database.SequentialDatabase

Retrieves the k nearest neighbors for the query object.

kNNQueryForID(Integer, int, DistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.database.SpatialIndexDatabase

kNNQueryForObject(O, int, DistanceFunction<O, D>) - Method in interface de.lmu.ifi.dbs.elki.database.Database

Performs a k-nearest neighbor query for the given object.

kNNQueryForObject(O, int, DistanceFunction<O, T>) - Method in class de.lmu.ifi.dbs.elki.database.MetricalIndexDatabase

kNNQueryForObject(O, int, DistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.database.SequentialDatabase

Retrieves the k nearest neighbors for the query object.

kNNQueryForObject(O, int, DistanceFunction<O, D>) - Method in class de.lmu.ifi.dbs.elki.database.SpatialIndexDatabase