Uses of Interface
elki.distance.Distance

Packages that use Distance

Package	Description
elki.algorithm	Miscellaneous algorithms.
elki.algorithm.statistics	Statistical analysis algorithms.
elki.application	Base classes for standalone applications.
elki.application.benchmark	Benchmarking pseudo algorithms.
elki.application.cache	Utility applications for the persistence layer such as distance cache builders.
elki.application.greedyensemble	Greedy ensembles for outlier detection.
elki.application.statistics	Applications to compute some basic data set statistics.
elki.classification	Classification algorithms.
elki.clustering	Clustering algorithms.
elki.clustering.affinitypropagation	Affinity Propagation (AP) clustering.
elki.clustering.dbscan	DBSCAN and its generalizations.
elki.clustering.dbscan.predicates	Neighbor and core predicated for Generalized DBSCAN.
elki.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
elki.clustering.kcenter	K-center clustering.
elki.clustering.kmedoids	K-medoids clustering (PAM).
elki.clustering.optics	OPTICS family of clustering algorithms.
elki.clustering.silhouette	Silhouette clustering algorithms.
elki.database.query	Database queries - computing distances, neighbors, similarities - API and general documentation.
elki.database.query.distance	Prepared queries for distances.
elki.distance	Distance functions for use within ELKI.
elki.distance.adapter	Distance functions deriving distances from, e.g., similarity measures.
elki.distance.colorhistogram	Distance functions for color histograms.
elki.distance.correlation	Distance functions using correlations.
elki.distance.external	Distance functions using external data sources.
elki.distance.geo	Geographic (earth) distance functions.
elki.distance.histogram	Distance functions for one-dimensional histograms.
elki.distance.minkowski	Minkowski space Lp norms such as the popular Euclidean and Manhattan distances.
elki.distance.probabilistic	Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence, F-divergence, χ²-divergence, etc.
elki.distance.set	Distance functions for binary and set type data.
elki.distance.strings	Distance functions for strings.
elki.distance.subspace	Distance functions based on subspaces.
elki.distance.timeseries	Distance functions designed for time series.
elki.evaluation.clustering.internal	Internal evaluation measures for clusterings.
elki.evaluation.similaritymatrix	Render a distance matrix to visualize a clustering-distance-combination.
elki.index	Index structure implementations.
elki.index.distancematrix	Precomputed distance matrix.
elki.index.idistance	iDistance is a distance based indexing technique, using a reference points embedding.
elki.index.laesa	Linear Approximating and Eliminating Search Algorithm (LAESA).
elki.index.lsh.hashfamilies	Hash function families for LSH.
elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
elki.index.preprocessed.snn	Indexes providing nearest neighbor sets.
elki.index.tree.metrical	Tree-based index structures for metrical vector spaces.
elki.index.tree.metrical.covertree	Cover-tree variations.
elki.index.tree.metrical.mtreevariants	M-tree and variants.
elki.index.tree.metrical.vptree
elki.outlier	Outlier detection algorithms.
elki.outlier.clustering	Clustering based outlier detection.
elki.outlier.distance	Distance-based outlier detection algorithms, such as DBOutlier and kNN.
elki.outlier.distance.parallel	Parallel implementations of distance-based outlier detectors.
elki.outlier.intrinsic	Outlier detection algorithms based on intrinsic dimensionality.
elki.outlier.lof	LOF family of outlier detection algorithms.
elki.outlier.lof.parallel	Parallelized variants of LOF.
elki.outlier.spatial	Spatial outlier detection algorithms.
elki.outlier.spatial.neighborhood	Spatial outlier neighborhood classes.
elki.projection	Data projections (see also preprocessing filters for basic projections).
elki.similarity	Similarity functions.
elki.similarity.cluster	Similarity measures for comparing clusters.
elki.similarity.kernel	Kernel functions.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.
tutorial.distancefunction	Classes from the tutorial on implementing distance functions.
tutorial.outlier	Tutorials on implementing outlier detection methods in ELKI.

Uses of Distance in elki.algorithm

Fields in elki.algorithm declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	KNNDistancesSampler.distance	Distance function used.
protected Distance<? super O>	KNNDistancesSampler.Par.distance	The distance function to use.

Constructors in elki.algorithm with parameters of type Distance

Constructor	Description
KNNDistancesSampler(Distance<? super O> distance, int k, double sample, RandomFactory rnd)	Constructor.

Uses of Distance in elki.algorithm.statistics

Fields in elki.algorithm.statistics declared as Distance

Modifier and Type	Field	Description
private Distance<? super O>	AveragePrecisionAtK.distance	Distance function used.
protected Distance<? super O>	AveragePrecisionAtK.Par.distance	The distance function to use.
private Distance<? super O>	DistanceQuantileSampler.distance	Distance function used.
protected Distance<? super O>	DistanceQuantileSampler.Par.distance	The distance function to use.
protected Distance<? super O>	DistanceStatisticsWithClasses.distance	Distance function used.
protected Distance<? super O>	DistanceStatisticsWithClasses.Par.distance	The distance function to use.
protected Distance<? super V>	EvaluateRankingQuality.distance	Distance function used.
protected Distance<? super V>	EvaluateRankingQuality.Par.distance	The distance function to use.
protected Distance<? super O>	EvaluateRetrievalPerformance.distance	Distance function used.
protected Distance<? super O>	EvaluateRetrievalPerformance.Par.distance	The distance function to use.
protected Distance<? super O>	RankingQualityHistogram.distance	Distance function used.
protected Distance<? super O>	RankingQualityHistogram.Par.distance	The distance function to use.

Constructors in elki.algorithm.statistics with parameters of type Distance

Constructor	Description
AveragePrecisionAtK(Distance<? super O> distance, int k, double sampling, RandomFactory random, boolean includeSelf)	Constructor.
DistanceQuantileSampler(Distance<? super O> distance, double quantile, double sampling, boolean nozeros, RandomFactory rand)	Constructor.
DistanceStatisticsWithClasses(Distance<? super O> distance, int numbins, boolean exact, boolean sampling)	Constructor.
EvaluateRankingQuality(Distance<? super V> distance, int numbins)	Constructor.
EvaluateRetrievalPerformance(Distance<? super O> distance, double sampling, RandomFactory random, boolean includeSelf, int maxk)	Constructor.
RankingQualityHistogram(Distance<? super O> distance, int numbins)	Constructor.

Uses of Distance in elki.application

Fields in elki.application declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractDistanceBasedApplication.distance	Distance function to use.
protected Distance<? super O>	AbstractDistanceBasedApplication.Par.distance	Distance function to use

Constructors in elki.application with parameters of type Distance

Constructor	Description
AbstractDistanceBasedApplication(InputStep inputstep, Distance<? super O> distance)	Constructor.

Uses of Distance in elki.application.benchmark

Constructors in elki.application.benchmark with parameters of type Distance

Constructor	Description
KNNBenchmark(InputStep inputstep, Distance<? super O> distance, int k, DatabaseConnection queries, double sampling, RandomFactory random)	Constructor.
PrioritySearchBenchmark(InputStep inputstep, Distance<? super O> distance, int k, DatabaseConnection queries, double sampling, RandomFactory random)	Constructor.
RangeQueryBenchmark(InputStep input, Distance<? super O> distance, double radius, double sampling, RandomFactory random)	Constructor.
RangeQueryBenchmark(InputStep input, Distance<? super O> distance, DatabaseConnection queries, double sampling, RandomFactory random)	Constructor.
ValidateApproximativeKNNIndex(InputStep input, Distance<? super O> distance, int k, DatabaseConnection queries, double sampling, boolean forcelinear, RandomFactory random, java.util.regex.Pattern pattern)	Constructor.

Uses of Distance in elki.application.cache

Fields in elki.application.cache declared as Distance

Modifier and Type	Field	Description
private Distance<? super O>	CacheDoubleDistanceInOnDiskMatrix.distance	Distance function that is to be cached.
private Distance<? super O>	CacheDoubleDistanceInOnDiskMatrix.Par.distance	Distance function that is to be cached.
private Distance<? super O>	CacheDoubleDistanceKNNLists.distance	Distance function that is to be cached.
private Distance<? super O>	CacheDoubleDistanceKNNLists.Par.distance	Distance function that is to be cached.
private Distance<? super O>	CacheDoubleDistanceRangeQueries.distance	Distance function that is to be cached.
private Distance<? super O>	CacheDoubleDistanceRangeQueries.Par.distance	Distance function that is to be cached.
private Distance<? super O>	CacheFloatDistanceInOnDiskMatrix.distance	Distance function that is to be cached.
private Distance<? super O>	CacheFloatDistanceInOnDiskMatrix.Par.distance	Distance function that is to be cached.
private Distance<? super O>	PrecomputeDistancesAsciiApplication.distance	Distance function that is to be cached.
private Distance<? super O>	PrecomputeDistancesAsciiApplication.Par.distance	Distance function that is to be cached.

Constructors in elki.application.cache with parameters of type Distance

Constructor	Description
CacheDoubleDistanceInOnDiskMatrix(Database database, Distance<? super O> distance, java.nio.file.Path out)	Constructor.
CacheDoubleDistanceKNNLists(Database database, Distance<? super O> distance, int k, java.nio.file.Path out)	Constructor.
CacheDoubleDistanceRangeQueries(Database database, Distance<? super O> distance, double radius, java.nio.file.Path out)	Constructor.
CacheFloatDistanceInOnDiskMatrix(Database database, Distance<? super O> distance, java.nio.file.Path out)	Constructor.
PrecomputeDistancesAsciiApplication(Database database, Distance<? super O> distance, java.nio.file.Path out)	Constructor.

Uses of Distance in elki.application.greedyensemble

Constructors in elki.application.greedyensemble with parameters of type Distance

Constructor	Description
ComputeKNNOutlierScores(InputStep inputstep, Distance<? super O> distance, IntGenerator krange, ByLabelOutlier bylabel, java.nio.file.Path outfile, ScalingFunction scaling, java.util.regex.Pattern disable, int ksquarestop, long timelimit)	Constructor.

Uses of Distance in elki.application.statistics

Constructors in elki.application.statistics with parameters of type Distance

Constructor	Description
EstimateIntrinsicDimensionality(InputStep inputstep, Distance<? super O> distance, IntrinsicDimensionalityEstimator<? super O> estimator, double krate, double samples)	Constructor.
RangeQuerySelectivity(InputStep inputstep, Distance<? super V> distance, double radius, double sampling, RandomFactory random)	Constructor.

Uses of Distance in elki.classification

Fields in elki.classification declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	KNNClassifier.distance	Distance function
protected Distance<? super O>	KNNClassifier.Par.distanceFunction	Distance function

Methods in elki.classification that return Distance

Modifier and Type	Method	Description
Distance<? super O>	KNNClassifier.getDistance()	Returns the distance.

Constructors in elki.classification with parameters of type Distance

Constructor	Description
KNNClassifier(Distance<? super O> distance, int k)	Constructor.

Uses of Distance in elki.clustering

Fields in elki.clustering declared as Distance

Modifier and Type	Field	Description
private Distance<? super O>	CanopyPreClustering.distance	Distance function used.
protected Distance<? super O>	CanopyPreClustering.Par.distance	The distance function to use.
protected Distance<? super O>	CFSFDP.distance	Distance function used.
protected Distance<? super O>	CFSFDP.Par.distance	The distance function to use.
protected Distance<? super O>	Leader.distance	Distance function used.
protected Distance<? super O>	Leader.Par.distance	The distance function to use.

Constructors in elki.clustering with parameters of type Distance

Constructor	Description
CanopyPreClustering(Distance<? super O> distance, double t1, double t2)	Constructor.
CFSFDP(Distance<? super O> distance, double dc, int k)	Constructor.
Leader(Distance<? super O> distance, double threshold)	Constructor.

Uses of Distance in elki.clustering.affinitypropagation

Fields in elki.clustering.affinitypropagation declared as Distance

Modifier and Type	Field	Description
(package private) Distance<? super O>	DistanceBasedInitializationWithMedian.distance	Distance function.
(package private) Distance<? super O>	DistanceBasedInitializationWithMedian.Par.distance	istance function.

Constructors in elki.clustering.affinitypropagation with parameters of type Distance

Constructor	Description
DistanceBasedInitializationWithMedian(Distance<? super O> distance, double quantile)	Constructor.

Uses of Distance in elki.clustering.dbscan

Fields in elki.clustering.dbscan declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	DBSCAN.distance	Distance function used.
protected Distance<? super O>	DBSCAN.Par.distance	The distance function to use.
protected Distance<? super V>	GriDBSCAN.distance	Distance function used.
protected Distance<? super V>	GriDBSCAN.Instance.distance	Distance function used.
protected Distance<? super O>	LSDBC.distance	Distance function used.
protected Distance<? super O>	LSDBC.Par.distance	The distance function to use.

Constructors in elki.clustering.dbscan with parameters of type Distance

Constructor	Description
DBSCAN(Distance<? super O> distance, double epsilon, int minpts)	Constructor with parameters.
GriDBSCAN(Distance<? super V> distance, double epsilon, int minpts, double gridwidth)	Constructor with parameters.
Instance(Distance<? super V> distance, double epsilon, int minpts, double gridwidth)	Constructor.
LSDBC(Distance<? super O> distance, int k, double alpha)	Constructor.

Uses of Distance in elki.clustering.dbscan.predicates

Fields in elki.clustering.dbscan.predicates declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractRangeQueryNeighborPredicate.distance	Distance function to use.
protected Distance<? super O>	EpsilonNeighborPredicate.distance	Distance function to use
(package private) Distance<O>	AbstractRangeQueryNeighborPredicate.Par.distfun	Distance function to use
protected Distance<O>	EpsilonNeighborPredicate.Par.distfun	Distance function to use

Constructors in elki.clustering.dbscan.predicates with parameters of type Distance

Constructor	Description
AbstractRangeQueryNeighborPredicate(double epsilon, Distance<? super O> distance)	Full constructor.
EpsilonNeighborPredicate(double epsilon, Distance<? super O> distance)	Full constructor.

Uses of Distance in elki.clustering.hierarchical

Fields in elki.clustering.hierarchical declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractHDBSCAN.distance	Distance function used.
protected Distance<? super O>	AbstractHDBSCAN.Par.distance	The distance function to use.
protected Distance<? super O>	AGNES.distance	Distance function used.
protected Distance<? super O>	AGNES.Par.distance	The distance function to use.
protected Distance<? super O>	Anderberg.Par.distance	The distance function to use.
protected Distance<? super O>	CLINK.Par.distance	The distance function to use.
protected Distance<? super O>	HACAM.distance	Distance to use
protected Distance<? super O>	HACAM.Par.distance	The distance function to use.
protected Distance<? super O>	MedoidLinkage.distance	The distance function to use.
protected Distance<? super O>	MedoidLinkage.Par.distance	The distance function to use.
protected Distance<? super O>	MiniMax.distance	Distance function used.
protected Distance<? super O>	MiniMax.Par.distance	The distance function to use.
protected Distance<? super O>	SLINK.distance	Distance function used.
protected Distance<? super O>	SLINK.Par.distance	The distance function to use.

Constructors in elki.clustering.hierarchical with parameters of type Distance

Constructor	Description
AbstractHDBSCAN(Distance<? super O> distance, int minPts)	Constructor.
AGNES(Distance<? super O> distance, Linkage linkage)	Constructor.
Anderberg(Distance<? super O> distance, Linkage linkage)	Constructor.
CLINK(Distance<? super O> distance)	Constructor.
HACAM(Distance<? super O> distance, HACAM.Variant variant)	Constructor.
HDBSCANLinearMemory(Distance<? super O> distance, int minPts)	Constructor.
MedoidLinkage(Distance<? super O> distance)	Constructor.
MiniMax(Distance<? super O> distance)	Constructor.
MiniMaxAnderberg(Distance<? super O> distance)	Constructor.
MiniMaxNNChain(Distance<? super O> distance)	Constructor.
NNChain(Distance<? super O> distance, Linkage linkage)	Constructor.
SLINK(Distance<? super O> distance)	Constructor.
SLINKHDBSCANLinearMemory(Distance<? super O> distance, int minPts)	Constructor.

Uses of Distance in elki.clustering.kcenter

Fields in elki.clustering.kcenter declared as Distance

Modifier and Type	Field	Description
(package private) Distance<? super O>	GreedyKCenter.distance	Distance function
(package private) Distance<? super O>	GreedyKCenter.Par.distance	Distance function to use

Constructors in elki.clustering.kcenter with parameters of type Distance

Constructor	Description
GreedyKCenter(int k, Distance<? super O> distance, RandomFactory rand)	Constructor.

Uses of Distance in elki.clustering.kmedoids

Fields in elki.clustering.kmedoids declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AlternatingKMedoids.distance	Distance function used.
protected Distance<? super V>	AlternatingKMedoids.Par.distance	The distance function to use.
protected Distance<? super O>	CLARANS.distance	Distance function used.
protected Distance<? super V>	CLARANS.Par.distance	The distance function to use.
protected Distance<? super O>	PAM.distance	Distance function used.
protected Distance<? super O>	PAM.Par.distance	The distance function to use.

Methods in elki.clustering.kmedoids that return Distance

Modifier and Type	Method	Description
Distance<? super V>	CLARA.CachedDistanceQuery.getDistance()

Constructors in elki.clustering.kmedoids with parameters of type Distance

Constructor	Description
AlternatingKMedoids(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
CLARA(Distance<? super V> distance, int k, int maxiter, KMedoidsInitialization<V> initializer, int numsamples, double sampling, boolean keepmed, RandomFactory random)	Constructor.
CLARANS(Distance<? super O> distance, int k, int numlocal, double maxneighbor, RandomFactory random)	Constructor.
EagerPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
FastCLARA(Distance<? super V> distance, int k, int maxiter, KMedoidsInitialization<V> initializer, double fasttol, int numsamples, double sampling, boolean keepmed, RandomFactory random)	Constructor.
FastCLARANS(Distance<? super V> distance, int k, int numlocal, double maxneighbor, RandomFactory random)	Constructor.
FasterCLARA(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer, int numsamples, double sampling, boolean keepmed, RandomFactory random)	Constructor.
FasterPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
FastPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
FastPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer, double fasttol)	Constructor.
FastPAM1(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
PAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
ReynoldsPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
SingleAssignmentKMedoids(Distance<? super O> distance, int k, KMedoidsInitialization<O> initializer)	Constructor.

Uses of Distance in elki.clustering.optics

Fields in elki.clustering.optics declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractOPTICS.distance	Distance function used.
protected Distance<? super O>	AbstractOPTICS.Par.distance	The distance function to use.

Constructors in elki.clustering.optics with parameters of type Distance

Constructor	Description
AbstractOPTICS(Distance<? super O> distance, double epsilon, int minpts)	Constructor.
OPTICSHeap(Distance<? super O> distance, double epsilon, int minpts)	Constructor.
OPTICSList(Distance<? super O> distance, double epsilon, int minpts)	Constructor.

Uses of Distance in elki.clustering.silhouette

Constructors in elki.clustering.silhouette with parameters of type Distance

Constructor	Description
FasterMSC(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
FastMSC(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
PAMMEDSIL(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.
PAMSIL(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.

Uses of Distance in elki.database.query

Fields in elki.database.query declared as Distance

Modifier and Type	Field	Description
private Distance<? super O>	QueryBuilder.distance	Distance to query

Methods in elki.database.query with parameters of type Distance

Modifier and Type	Method	Description
<O> DistanceQuery<O>	EmpiricalQueryOptimizer.getDistanceQuery(Relation<? extends O> relation, Distance<? super O> distance, int flags)
default <O> DistanceQuery<O>	QueryOptimizer.getDistanceQuery(Relation<? extends O> relation, Distance<? super O> distanceFunction, int flags)	Optimize a distance query for this relation.
private <O> DistancePriorityIndex<O>	EmpiricalQueryOptimizer.makeCoverTree(Relation<? extends O> relation, Distance<? super O> distance, int leafsize)
private <O> DistancePriorityIndex<O>	EmpiricalQueryOptimizer.makeKDTree(Relation<? extends O> relation, Distance<? super O> distance, int k)
private <O> DistancePriorityIndex<O>	EmpiricalQueryOptimizer.makeMatrixIndex(Relation<? extends O> relation, Distance<? super O> distance)
private <O> DistancePriorityIndex<O>	EmpiricalQueryOptimizer.makeVPTree(Relation<? extends O> relation, Distance<? super O> distance, int leafsize)

Constructors in elki.database.query with parameters of type Distance

Constructor	Description
QueryBuilder(Relation<O> relation, Distance<? super O> distance)	Constructor.

Uses of Distance in elki.database.query.distance

Methods in elki.database.query.distance that return Distance

Modifier and Type	Method	Description
Distance<? super O>	DistanceQuery.getDistance()	Get the inner distance function.

Uses of Distance in elki.distance

Classes in elki.distance with type parameters of type Distance

Modifier and Type	Class	Description
static class	AbstractIndexBasedDistance.Instance<O,I extends Index,F extends Distance<? super O>>	The actual instance bound to a particular database.

Subinterfaces of Distance in elki.distance

Modifier and Type	Interface	Description
interface	DBIDDistance	Distance functions valid in a database context only (i.e. for DBIDs)
interface	DBIDRangeDistance	Distance functions valid in a static database context only (i.e. for DBIDRanges) For any "distance" that cannot be computed for arbitrary objects, only those that exist in the database and referenced by their ID.
interface	IndexBasedDistance<O>	Distance function relying on an index (such as preprocessed neighborhoods).
interface	Norm<O>	Abstract interface for a mathematical norm.
interface	NumberVectorDistance<O>	Base interface for the common case of distance functions defined on numerical vectors.
interface	PrimitiveDistance<O>	Primitive distance function that is defined on some kind of object.
interface	SpatialPrimitiveDistance<V extends SpatialComparable>	API for a spatial primitive distance function.
interface	WeightedNumberVectorDistance<V>	Distance functions where each dimension is assigned a weight.

Classes in elki.distance that implement Distance

Modifier and Type	Class	Description
class	AbstractDatabaseDistance<O>	Abstract super class for distance functions needing a database context.
class	AbstractDBIDRangeDistance	Abstract base class for distance functions that rely on integer offsets within a consecutive range.
class	AbstractIndexBasedDistance<O,F extends IndexFactory<O>>	Abstract super class for distance functions needing a database index.
class	AbstractNumberVectorDistance	Abstract base class for the most common family of distance functions: defined on number vectors and returning double values.
class	ArcCosineDistance	Arcus cosine distance function for feature vectors.
class	ArcCosineUnitlengthDistance	Arcus cosine distance function for feature vectors.
class	BrayCurtisDistance	Bray-Curtis distance function / Sørensen–Dice coefficient for continuous vector spaces (not only binary data).
class	CanberraDistance	Canberra distance function, a variation of Manhattan distance.
class	ClarkDistance	Clark distance function for vector spaces.
class	CosineDistance	Cosine distance function for feature vectors.
class	CosineUnitlengthDistance	Cosine distance function for unit length feature vectors.
class	MahalanobisDistance	Mahalanobis quadratic form distance for feature vectors.
class	MatrixWeightedQuadraticDistance	Matrix weighted quadratic distance, the squared form of MahalanobisDistance.
class	RandomStableDistance	This is a dummy distance providing random values (obviously not metrical), useful mostly for unit tests and baseline evaluations: obviously this distance provides no benefit whatsoever.
class	SharedNearestNeighborJaccardDistance<O>	SharedNearestNeighborJaccardDistance computes the Jaccard coefficient, which is a proper distance metric.
class	SqrtCosineDistance	Cosine distance function for feature vectors using the square root.
class	SqrtCosineUnitlengthDistance	Cosine distance function for unit length feature vectors using the square root.
class	WeightedCanberraDistance	Weighted Canberra distance function, a variation of Manhattan distance.

Fields in elki.distance declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractDatabaseDistance.Instance.parent	Parent distance
protected F	AbstractIndexBasedDistance.Instance.parent	Our parent distance function

Methods in elki.distance that return Distance

Modifier and Type	Method	Description
Distance<? super O>	AbstractDatabaseDistance.Instance.getDistance()

Constructors in elki.distance with parameters of type Distance

Constructor	Description
Instance(Relation<O> relation, Distance<? super O> parent)	Constructor.

Uses of Distance in elki.distance.adapter

Classes in elki.distance.adapter that implement Distance

Modifier and Type	Class	Description
class	AbstractSimilarityAdapter<O>	Adapter from a similarity function to a distance function.
class	ArccosSimilarityAdapter<O>	Adapter from a normalized similarity function to a distance function using arccos(sim).
class	LinearSimilarityAdapter<O>	Adapter from a normalized similarity function to a distance function using 1 - sim.
class	LnSimilarityAdapter<O>	Adapter from a normalized similarity function to a distance function using -log(sim).

Constructors in elki.distance.adapter with parameters of type Distance

Constructor	Description
Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<? super O> similarityQuery)	Constructor.
Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<O> similarityQuery)	Constructor.
Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<? super O> similarityQuery)	Constructor.
Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<O> similarityQuery)	Constructor.

Uses of Distance in elki.distance.colorhistogram

Classes in elki.distance.colorhistogram that implement Distance

Modifier and Type	Class	Description
class	HistogramIntersectionDistance	Intersection distance for color histograms.
class	HSBHistogramQuadraticDistance	Distance function for HSB color histograms based on a quadratic form and color similarity.
class	RGBHistogramQuadraticDistance	Distance function for RGB color histograms based on a quadratic form and color similarity.

Uses of Distance in elki.distance.correlation

Classes in elki.distance.correlation that implement Distance

Modifier and Type	Class	Description
class	AbsolutePearsonCorrelationDistance	Absolute Pearson correlation distance function for feature vectors.
class	AbsoluteUncenteredCorrelationDistance	Absolute uncentered correlation distance function for feature vectors.
class	PearsonCorrelationDistance	Pearson correlation distance function for feature vectors.
class	SquaredPearsonCorrelationDistance	Squared Pearson correlation distance function for feature vectors.
class	SquaredUncenteredCorrelationDistance	Squared uncentered correlation distance function for feature vectors.
class	UncenteredCorrelationDistance	Uncentered correlation distance.
class	WeightedPearsonCorrelationDistance	Pearson correlation distance function for feature vectors.
class	WeightedSquaredPearsonCorrelationDistance	Weighted squared Pearson correlation distance function for feature vectors.

Uses of Distance in elki.distance.external

Classes in elki.distance.external that implement Distance

Modifier and Type	Class	Description
class	DiskCacheBasedDoubleDistance	Distance function that is based on double distances given by a distance matrix of an external binary matrix file.
class	DiskCacheBasedFloatDistance	Distance function that is based on float distances given by a distance matrix of an external binary matrix file.
class	FileBasedSparseDoubleDistance	Distance function that is based on double distances given by a distance matrix of an external ASCII file.
class	FileBasedSparseFloatDistance	Distance function that is based on float distances given by a distance matrix of an external ASCII file.

Uses of Distance in elki.distance.geo

Classes in elki.distance.geo that implement Distance

Modifier and Type	Class	Description
class	DimensionSelectingLatLngDistance	Distance function for 2D vectors in Latitude, Longitude form.
class	LatLngDistance	Distance function for 2D vectors in Latitude, Longitude form.
class	LngLatDistance	Distance function for 2D vectors in Longitude, Latitude form.

Uses of Distance in elki.distance.histogram

Classes in elki.distance.histogram that implement Distance

Modifier and Type	Class	Description
class	HistogramMatchDistance	Distance function based on histogram matching, i.e., Manhattan distance on the cumulative density function.
class	KolmogorovSmirnovDistance	Distance function based on the Kolmogorov-Smirnov goodness of fit test.

Uses of Distance in elki.distance.minkowski

Classes in elki.distance.minkowski that implement Distance

Modifier and Type	Class	Description
class	EuclideanDistance	Euclidean distance for NumberVectors.
class	LPIntegerNormDistance	Lp-Norm for NumberVectors, optimized version for integer values of p.
class	LPNormDistance	Lp-Norm (Minkowski norms) are a family of distances for NumberVectors.
class	ManhattanDistance	Manhattan distance for NumberVectors.
class	MaximumDistance	Maximum distance for NumberVectors.
class	MinimumDistance	Minimum distance for NumberVectors.
class	SparseEuclideanDistance	Euclidean distance function, optimized for SparseNumberVectors.
class	SparseLPNormDistance	Lp-Norm, optimized for SparseNumberVectors.
class	SparseManhattanDistance	Manhattan distance, optimized for SparseNumberVectors.
class	SparseMaximumDistance	Maximum distance, optimized for SparseNumberVectors.
class	SparseSquaredEuclideanDistance	Squared Euclidean distance function, optimized for SparseNumberVectors.
class	SquaredEuclideanDistance	Squared Euclidean distance, optimized for SparseNumberVectors.
class	WeightedEuclideanDistance	Weighted Euclidean distance for NumberVectors.
class	WeightedLPNormDistance	Weighted version of the Minkowski Lp norm distance for NumberVector.
class	WeightedManhattanDistance	Weighted version of the Manhattan (L1) metric.
class	WeightedMaximumDistance	Weighted version of the maximum distance function for NumberVectors.
class	WeightedSquaredEuclideanDistance	Weighted squared Euclidean distance for NumberVectors.

Uses of Distance in elki.distance.probabilistic

Classes in elki.distance.probabilistic that implement Distance

Modifier and Type	Class	Description
class	ChiDistance	χ distance function, symmetric version.
class	ChiSquaredDistance	χ² distance function, symmetric version.
class	FisherRaoDistance	Fisher-Rao riemannian metric for (discrete) probability distributions.
class	HellingerDistance	Hellinger metric / affinity / kernel, Bhattacharyya coefficient, fidelity similarity, Matusita distance, Hellinger-Kakutani metric on a probability distribution.
class	JeffreyDivergenceDistance	Jeffrey Divergence for NumberVectors is a symmetric, smoothened version of the KullbackLeiblerDivergenceAsymmetricDistance.
class	JensenShannonDivergenceDistance	Jensen-Shannon Divergence for NumberVectors is a symmetric, smoothened version of the KullbackLeiblerDivergenceAsymmetricDistance.
class	KullbackLeiblerDivergenceAsymmetricDistance	Kullback-Leibler divergence, also known as relative entropy, information deviation, or just KL-distance (albeit asymmetric).
class	KullbackLeiblerDivergenceReverseAsymmetricDistance	Kullback-Leibler divergence, also known as relative entropy, information deviation or just KL-distance (albeit asymmetric).
class	SqrtJensenShannonDivergenceDistance	The square root of Jensen-Shannon divergence is a metric.
class	TriangularDiscriminationDistance	Triangular Discrimination has relatively tight upper and lower bounds to the Jensen-Shannon divergence, but is much less expensive.
class	TriangularDistance	Triangular Distance has relatively tight upper and lower bounds to the (square root of the) Jensen-Shannon divergence, but is much less expensive.

Uses of Distance in elki.distance.set

Classes in elki.distance.set that implement Distance

Modifier and Type	Class	Description
class	AbstractSetDistance<O>	Abstract base class for set distance functions.
class	HammingDistance	Computes the Hamming distance of arbitrary vectors - i.e. counting, on how many places they differ.
class	JaccardSimilarityDistance	A flexible extension of Jaccard similarity to non-binary vectors.

Uses of Distance in elki.distance.strings

Classes in elki.distance.strings that implement Distance

Modifier and Type	Class	Description
class	LevenshteinDistance	Classic Levenshtein distance on strings.
class	NormalizedLevenshteinDistance	Levenshtein distance on strings, normalized by string length.

Uses of Distance in elki.distance.subspace

Subinterfaces of Distance in elki.distance.subspace

Modifier and Type	Interface	Description
interface	DimensionSelectingSubspaceDistance<O>	Interface for dimension selecting subspace distance functions.

Classes in elki.distance.subspace that implement Distance

Modifier and Type	Class	Description
class	AbstractDimensionsSelectingDistance<V extends FeatureVector<?>>	Abstract base class for distances computed only in subspaces.
class	OnedimensionalDistance	Distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension only.
class	SubspaceEuclideanDistance	Euclidean distance function between NumberVectors only in specified dimensions.
class	SubspaceLPNormDistance	Lp-Norm distance function between NumberVectors only in specified dimensions.
class	SubspaceManhattanDistance	Manhattan distance function between NumberVectors only in specified dimensions.
class	SubspaceMaximumDistance	Maximum distance function between NumberVectors only in specified dimensions.

Uses of Distance in elki.distance.timeseries

Classes in elki.distance.timeseries that implement Distance

Modifier and Type	Class	Description
class	AbstractEditDistance	Edit Distance for FeatureVectors.
class	DerivativeDTWDistance	Derivative Dynamic Time Warping distance for numerical vectors.
class	DTWDistance	Dynamic Time Warping distance (DTW) for numerical vectors.
class	EDRDistance	Edit Distance on Real Sequence distance for numerical vectors.
class	ERPDistance	Edit Distance With Real Penalty distance for numerical vectors.
class	LCSSDistance	Longest Common Subsequence distance for numerical vectors.

Uses of Distance in elki.evaluation.clustering.internal

Fields in elki.evaluation.clustering.internal declared as Distance

Modifier and Type	Field	Description
private Distance<? super O>	CIndex.distance	Distance function to use.
private Distance<? super O>	CIndex.Par.distance	Distance function to use.
private Distance<? super O>	DBCV.distance	Distance function to use.
private Distance<? super O>	DBCV.Par.distance	Distance function to use.
private Distance<? super O>	Silhouette.distance	Distance function to use.
private Distance<? super O>	Silhouette.Par.distance	Distance function to use.

Constructors in elki.evaluation.clustering.internal with parameters of type Distance

Constructor	Description
CIndex(Distance<? super O> distance, NoiseHandling noiseOpt)	Constructor.
DBCV(Distance<? super O> distance)	Constructor.
Silhouette(Distance<? super O> distance, boolean mergenoise)	Constructor.
Silhouette(Distance<? super O> distance, NoiseHandling noiseOption, boolean penalize)	Constructor.

Uses of Distance in elki.evaluation.similaritymatrix

Fields in elki.evaluation.similaritymatrix declared as Distance

Modifier and Type	Field	Description
private Distance<? super O>	ComputeSimilarityMatrixImage.distance	The distance function to use
private Distance<O>	ComputeSimilarityMatrixImage.Par.distance	The distance function to use

Constructors in elki.evaluation.similaritymatrix with parameters of type Distance

Constructor	Description
ComputeSimilarityMatrixImage(Distance<? super O> distance, ScalingFunction scaling, boolean skipzero)	Constructor.

Uses of Distance in elki.index

Methods in elki.index with parameters of type Distance

Modifier and Type	Method	Description
DistanceQuery<O>	DistanceIndex.getDistanceQuery(Distance<? super O> distanceFunction)	Get a KNN query object for the given distance query and k.

Uses of Distance in elki.index.distancematrix

Fields in elki.index.distancematrix declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	PrecomputedDistanceMatrix.distance	Nested distance function.
protected Distance<? super O>	PrecomputedDistanceMatrix.Factory.distance	Nested distance function.
protected Distance<? super O>	PrecomputedDistanceMatrix.Factory.Par.distanceFunction	Nested distance function.

Methods in elki.index.distancematrix that return Distance

Modifier and Type	Method	Description
Distance<? super O>	PrecomputedDistanceMatrix.PrecomputedDistanceQuery.getDistance()

Methods in elki.index.distancematrix with parameters of type Distance

Modifier and Type	Method	Description
DistanceQuery<O>	PrecomputedDistanceMatrix.getDistanceQuery(Distance<? super O> distanceFunction)

Constructors in elki.index.distancematrix with parameters of type Distance

Constructor	Description
Factory(Distance<? super O> distance)	Constructor.
PrecomputedDistanceMatrix(Relation<O> relation, DBIDRange range, Distance<? super O> distance)	Constructor.

Uses of Distance in elki.index.idistance

Fields in elki.index.idistance declared as Distance

Modifier and Type	Field	Description
(package private) Distance<? super V>	InMemoryIDistanceIndex.Factory.distance	Distance function to use.
(package private) Distance<? super V>	InMemoryIDistanceIndex.Factory.Par.distance	Distance function to use.

Methods in elki.index.idistance that return Distance

Modifier and Type	Method	Description
private Distance<? super O>	InMemoryIDistanceIndex.getDistance()	Distance function.

Constructors in elki.index.idistance with parameters of type Distance

Constructor	Description
Factory(Distance<? super V> distance, KMedoidsInitialization<V> initialization, int k)	Constructor.

Uses of Distance in elki.index.laesa

Fields in elki.index.laesa declared as Distance

Modifier and Type	Field	Description
(package private) Distance<? super O>	LAESA.distance	Distance function
(package private) Distance<? super O>	LAESA.Factory.distance	Distance function
(package private) Distance<? super O>	LAESA.Factory.Par.distance	Distance function

Constructors in elki.index.laesa with parameters of type Distance

Constructor	Description
Factory(Distance<? super O> distance, int m, int k, RandomFactory rng)	Constructor.
LAESA(Relation<O> relation, Distance<? super O> distance, int m, int k, RandomFactory rng)	Constructor.

Uses of Distance in elki.index.lsh.hashfamilies

Methods in elki.index.lsh.hashfamilies with parameters of type Distance

Modifier and Type	Method	Description
boolean	CosineHashFunctionFamily.isCompatible(Distance<?> df)
boolean	EuclideanHashFunctionFamily.isCompatible(Distance<?> df)
boolean	LocalitySensitiveHashFunctionFamily.isCompatible(Distance<?> df)	Check whether the given distance function can be accelerated using this hash family.
boolean	ManhattanHashFunctionFamily.isCompatible(Distance<?> df)

Uses of Distance in elki.index.preprocessed.knn

Fields in elki.index.preprocessed.knn declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractMaterializeKNNPreprocessor.distance	The distance function to be used.
protected Distance<? super O>	AbstractMaterializeKNNPreprocessor.Factory.distance	Hold the distance function to be used.
protected Distance<? super O>	AbstractMaterializeKNNPreprocessor.Factory.Par.distance	Hold the distance function to be used.

Methods in elki.index.preprocessed.knn that return Distance

Modifier and Type	Method	Description
Distance<? super O>	AbstractMaterializeKNNPreprocessor.Factory.getDistance()	Get the distance function.

Constructors in elki.index.preprocessed.knn with parameters of type Distance

Constructor	Description
AbstractMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)	Constructor.
CachedDoubleDistanceKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, java.nio.file.Path file)	Constructor.
Factory(int k, Distance<? super O> distance)	Index factory.
Factory(int k, Distance<? super O> distance, java.nio.file.Path filename)	Index factory.
Factory(int k, Distance<? super O> distance)	Constructor.
Factory(int k, Distance<? super O> distance)	Constructor.
Factory(int k, Distance<? super O> distance)	Index factory.
Factory(int k, Distance<? super O> distance)	Constructor.
Factory(int k, Distance<? super O> distance, RandomFactory rnd, double delta, double rho, boolean noInitialNeighbors, int iterations)	Constructor.
Factory(int k, Distance<? super O> distance, int partitions, RandomFactory rnd)	Constructor.
Factory(int k, Distance<? super O> distance, double share, RandomFactory rnd)	Constructor.
Factory(int k, Distance<? super V> distance, java.util.List<? extends SpatialSorter> curvegen, double window, int variants, RandomFactory random)	Constructor.
Factory(int k, Distance<? super NumberVector> distance)	Constructor.
KNNJoinMaterializeKNNPreprocessor(Relation<V> relation, Distance<? super V> distance, int k)	Constructor.
MaterializeKNNAndRKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)	Constructor.
MaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)	Constructor with preprocessing step.
MetricalIndexApproximationMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)	Constructor
NNDescent(Relation<O> relation, Distance<? super O> distance, int k, RandomFactory rnd, double delta, double rho, boolean noInitialNeighbors, int iterations)	Constructor.
PartitionApproximationMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, int partitions, RandomFactory rnd)	Constructor
RandomSampleKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, double share, RandomFactory rnd)	Constructor.
SpacefillingMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, java.util.List<? extends SpatialSorter> curvegen, double window, int variants, java.util.Random random)	Constructor.
SpatialApproximationMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)	Constructor

Uses of Distance in elki.index.preprocessed.snn

Fields in elki.index.preprocessed.snn declared as Distance

Modifier and Type	Field	Description
protected Distance<O>	SharedNearestNeighborPreprocessor.distance	Hold the distance function to be used.
protected Distance<O>	SharedNearestNeighborPreprocessor.Factory.distanceFunction	Hold the distance function to be used.
protected Distance<O>	SharedNearestNeighborPreprocessor.Factory.Par.distanceFunction	Hold the distance function to be used.

Constructors in elki.index.preprocessed.snn with parameters of type Distance

Constructor	Description
Factory(int numberOfNeighbors, Distance<O> distance)	Constructor.
SharedNearestNeighborPreprocessor(Relation<O> relation, int numberOfNeighbors, Distance<O> distance)	Constructor.

Uses of Distance in elki.index.tree.metrical

Methods in elki.index.tree.metrical that return Distance

Modifier and Type	Method	Description
abstract Distance<? super O>	MetricalIndexTree.getDistance()	Returns the distance function of this metrical index.

Uses of Distance in elki.index.tree.metrical.covertree

Fields in elki.index.tree.metrical.covertree declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractCoverTree.distance	Holds the instance of the trees distance function.
protected Distance<? super O>	AbstractCoverTree.Factory.distance	Holds the instance of the trees distance function.
protected Distance<? super O>	AbstractCoverTree.Factory.Par.distance	Holds the instance of the trees distance function.

Constructors in elki.index.tree.metrical.covertree with parameters of type Distance

Constructor	Description
AbstractCoverTree(Relation<O> relation, Distance<? super O> distance, double expansion, int truncate)	Constructor.
CoverTree(Relation<O> relation, Distance<? super O> distance, double expansion, int truncate)	Constructor.
CoverTree(Relation<O> relation, Distance<? super O> distance, int truncate)	Constructor.
Factory(Distance<? super O> distance, double expansion, int truncate)	Constructor.
Factory(Distance<? super O> distance, double expansion, int truncate)	Constructor.
Factory(Distance<? super O> distance, double expansion, int truncate)	Constructor.
SimplifiedCoverTree(Relation<O> relation, Distance<? super O> distance, double expansion, int truncate)	Constructor.

Uses of Distance in elki.index.tree.metrical.mtreevariants

Fields in elki.index.tree.metrical.mtreevariants declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	MTreeSettings.distanceFunction	Holds the instance of the trees distance function.

Methods in elki.index.tree.metrical.mtreevariants that return Distance

Modifier and Type	Method	Description
Distance<? super O>	AbstractMTree.getDistance()

Uses of Distance in elki.index.tree.metrical.vptree

Fields in elki.index.tree.metrical.vptree declared as Distance

Modifier and Type	Field	Description
(package private) Distance<? super O>	GNAT.Factory.distance	Distance Function
protected Distance<? super O>	GNAT.Factory.Par.distance	Distance function
(package private) Distance<? super O>	VPTree.Factory.distance	Distance Function
protected Distance<? super O>	VPTree.Factory.Par.distance	Distance function
(package private) Distance<? super O>	GNAT.distFunc	Distance Function to use
(package private) Distance<? super O>	VPTree.distFunc	Distance Function to use

Constructors in elki.index.tree.metrical.vptree with parameters of type Distance

Constructor	Description
Factory(Distance<? super O> distFunc, RandomFactory random, int numberVantagePoints)	Constructor.
Factory(Distance<? super O> distFunc, RandomFactory random, int sampleSize, int truncate)	Constructor.
GNAT(Relation<O> relation, Distance<? super O> distance, RandomFactory random, int numberVPs)	Constructor.
VPTree(Relation<O> relation, Distance<? super O> distance, int leafsize)	Constructor with default values, used by EmpiricalQueryOptimizer
VPTree(Relation<O> relation, Distance<? super O> distance, RandomFactory random, int sampleSize, int truncate)	Constructor.

Uses of Distance in elki.outlier

Fields in elki.outlier declared as Distance

Modifier and Type	Field	Description
protected Distance<? super V>	COP.distance	Distance function used.
protected Distance<? super V>	COP.Par.distance	The distance function to use.
protected Distance<? super O>	DWOF.distance	Distance function used.
protected Distance<? super O>	DWOF.Par.distance	The distance function to use.
protected Distance<? super O>	OPTICSOF.distance	Distance function used.
protected Distance<? super O>	OPTICSOF.Par.distance	The distance function to use.
protected Distance<? super V>	SimpleCOP.distance	Distance function used.
protected Distance<? super V>	SimpleCOP.Par.distance	The distance function to use.

Constructors in elki.outlier with parameters of type Distance

Constructor	Description
COP(Distance<? super V> distance, int k, PCARunner pca, double expect, COP.DistanceDist dist, boolean models)	Constructor.
DWOF(Distance<? super O> distance, int k, double delta)	Constructor.
OPTICSOF(Distance<? super O> distance, int minpts)	Constructor with parameters.
SimpleCOP(Distance<? super V> distance, int k, PCARunner pca, EigenPairFilter filter)	Constructor.

Uses of Distance in elki.outlier.clustering

Fields in elki.outlier.clustering declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	SilhouetteOutlierDetection.distance	Distance function used.
protected Distance<? super O>	SilhouetteOutlierDetection.Par.distance	The distance function to use.

Constructors in elki.outlier.clustering with parameters of type Distance

Constructor	Description
SilhouetteOutlierDetection(Distance<? super O> distance, ClusteringAlgorithm<?> clusterer, NoiseHandling noiseOption)	Constructor.

Uses of Distance in elki.outlier.distance

Fields in elki.outlier.distance declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	AbstractDBOutlier.distance	Distance function used.
protected Distance<? super O>	AbstractDBOutlier.Par.distance	The distance function to use.
private Distance<? super O>	HilOut.distance	Distance function used.
protected Distance<? super O>	KNNDD.distance	Distance function used.
protected Distance<? super O>	KNNDD.Par.distance	The distance function to use.
protected Distance<? super O>	KNNOutlier.distance	Distance function used.
protected Distance<? super O>	KNNOutlier.Par.distance	The distance function to use.
protected Distance<? super O>	KNNSOS.distance	Distance function used.
protected Distance<? super O>	KNNSOS.Par.distance	The distance function to use.
protected Distance<? super O>	KNNWeightOutlier.distance	Distance function used.
protected Distance<? super O>	KNNWeightOutlier.Par.distance	The distance function to use.
protected Distance<? super O>	LocalIsolationCoefficient.distance	Distance function used.
protected Distance<? super O>	LocalIsolationCoefficient.Par.distance	The distance function to use.
protected Distance<? super O>	ODIN.distance	Distance function used.
protected Distance<? super O>	ODIN.Par.distance	The distance function to use.
protected Distance<? super O>	SOS.distance	Distance function used.
protected Distance<? super O>	SOS.Par.distance	The distance function to use.

Constructors in elki.outlier.distance with parameters of type Distance

Constructor	Description
AbstractDBOutlier(Distance<? super O> distance, double d)	Constructor with actual parameters.
DBOutlierDetection(Distance<? super O> distance, double d, double p)	Constructor with actual parameters.
DBOutlierScore(Distance<? super O> distance, double d)	Constructor with parameters.
KNNDD(Distance<? super O> distance, int k)	Constructor for a single kNN query.
KNNOutlier(Distance<? super O> distance, int k)	Constructor for a single kNN query.
KNNSOS(Distance<? super O> distance, int k)	Constructor.
KNNWeightOutlier(Distance<? super O> distance, int k)	Constructor with parameters.
LocalIsolationCoefficient(Distance<? super O> distance, int k)	Constructor with parameters.
ODIN(Distance<? super O> distance, int k)	Constructor.
SOS(Distance<? super O> distance, double h)	Constructor.

Uses of Distance in elki.outlier.distance.parallel

Fields in elki.outlier.distance.parallel declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	ParallelKNNOutlier.distance	Distance function used.
protected Distance<? super O>	ParallelKNNOutlier.Par.distance	The distance function to use.
protected Distance<? super O>	ParallelKNNWeightOutlier.distance	Distance function used.
protected Distance<? super O>	ParallelKNNWeightOutlier.Par.distance	The distance function to use.

Constructors in elki.outlier.distance.parallel with parameters of type Distance

Constructor	Description
ParallelKNNOutlier(Distance<? super O> distance, int k)	Constructor.
ParallelKNNWeightOutlier(Distance<? super O> distance, int k)	Constructor.

Uses of Distance in elki.outlier.intrinsic

Fields in elki.outlier.intrinsic declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	IDOS.distance	Distance function used.
protected Distance<? super O>	IDOS.Par.distance	The distance function to use.
protected Distance<? super O>	ISOS.distance	Distance function used.
protected Distance<? super O>	ISOS.Par.distance	The distance function to use.
protected Distance<? super O>	LID.distance	Distance function used.
protected Distance<? super O>	LID.Par.distance	The distance function to use.

Constructors in elki.outlier.intrinsic with parameters of type Distance

Constructor	Description
IDOS(Distance<? super O> distance, IntrinsicDimensionalityEstimator<? super O> estimator, int kc, int kr)	Constructor.
ISOS(Distance<? super O> distance, int k, DistanceBasedIntrinsicDimensionalityEstimator estimator)	Constructor.
LID(Distance<? super O> distance, int k, IntrinsicDimensionalityEstimator<? super O> estimator)	Constructor.

Uses of Distance in elki.outlier.lof

Fields in elki.outlier.lof declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	LoOP.comparisonDistance	Distance function for comparison set.
protected Distance<O>	LoOP.Par.comparisonDistance	Preprocessor Step 2.
protected Distance<? super O>	COF.distance	Distance function used.
protected Distance<? super O>	COF.Par.distance	The distance function to use.
protected Distance<? super O>	FlexibleLOF.Par.distance	The distance function to use.
private Distance<? super O>	INFLO.distance	Distance function used.
protected Distance<? super O>	INFLO.Par.distance	The distance function to use.
protected Distance<? super O>	KDEOS.distance	Distance function used.
protected Distance<? super O>	KDEOS.Par.distance	The distance function to use.
protected Distance<? super O>	LDF.distance	Distance function used.
protected Distance<? super O>	LDF.Par.distance	The distance function to use.
protected Distance<? super O>	LDOF.distance	Distance function used.
protected Distance<? super O>	LDOF.Par.distance	The distance function to use.
private Distance<? super O>	LOCI.distance	Distance function used.
protected Distance<? super O>	LOCI.Par.distance	The distance function to use.
protected Distance<? super O>	LOF.distance	Distance function used.
protected Distance<? super O>	LOF.Par.distance	The distance function to use.
protected Distance<? super O>	SimpleKernelDensityLOF.distance	Distance function used.
protected Distance<? super O>	SimpleKernelDensityLOF.Par.distance	The distance function to use.
protected Distance<? super O>	SimplifiedLOF.distance	Distance function used.
protected Distance<? super O>	SimplifiedLOF.Par.distance	The distance function to use.
protected Distance<? super O>	VarianceOfVolume.distance	Distance function used.
protected Distance<? super O>	VarianceOfVolume.Par.distance	The distance function to use.
protected Distance<? super O>	FlexibleLOF.Par.reachabilityDistance	Reachability distance function.
protected Distance<? super O>	FlexibleLOF.reachabilityDistance	Reachability distance function.
protected Distance<O>	LoOP.Par.reachabilityDistance	Preprocessor Step 1.
protected Distance<? super O>	LoOP.reachabilityDistance	Distance function for reachability.
protected Distance<? super O>	FlexibleLOF.referenceDistance	Neighborhood distance function.

Constructors in elki.outlier.lof with parameters of type Distance

Constructor	Description
COF(Distance<? super O> distance, int k)	Constructor.
FlexibleLOF(int krefer, int kreach, Distance<? super O> neighborhoodDistance, Distance<? super O> reachabilityDistance)	Constructor.
INFLO(Distance<? super O> distance, double m, int k)	Constructor with parameters.
KDEOS(Distance<? super O> distance, int kmin, int kmax, KernelDensityFunction kernel, double minBandwidth, double scale, int idim)	Constructor.
LDF(int k, Distance<? super O> distance, KernelDensityFunction kernel, double h, double c)	Constructor.
LDOF(Distance<? super O> distance, int k)	Constructor.
LOCI(Distance<? super O> distance, double rmax, int nmin, double alpha)	Constructor.
LOF(int k, Distance<? super O> distance)	Constructor.
LoOP(int kreach, int kcomp, Distance<? super O> reachabilityDistance, Distance<? super O> comparisonDistance, double lambda)	Constructor with parameters.
OnlineLOF(int krefer, int kreach, Distance<? super O> neighborhoodDistance, Distance<? super O> reachabilityDistance)	Constructor.
SimpleKernelDensityLOF(int k, Distance<? super O> distance, KernelDensityFunction kernel)	Constructor.
SimplifiedLOF(Distance<? super O> distance, int k)	Constructor.
VarianceOfVolume(int k, Distance<? super O> distance)	Constructor.

Uses of Distance in elki.outlier.lof.parallel

Fields in elki.outlier.lof.parallel declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	ParallelLOF.distance	Distance function used.
protected Distance<? super O>	ParallelLOF.Par.distance	The distance function to use.
protected Distance<? super O>	ParallelSimplifiedLOF.distance	Distance function used.
protected Distance<? super O>	ParallelSimplifiedLOF.Par.distance	The distance function to use.

Constructors in elki.outlier.lof.parallel with parameters of type Distance

Constructor	Description
ParallelLOF(Distance<? super O> distance, int k)	Constructor.
ParallelSimplifiedLOF(Distance<? super O> distance, int k)	Constructor.

Uses of Distance in elki.outlier.spatial

Fields in elki.outlier.spatial declared as Distance

Modifier and Type	Field	Description
protected Distance<? super V>	CTLuGLSBackwardSearchAlgorithm.distance	Distance function used.
protected Distance<? super V>	CTLuGLSBackwardSearchAlgorithm.Par.distance	The distance function to use.
private Distance<? super O>	CTLuRandomWalkEC.distance	Distance function used.
protected Distance<? super O>	CTLuRandomWalkEC.Par.distance	The distance function to use.
private Distance<O>	AbstractDistanceBasedSpatialOutlier.nonSpatialDistance	The distance function to use

Methods in elki.outlier.spatial that return Distance

Modifier and Type	Method	Description
protected Distance<O>	AbstractDistanceBasedSpatialOutlier.getNonSpatialDistance()	Get the non-spatial relation

Constructors in elki.outlier.spatial with parameters of type Distance

Constructor	Description
AbstractDistanceBasedSpatialOutlier(NeighborSetPredicate.Factory<N> npredf, Distance<O> nonSpatialDistance)	Constructor.
CTLuGLSBackwardSearchAlgorithm(Distance<? super V> distance, int k, double alpha)	Constructor.
CTLuRandomWalkEC(Distance<? super O> distance, double alpha, double c, int k)	Constructor.

Uses of Distance in elki.outlier.spatial.neighborhood

Fields in elki.outlier.spatial.neighborhood declared as Distance

Modifier and Type	Field	Description
private Distance<? super O>	PrecomputedKNearestNeighborNeighborhood.Factory.distance	distance function to use
(package private) Distance<? super O>	PrecomputedKNearestNeighborNeighborhood.Factory.Par.distFunc	Distance function

Constructors in elki.outlier.spatial.neighborhood with parameters of type Distance

Constructor	Description
Factory(int k, Distance<? super O> distance)	Factory Constructor

Uses of Distance in elki.projection

Fields in elki.projection declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	GaussianAffinityMatrixBuilder.distance	Input distance function.
protected Distance<? super O>	GaussianAffinityMatrixBuilder.Par.distance	The distance function to use.
protected Distance<? super O>	PerplexityAffinityMatrixBuilder.distance	Input distance function.
protected Distance<? super O>	PerplexityAffinityMatrixBuilder.Par.distance	The distance function to use.

Constructors in elki.projection with parameters of type Distance

Constructor	Description
GaussianAffinityMatrixBuilder(Distance<? super O> distance, double sigma)	Constructor.
IntrinsicNearestNeighborAffinityMatrixBuilder(Distance<? super O> distance, double perplexity, DistanceBasedIntrinsicDimensionalityEstimator estimator)	Constructor.
NearestNeighborAffinityMatrixBuilder(Distance<? super O> distance, double perplexity)	Constructor.
NearestNeighborAffinityMatrixBuilder(Distance<? super O> distance, double perplexity, int neighbors)	Constructor.
PerplexityAffinityMatrixBuilder(Distance<? super O> distance, double perplexity)	Constructor.

Uses of Distance in elki.similarity

Classes in elki.similarity that implement Distance

Modifier and Type	Class	Description
class	Kulczynski1Similarity	Kulczynski similarity 1.

Uses of Distance in elki.similarity.cluster

Subinterfaces of Distance in elki.similarity.cluster

Modifier and Type	Interface	Description
interface	ClusteringDistanceSimilarity	Distance and similarity measure for clusterings.

Classes in elki.similarity.cluster that implement Distance

Modifier and Type	Class	Description
class	ClusteringAdjustedRandIndexSimilarity	Measure the similarity of clusters via the Adjusted Rand Index.
class	ClusteringBCubedF1Similarity	Measure the similarity of clusters via the BCubed F1 Index.
class	ClusteringFowlkesMallowsSimilarity	Measure the similarity of clusters via the Fowlkes-Mallows Index.
class	ClusteringRandIndexSimilarity	Measure the similarity of clusters via the Rand Index.
class	ClusterIntersectionSimilarity	Measure the similarity of clusters via the intersection size.
class	ClusterJaccardSimilarity	Measure the similarity of clusters via the Jaccard coefficient.

Uses of Distance in elki.similarity.kernel

Classes in elki.similarity.kernel that implement Distance

Modifier and Type	Class	Description
class	LinearKernel	Linear Kernel function that computes a similarity between the two feature vectors x and y defined by \(x^T\cdot y\).
class	PolynomialKernel	Polynomial Kernel function that computes a similarity between the two feature vectors x and y defined by \((x^T\cdot y+b)^{\text{degree}}\).

Uses of Distance in tutorial.clustering

Fields in tutorial.clustering declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	CFSFDP.distance	Distance function used.
protected Distance<? super O>	CFSFDP.Par.distance	The distance function to use.
(package private) Distance<? super O>	NaiveAgglomerativeHierarchicalClustering1.distance	Distance function used.
protected Distance<? super O>	NaiveAgglomerativeHierarchicalClustering1.Par.distance	The distance function to use.
(package private) Distance<? super O>	NaiveAgglomerativeHierarchicalClustering2.distance	Distance function used.
protected Distance<? super O>	NaiveAgglomerativeHierarchicalClustering2.Par.distance	The distance function to use.
(package private) Distance<? super O>	NaiveAgglomerativeHierarchicalClustering3.distance	Distance function used.
protected Distance<? super O>	NaiveAgglomerativeHierarchicalClustering3.Par.distance	The distance function to use.
(package private) Distance<? super O>	NaiveAgglomerativeHierarchicalClustering4.distance	Distance function used.
protected Distance<? super O>	NaiveAgglomerativeHierarchicalClustering4.Par.distance	The distance function to use.

Constructors in tutorial.clustering with parameters of type Distance

Constructor	Description
CFSFDP(Distance<? super O> distance, double dc, int k)	Constructor.
NaiveAgglomerativeHierarchicalClustering1(Distance<? super O> distance, int numclusters)	Constructor.
NaiveAgglomerativeHierarchicalClustering2(Distance<? super O> distance, int numclusters)	Constructor.
NaiveAgglomerativeHierarchicalClustering3(Distance<? super O> distance, int numclusters, NaiveAgglomerativeHierarchicalClustering3.Linkage linkage)	Constructor.
NaiveAgglomerativeHierarchicalClustering4(Distance<? super O> distance, NaiveAgglomerativeHierarchicalClustering4.Linkage linkage)	Constructor.

Uses of Distance in tutorial.distancefunction

Classes in tutorial.distancefunction that implement Distance

Modifier and Type	Class	Description
class	MultiLPNorm	Tutorial example Minowski-distance variation with different exponents for different dimensions for ELKI.
class	TutorialDistance	Tutorial distance function example for ELKI.

Uses of Distance in tutorial.outlier

Fields in tutorial.outlier declared as Distance

Modifier and Type	Field	Description
protected Distance<? super O>	DistanceStddevOutlier.distance	Distance function used.
protected Distance<? super O>	DistanceStddevOutlier.Par.distance	The distance function to use.
(package private) Distance<? super O>	ODIN.distance	Distance function used.
protected Distance<? super O>	ODIN.Par.distance	The distance function to use.

Constructors in tutorial.outlier with parameters of type Distance

Constructor	Description
DistanceStddevOutlier(Distance<? super O> distance, int k)	Constructor.
ODIN(Distance<? super O> distance, int k)	Constructor.