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

Keeps k - the number of clusters to find.

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

Keeps k - the number of clusters to find.

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

Number of clusters.

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.index.tree.metrical.mtreevariants.mkmax.MkMaxTreeHeader

The parameter k.

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

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.utilities.KNNList

The maximum size of this list.

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

The start value for k.

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

Description for parameter k.

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

Description for parameter k.

K_D - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkmax.MkMaxTree

Description for parameter k.

K_D - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktab.MkTabTree

Description for parameter k.

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

Description for parameter k.

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

Description for parameter k.

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

Multiplier for initial number of seeds.

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

Parameter k.

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

Parameter k.

k_max - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkmax.MkMaxTree

Parameter k.

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

Parameter k.

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

Parameter k.

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

Parameter k.

K_P - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkmax.MkMaxTree

Parameter k.

K_P - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktab.MkTabTree

Parameter k.

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

Parameter k.

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

Option string for parameter k.

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.preprocessing.KnnQueryBasedHiCOPreprocessor

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

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

The kappa value for generating the variance vector.

KDD_FRAMEWORK_PROPERTIES - Static variable in class de.lmu.ifi.dbs.elki.properties.Properties

The Properties for the KDDFramework.

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

Description for parameter kernel.

KERNEL_FUNCTION_CLASS_D - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.KernelFourCPreprocessor

Description for parameter preprocessor.

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

Parameter for kernel.

KERNEL_FUNCTION_CLASS_P - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.KernelFourCPreprocessor

Parameter for preprocessor.

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

The association id to associate a kernel matrix.

KernelBasedLocallyWeightedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> - 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.

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

Preprocessor for kernel 4C local dimensionality, neighbor objects and strong eigenvector matrix assignment to objects of a certain database.

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

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.

KMEANS_K - Static variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID

OptionID for KMeans.K_PARAM

KNN_HICO_PREPROCESSOR_K - Static variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID

OptionID for KnnQueryBasedHiCOPreprocessor.K_PARAM

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

The aggregated knn distance of the underlying MkMax-Tree node.

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

The knn distance of the underlying data object.

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

Determines and returns the knn distance of this node as the maximum knn distance 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

knnDistanceApproximation() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.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<O extends DatabaseObject,D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.algorithm.result

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

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

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

The aggregated knn distances of the underlying node.

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

The knn distances of the underlying data object.

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

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

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.

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

Provides the result of a kNN-Join.

KNNJoinResult(HashMap<Integer, KNNList<D>>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.result.KNNJoinResult

Creates a new KNNJoinResult.

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

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

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

Creates a new KNNList with the specified parameters.

knnLists - Variable in class de.lmu.ifi.dbs.elki.algorithm.result.KNNJoinResult

The kNN lists for each object.

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

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

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

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

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, D>) - Method in class de.lmu.ifi.dbs.elki.database.InvertedListDatabase

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

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

kParameter - Variable in class de.lmu.ifi.dbs.elki.preprocessing.FracClusPreprocessor