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.AbstractProjectedClustering

Holds the value of AbstractProjectedClustering.K_ID.

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

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

Holds the value of EM.K_ID.

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

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

Holds the value of KMeans.K_ID.

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

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

Holds the value of KNNDistanceOrder.K_ID.

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

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

The k parameter

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

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.ABOD.Parameterizer

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

The target dimensionality.

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

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

Holds the value of INFLO.K_ID.

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

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

The parameter k

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

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

Holds the value of KNNWeightOutlier.K_ID.

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

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

Holds the value of LDOF.K_ID.

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

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

Holds the value of LOF.K_ID.

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

The neighborhood size to use

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

The parameters k for LOF.

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.FeatureBagging.Parameterizer

The neighborhood size to use

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

The neighborhood size to use

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

Holds the value of ReferenceBasedOutlierDetection.K_ID.

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

Holds the value of ReferenceBasedOutlierDetection.K_ID.

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

Parameter k - neighborhood size

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm.Parameterizer

Parameter k - neighborhood size

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

Parameter k

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer

Parameter for kNN

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.PrecomputedKNearestNeighborNeighborhood.Factory

parameter k

k - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer

Parameter k

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

k - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.distribution.GammaDistribution

Alpha == k

k - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractRandomFeatureSelectionFilter

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

k - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractRandomFeatureSelectionFilter.Parameterizer

k - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.MinKDistance.Instance

Value for k

k - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.MinKDistance

The value of k

k - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.MinKDistance.Parameterizer

The value of k

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory

Holds the value of AbstractMaterializeKNNPreprocessor.Factory.K_ID.

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory.Parameterizer

Holds the value of AbstractMaterializeKNNPreprocessor.Factory.K_ID.

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor

The query k value.

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex.Factory

Holds the value of KNNQueryFilteredPCAIndex.Factory.K_ID.

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex.Factory.Parameterizer

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex

Query k

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex.Factory

Holds the value of parameter HiSCPreferenceVectorIndex.Factory.K_ID.

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex.Factory.Parameterizer

Holds the value of parameter HiSCPreferenceVectorIndex.Factory.K_ID.

k - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex

Holds the value of parameter k.

k - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNList

The value of k this was materialized for.

k - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierGammaScaling

Gamma parameter k

k - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.TopKOutlierScaling

Number of outliers to keep.

k - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.TopKOutlierScaling.Parameterizer

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.AbstractProjectedClustering

Holds the value of AbstractProjectedClustering.K_I_ID.

k_i - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedClustering.Parameterizer

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

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.AbstractProjectedClustering

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

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

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

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

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

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

OptionID for the target dimensionality

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

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

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

Parameter to specify the k nearest neighbor

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

Parameter to specify the k nearest neighbor

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

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

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

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

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm.Parameterizer

Parameter to specify the k nearest neighbors

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer

Parameter to specify the number of neighbors

K_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer

Parameter k

K_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.MinKDistance

OptionID for the "k" parameter.

K_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory

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

K_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex.Factory

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

K_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex.Factory

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

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

Parameter for k

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

Parameter for k

K_ID - Static variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.TopKOutlierScaling

Parameter to specify the number of outliers to keep Key: -topk.k

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

Holds the maximum value of k to support.

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

Holds the value of parameter AbstractMkTreeUnifiedFactory.K_MAX_ID.

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

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.mkapp.MkAppTreeFactory

Parameter k.

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

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.mkcop.MkCopTreeFactory

Parameter k.

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

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

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

kappa - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj.PreDeConSubspaceIndex

The kappa value for generating the variance vector.

KAPPA - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d.EMClusterVisualization

kcomp - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LoOP

Holds the value of LoOP.KCOMP_ID.

kcomp - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LoOP.Parameterizer

Holds the value of LoOP.KCOMP_ID.

KCOMP_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LoOP

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

KDDCLIApplication - Class in de.lmu.ifi.dbs.elki.application

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

KDDCLIApplication(boolean, KDDTask) - Constructor for class de.lmu.ifi.dbs.elki.application.KDDCLIApplication

Constructor.

KDDCLIApplication.Parameterizer - Class in de.lmu.ifi.dbs.elki.application

Parameterization class.

KDDCLIApplication.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.application.KDDCLIApplication.Parameterizer

KDDTask - 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(InputStep, AlgorithmStep, EvaluationStep, OutputStep, Collection<Pair<Object, Parameter<?, ?>>>) - Constructor for class de.lmu.ifi.dbs.elki.KDDTask

Constructor.

KDDTask.Parameterizer - Class in de.lmu.ifi.dbs.elki

Parameterization class.

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

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

The kernel matrix

KERNEL - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.EpanechnikovKernelDensityFunction

Static instance.

KERNEL - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.GaussianKernelDensityFunction

Static instance.

KERNEL - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.TriangularKernelDensityFunction

Static instance.

KERNEL - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.UniformKernelDensityFunction

Static instance.

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

Parameter for the kernel function.

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

Estimate density given an array of points.

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

Initialize and execute kernel density estimation.

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

Process an array of data

KernelDensityFunction - Interface in de.lmu.ifi.dbs.elki.math.statistics

Inner function of a kernel density estimator.

KernelMatrix - 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(PrimitiveSimilarityFunction<? super O, DoubleDistance>, Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix

Deprecated.

ID mapping is not reliable!

KernelMatrix(PrimitiveSimilarityFunction<? super O, DoubleDistance>, Relation<? extends O>, ArrayDBIDs) - 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 (with data copying).

KEY - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary

Key

keymap - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.TermFrequencyParser

Map

KeyVisFactory - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj

Pseudo-Visualizer, that gives the key for a clustering.

KeyVisFactory() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.KeyVisFactory

Constructor, adhering to Parameterizable

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

Provides the k-means algorithm.

KMeans(PrimitiveDistanceFunction<? super V, D>, int, int, Long) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.KMeans

Constructor.

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

Parameterization class.

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

KMLOutputHandler - Class in de.lmu.ifi.dbs.elki.result

Class to handle KML output.

KMLOutputHandler(File, OutlierScalingFunction, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.result.KMLOutputHandler

Constructor.

KMLOutputHandler.Parameterizer - Class in de.lmu.ifi.dbs.elki.result

Parameterization class

KMLOutputHandler.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.result.KMLOutputHandler.Parameterizer

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

Holds the value of SOD.KNN_ID.

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

Holds the value of SOD.KNN_ID.

KNN_ID - Static 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.

KNNChangeEvent - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn

Encapsulates information describing changes of the k nearest neighbors (kNNs) of some objects due to insertion or removal of objects.

KNNChangeEvent(Object, KNNChangeEvent.Type, DBIDs, DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.KNNChangeEvent

Used to create an event when kNNs of some objects have been changed.

KNNChangeEvent.Type - Enum in de.lmu.ifi.dbs.elki.index.preprocessed.knn

Available event types.

KNNChangeEvent.Type() - Constructor for enum de.lmu.ifi.dbs.elki.index.preprocessed.knn.KNNChangeEvent.Type

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(DistanceQuery<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.

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

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

kNNdistanceAdjustment(MkMaxEntry<D>, Map<DBID, KNNHeap<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<DBID, KNNHeap<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,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(DistanceFunction<O, D>, int, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.KNNDistanceOrder

Constructor.

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

Parameterization class.

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

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

Wraps a list containing the knn distances.

KNNDistanceOrderResult(String, String, 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(O) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeIndex

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

kNNDistances(DistanceQuery<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<?,?>,D extends NumberDistance<D,?>> - 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(boolean, Database, DistanceFunction<O, D>) - Constructor for class de.lmu.ifi.dbs.elki.application.visualization.KNNExplorer

Constructor.

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

Main window of KNN Explorer.

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

Constructor.

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

Renderer for the labels, with coloring as in the plot.

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

Constructor.

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

Parameterization class.

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

KNNHeap<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap

Heap used for KNN management.

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

Constructor.

KNNHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNHeap

Simplified constructor.

KNNHeap.Comp<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap

Comparator to use.

KNNHeap.Comp() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNHeap.Comp

KNNIndex<O> - Interface in de.lmu.ifi.dbs.elki.index

Index with support for kNN queries.

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(DistanceFunction<? super V, D>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.KNNJoin

Constructor.

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

Parameterization class.

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

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

Finalized KNN List.

KNNList(KNNHeap<D>, D) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNList

Constructor, to be called from KNNHeap only!

KNNList.DBIDItr - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap

Proxy iterator for accessing DBIDs.

KNNList.DBIDItr(Iterator<? extends DistanceResultPair<?>>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNList.DBIDItr

Constructor.

KNNList.DBIDView - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap

A view on the DBIDs of the result

KNNList.DBIDView(List<? extends DistanceResultPair<?>>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNList.DBIDView

Constructor.

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

Proxy iterator for accessing DBIDs.

KNNList.DistanceItr(Iterator<? extends DistanceResultPair<D>>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNList.DistanceItr

Constructor.

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

A view on the Distances of the result

KNNList.DistanceView(List<? extends DistanceResultPair<D>>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNList.DistanceView

Constructor.

KNNListener - Interface in de.lmu.ifi.dbs.elki.index.preprocessed.knn

Listener interface invoked when the k nearest neighbors (kNNs) of some objects have been changed due to insertion or removals of objects.

KNNOutlier<O,D extends NumberDistance<D,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier

Outlier Detection based on the distance of an object to its k nearest neighbor.

KNNOutlier(DistanceFunction<? super O, D>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.KNNOutlier

Constructor for a single kNN query.

KNNOutlier.Parameterizer<O,D extends NumberDistance<D,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier

Parameterization class.

KNNOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.KNNOutlier.Parameterizer

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

Holds the associated kNN query

KNNQuery<O,D extends Distance<D>> - Interface in de.lmu.ifi.dbs.elki.database.query.knn

The interface of an actual instance.

knnQuery - Variable in class de.lmu.ifi.dbs.elki.database.query.rknn.LinearScanRKNNQuery

KNN query we use.

knnQuery - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.MinKDistance.Instance

KNN query instance

knnQuery - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNPreprocessor

KNNQuery instance to use.

knnQuery - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex

The kNN query instance we use

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

The knn query we use internally.

KNNQUERY_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.KNNWeightOutlier

The kNN query used.

KNNQUERY_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.MinKDistance

OptionID for the KNN query class to use (preprocessor, approximation, ...)

KNNQueryFilteredPCAIndex<NV extends NumberVector<? extends NV,?>> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Provides the local neighborhood to be considered in the PCA as the k nearest neighbors of an object.

KNNQueryFilteredPCAIndex(Relation<NV>, PCAFilteredRunner<NV>, KNNQuery<NV, DoubleDistance>, int) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex

Constructor.

KNNQueryFilteredPCAIndex.Factory<V extends NumberVector<V,?>> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Factory class

KNNQueryFilteredPCAIndex.Factory(DistanceFunction<V, DoubleDistance>, PCAFilteredRunner<V>, Integer) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex.Factory

Constructor.

KNNQueryFilteredPCAIndex.Factory.Parameterizer<NV extends NumberVector<NV,?>> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Parameterization class.

KNNQueryFilteredPCAIndex.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex.Factory.Parameterizer

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

The kNN query w.r.t. the reachability distance.

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

The kNN query w.r.t. the reference neighborhood distance.

kNNsChanged(KNNChangeEvent) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.OnlineLOF.LOFKNNListener

kNNsChanged(KNNChangeEvent, KNNChangeEvent) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.OnlineLOF.LOFKNNListener

Invoked after the events of both preprocessors have been received, i.e.

kNNsChanged(KNNChangeEvent) - Method in interface de.lmu.ifi.dbs.elki.index.preprocessed.knn.KNNListener

Invoked after kNNs have been updated, inserted or removed in some way.

kNNsInserted(DBIDs, DBIDs, DBIDs, LOF.LOFResult<O, D>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.OnlineLOF.LOFKNNListener

Invoked after kNNs have been inserted and updated, updates the result.

kNNsRemoved(DBIDs, DBIDs, DBIDs, LOF.LOFResult<O, D>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.OnlineLOF.LOFKNNListener

Invoked after kNNs have been removed and updated, updates the result.

KNNWeightOutlier<O,D extends NumberDistance<D,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier

Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.

KNNWeightOutlier(DistanceFunction<? super O, D>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.KNNWeightOutlier

Constructor with parameters.

KNNWeightOutlier.Parameterizer<O,D extends NumberDistance<D,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier

Parameterization class.

KNNWeightOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.KNNWeightOutlier.Parameterizer

kreach - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LoOP

Holds the value of LoOP.KREACH_ID.

kreach - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LoOP.Parameterizer

Holds the value of LoOP.KREACH_ID.

KREACH_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.LoOP

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

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