Uses of Interface
de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction

Packages that use DistanceFunction

de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial	Spatial outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood	Spatial outlier neighborhood classes
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)
de.lmu.ifi.dbs.elki.application.cache	Utility applications for the persistence layer such as distance cache builders.
de.lmu.ifi.dbs.elki.application.visualization	Visualization applications in ELKI.
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.query.distance	Prepared queries for distances.
de.lmu.ifi.dbs.elki.datasource.parser	Parsers for different file formats and data types.
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.adapter	Distance functions deriving distances from e.g. similarity measures
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram	Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation	Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.external	Distance functions using external data sources.
de.lmu.ifi.dbs.elki.distance.distancefunction.geo	Geographic (earth) distance functions.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries	Distance functions designed for time series.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Kernel functions.
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix	Render a distance matrix to visualize a clustering-distance-combination.
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.localpca	Index using a preprocessed local PCA.
de.lmu.ifi.dbs.elki.index.preprocessed.snn	Indexes providing nearest neighbor sets
de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj	Index using a preprocessed local subspaces.
de.lmu.ifi.dbs.elki.index.tree.metrical	Tree-based index structures for metrical vector spaces.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants	M-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees	Metrical index structures based on the concepts of the M-Tree supporting processing of reverse k nearest neighbor queries by using the k-nn distances of the entries.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp	MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop	MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax	MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab	MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree	MTree
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters	Classes for various typed parameters.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.algorithm

Fields in de.lmu.ifi.dbs.elki.algorithm declared as DistanceFunction

private DistanceFunction<? super O,D>	AbstractDistanceBasedAlgorithm.distanceFunction Holds the instance of the distance function specified by AbstractDistanceBasedAlgorithm.DISTANCE_FUNCTION_ID.
protected DistanceFunction<O,D>	AbstractDistanceBasedAlgorithm.Parameterizer.distanceFunction

Methods in de.lmu.ifi.dbs.elki.algorithm with type parameters of type DistanceFunction

static <F extends DistanceFunction<?,?>> ObjectParameter<F>

AbstractAlgorithm.makeParameterDistanceFunction(Class<?> defaultDistanceFunction, Class<?> restriction) Make a default distance function configuration option

Methods in de.lmu.ifi.dbs.elki.algorithm that return DistanceFunction

DistanceFunction<? super O,D>

AbstractDistanceBasedAlgorithm.getDistanceFunction() Returns the distanceFunction.

Constructors in de.lmu.ifi.dbs.elki.algorithm with parameters of type DistanceFunction

AbstractDistanceBasedAlgorithm(DistanceFunction<? super O,D> distanceFunction)
Constructor.

KNNDistanceOrder(DistanceFunction<O,D> distanceFunction, int k, double percentage)
Constructor.

KNNJoin(DistanceFunction<? super V,D> distanceFunction, int k)
Constructor.

MaterializeDistances(DistanceFunction<? super O,D> distanceFunction)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.algorithm.clustering

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering declared as DistanceFunction

private DistanceFunction<? super V,DoubleDistance>	AbstractProjectedClustering.distanceFunction The euclidean distance function.
protected DistanceFunction<V,D>	AbstractProjectedDBSCAN.Parameterizer.innerdist

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering that return DistanceFunction

protected DistanceFunction<? super V,DoubleDistance>

AbstractProjectedClustering.getDistanceFunction() Returns the distance function.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type DistanceFunction

protected void	AbstractProjectedDBSCAN.Parameterizer.configEpsilon(Parameterization config, DistanceFunction<V,D> innerdist)
protected void	AbstractProjectedDBSCAN.Parameterizer.configOuterDistance(Parameterization config, D epsilon, int minpts, Class<?> preprocessorClass, DistanceFunction<V,D> innerdist)

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type DistanceFunction

DBSCAN(DistanceFunction<? super O,D> distanceFunction, D epsilon, int minpts)
Constructor with parameters.

DeLiClu(DistanceFunction<? super NV,D> distanceFunction, int minpts)
Constructor.

OPTICS(DistanceFunction<? super O,D> distanceFunction, D epsilon, int minpts)
Constructor.

SLINK(DistanceFunction<? super O,D> distanceFunction, Integer minclusters)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.algorithm.outlier

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier declared as DistanceFunction

protected DistanceFunction<? super O,D>	LoOP.comparisonDistanceFunction Preprocessor Step 2
protected DistanceFunction<O,D>	LoOP.Parameterizer.comparisonDistanceFunction Preprocessor Step 2
private DistanceFunction<V,D>	ReferenceBasedOutlierDetection.distanceFunction Distance function to use.
protected DistanceFunction<O,D>	OnlineLOF.Parameterizer.neighborhoodDistanceFunction Neighborhood distance function.
protected DistanceFunction<? super O,D>	LOF.neighborhoodDistanceFunction Neighborhood distance function.
protected DistanceFunction<O,D>	LOF.Parameterizer.neighborhoodDistanceFunction Neighborhood distance function.
protected DistanceFunction<O,D>	OnlineLOF.Parameterizer.reachabilityDistanceFunction Reachability distance function.
protected DistanceFunction<? super O,D>	LoOP.reachabilityDistanceFunction Preprocessor Step 1
protected DistanceFunction<O,D>	LoOP.Parameterizer.reachabilityDistanceFunction Preprocessor Step 1
protected DistanceFunction<? super O,D>	LOF.reachabilityDistanceFunction Reachability distance function.
protected DistanceFunction<O,D>	LOF.Parameterizer.reachabilityDistanceFunction Reachability distance function.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier with parameters of type DistanceFunction

protected void

AbstractDBOutlier.Parameterizer.configD(Parameterization config, DistanceFunction<?,D> distanceFunction) Grab the 'd' configuration option.

Constructors in de.lmu.ifi.dbs.elki.algorithm.outlier with parameters of type DistanceFunction

ABOD(int k, int sampleSize, PrimitiveSimilarityFunction<? super V,DoubleDistance> primitiveKernelFunction, DistanceFunction<V,DoubleDistance> distanceFunction)
Actual constructor, with parameters.

ABOD(int k, PrimitiveSimilarityFunction<? super V,DoubleDistance> primitiveKernelFunction, DistanceFunction<V,DoubleDistance> distanceFunction)
Actual constructor, with parameters.

AbstractDBOutlier(DistanceFunction<? super O,D> distanceFunction, D d)
Constructor with actual parameters.

DBOutlierDetection(DistanceFunction<O,D> distanceFunction, D d, double p)
Constructor with actual parameters.

DBOutlierScore(DistanceFunction<O,D> distanceFunction, D d)
Constructor with parameters.

INFLO(DistanceFunction<? super O,D> distanceFunction, double m, int k)
Constructor with parameters.

KNNOutlier(DistanceFunction<? super O,D> distanceFunction, int k)
Constructor for a single kNN query.

KNNWeightOutlier(DistanceFunction<? super O,D> distanceFunction, int k)
Constructor with parameters.

LDOF(DistanceFunction<? super O,D> distanceFunction, int k)
Constructor.

LOCI(DistanceFunction<? super O,D> distanceFunction, D rmax, int nmin, double alpha)
Constructor.

LOF(int k, DistanceFunction<? super O,D> neighborhoodDistanceFunction, DistanceFunction<? super O,D> reachabilityDistanceFunction)
Constructor.

LOF(int k, DistanceFunction<? super O,D> neighborhoodDistanceFunction, DistanceFunction<? super O,D> reachabilityDistanceFunction)
Constructor.

LoOP(int kreach, int kcomp, DistanceFunction<? super O,D> reachabilityDistanceFunction, DistanceFunction<? super O,D> comparisonDistanceFunction, double lambda)
Constructor with parameters.

LoOP(int kreach, int kcomp, DistanceFunction<? super O,D> reachabilityDistanceFunction, DistanceFunction<? super O,D> comparisonDistanceFunction, double lambda)
Constructor with parameters.

OnlineLOF(int k, DistanceFunction<? super O,D> neighborhoodDistanceFunction, DistanceFunction<? super O,D> reachabilityDistanceFunction)
Constructor.

OnlineLOF(int k, DistanceFunction<? super O,D> neighborhoodDistanceFunction, DistanceFunction<? super O,D> reachabilityDistanceFunction)
Constructor.

OPTICSOF(DistanceFunction<? super O,D> distanceFunction, int minpts)
Constructor with parameters.

ReferenceBasedOutlierDetection(int k, DistanceFunction<V,D> distanceFunction, ReferencePointsHeuristic<V> refp)
Constructor with parameters.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial declared as DistanceFunction

private DistanceFunction<O,D>

AbstractDistanceBasedSpatialOutlier.nonSpatialDistanceFunction The distance function to use

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial that return DistanceFunction

protected DistanceFunction<O,D>

AbstractDistanceBasedSpatialOutlier.getNonSpatialDistanceFunction() Get the non-spatial relation

Constructors in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial with parameters of type DistanceFunction

AbstractDistanceBasedSpatialOutlier(NeighborSetPredicate.Factory<N> npredf, DistanceFunction<O,D> nonSpatialDistanceFunction)
Constructor.

CTLuGLSBackwardSearchAlgorithm(DistanceFunction<V,D> distanceFunction, int k, double alpha)
Constructor.

CTLuRandomWalkEC(DistanceFunction<N,D> distanceFunction, double alpha, double c, int k)
Constructor

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood declared as DistanceFunction

private DistanceFunction<? super O,D>	PrecomputedKNearestNeighborNeighborhood.Factory.distFunc distance function to use
(package private) DistanceFunction<? super O,D>	PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer.distFunc Distance function

Constructors in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood with parameters of type DistanceFunction

PrecomputedKNearestNeighborNeighborhood.Factory(int k, DistanceFunction<? super O,D> distFunc)
Factory Constructor

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.algorithm.statistics

Constructors in de.lmu.ifi.dbs.elki.algorithm.statistics with parameters of type DistanceFunction

DistanceStatisticsWithClasses(DistanceFunction<? super O,D> distanceFunction, int numbins, boolean exact, boolean sampling)
Constructor.

EvaluateRankingQuality(DistanceFunction<? super V,D> distanceFunction, int numbins)
Constructor.

RankingQualityHistogram(DistanceFunction<? super O,D> distanceFunction, int numbins)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.application.cache

Fields in de.lmu.ifi.dbs.elki.application.cache declared as DistanceFunction

private DistanceFunction<O,D>	CacheFloatDistanceInOnDiskMatrix.distance Distance function that is to be cached.
private DistanceFunction<O,D>	CacheFloatDistanceInOnDiskMatrix.Parameterizer.distance Distance function that is to be cached.
private DistanceFunction<O,D>	CacheDoubleDistanceInOnDiskMatrix.distance Distance function that is to be cached.
private DistanceFunction<O,D>	CacheDoubleDistanceInOnDiskMatrix.Parameterizer.distance Distance function that is to be cached.

Constructors in de.lmu.ifi.dbs.elki.application.cache with parameters of type DistanceFunction

CacheDoubleDistanceInOnDiskMatrix(boolean verbose, Database database, DistanceFunction<O,D> distance, File out)
Constructor.

CacheFloatDistanceInOnDiskMatrix(boolean verbose, Database database, DistanceFunction<O,D> distance, File out)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.application.visualization

Fields in de.lmu.ifi.dbs.elki.application.visualization declared as DistanceFunction

private DistanceFunction<O,D>	KNNExplorer.distanceFunction Holds the instance of the distance function specified by KNNExplorer.DISTANCE_FUNCTION_ID.
protected DistanceFunction<O,D>	KNNExplorer.Parameterizer.distanceFunction

Constructors in de.lmu.ifi.dbs.elki.application.visualization with parameters of type DistanceFunction

KNNExplorer(boolean verbose, Database database, DistanceFunction<O,D> distanceFunction)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.database

Methods in de.lmu.ifi.dbs.elki.database with parameters of type DistanceFunction

static <O,D extends Distance<D>> DistanceQuery<O,D>	QueryUtil.getDistanceQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a distance query for a given distance function, automatically choosing a relation.
<O,D extends Distance<D>> DistanceQuery<O,D>	AbstractDatabase.getDistanceQuery(Relation<O> objQuery, DistanceFunction<? super O,D> distanceFunction, Object... hints)
<O,D extends Distance<D>> DistanceQuery<O,D>	Database.getDistanceQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get the distance query for a particular distance function.
static <O,D extends Distance<D>> KNNQuery<O,D>	QueryUtil.getKNNQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a KNN query object for the given distance function.
static <O,D extends Distance<D>> KNNQuery<O,D>	QueryUtil.getKNNQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a KNN query object for the given distance function.
static <O,D extends Distance<D>> RangeQuery<O,D>	QueryUtil.getRangeQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a range query object for the given distance function.
static <O,D extends Distance<D>> RangeQuery<O,D>	QueryUtil.getRangeQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a range query object for the given distance function.
static <O,D extends Distance<D>> RKNNQuery<O,D>	QueryUtil.getRKNNQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a rKNN query object for the given distance function.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.database.query.distance

Methods in de.lmu.ifi.dbs.elki.database.query.distance that return DistanceFunction

DistanceFunction<? super O,D>

DistanceQuery.getDistanceFunction() Get the inner distance function.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.datasource.parser

Fields in de.lmu.ifi.dbs.elki.datasource.parser declared as DistanceFunction

private DistanceFunction<?,D>	NumberDistanceParser.distanceFunction The distance function.
protected DistanceFunction<?,D>	NumberDistanceParser.Parameterizer.distanceFunction The distance function.

Constructors in de.lmu.ifi.dbs.elki.datasource.parser with parameters of type DistanceFunction

NumberDistanceParser(Pattern colSep, char quoteChar, DistanceFunction<?,D> distanceFunction)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction with type parameters of type DistanceFunction

static class

AbstractIndexBasedDistanceFunction.Instance<O,I extends Index,D extends Distance<D>,F extends DistanceFunction<? super O,D>> The actual instance bound to a particular database.

Subinterfaces of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction

interface	DBIDDistanceFunction<D extends Distance<?>> Distance functions valid in a database context only (i.e. for DBIDs) For any "distance" that cannot be computed for arbitrary objects, only those that exist in the database and referenced by their ID.
interface	FilteredLocalPCABasedDistanceFunction<O extends NumberVector<?,?>,P extends FilteredLocalPCAIndex<? super O>,D extends Distance<D>> Interface for local PCA based preprocessors.
interface	IndexBasedDistanceFunction<O,D extends Distance<D>> Distance function relying on an index (such as preprocessed neighborhoods).
interface	PrimitiveDistanceFunction<O,D extends Distance<?>> Primitive distance function that is defined on some kind of object.
interface	PrimitiveDoubleDistanceFunction<O> Interface for distance functions that can provide a raw double value.
interface	SpatialPrimitiveDistanceFunction<V extends SpatialComparable,D extends Distance<D>> API for a spatial primitive distance function.
interface	SpatialPrimitiveDoubleDistanceFunction<V extends SpatialComparable> Interface combining spatial primitive distance functions with primitive number distance functions.

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction that implement DistanceFunction

class	AbstractCosineDistanceFunction Abstract base class for Cosine and ArcCosine distances.
class	AbstractDatabaseDistanceFunction<O,D extends Distance<D>> Abstract super class for distance functions needing a database context.
class	AbstractDBIDDistanceFunction<D extends Distance<D>> AbstractDistanceFunction provides some methods valid for any extending class.
class	AbstractIndexBasedDistanceFunction<O,I extends Index,D extends Distance<D>> Abstract super class for distance functions needing a database index.
class	AbstractPrimitiveDistanceFunction<O,D extends Distance<D>> AbstractDistanceFunction provides some methods valid for any extending class.
class	AbstractVectorDoubleDistanceFunction Abstract base class for the most common family of distance functions: defined on number vectors and returning double values.
class	ArcCosineDistanceFunction Cosine distance function for feature vectors.
class	CosineDistanceFunction Cosine distance function for feature vectors.
class	EuclideanDistanceFunction Provides the Euclidean distance for FeatureVectors.
class	LocallyWeightedDistanceFunction<V extends NumberVector<?,?>> Provides a locally weighted distance function.
class	LPNormDistanceFunction Provides a LP-Norm for FeatureVectors.
class	ManhattanDistanceFunction Manhattan distance function to compute the Manhattan distance for a pair of FeatureVectors.
class	MaximumDistanceFunction Maximum distance function to compute the Maximum distance for a pair of FeatureVectors.
class	MinimumDistanceFunction Maximum distance function to compute the Minimum distance for a pair of FeatureVectors.
class	MinKDistance<O,D extends Distance<D>> A distance that is at least the distance to the kth nearest neighbor.
class	ProxyDistanceFunction<O,D extends Distance<D>> Distance function to proxy computations to another distance (that probably was run before).
class	RandomStableDistanceFunction 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	SharedNearestNeighborJaccardDistanceFunction<O> SharedNearestNeighborJaccardDistanceFunction computes the Jaccard coefficient, which is a proper distance metric.
class	SquaredEuclideanDistanceFunction Provides the squared Euclidean distance for FeatureVectors.
class	WeightedDistanceFunction Provides the Weighted distance for feature vectors.
class	WeightedLPNormDistanceFunction Weighted version of the Euclidean distance function.
class	WeightedSquaredEuclideanDistanceFunction Provides the squared Euclidean distance for FeatureVectors.

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction declared as DistanceFunction

(package private) DistanceFunction<? super O,D>	AbstractDatabaseDistanceFunction.Instance.parent Parent distance
protected F	AbstractIndexBasedDistanceFunction.Instance.parent Our parent distance function
protected DistanceFunction<? super O,D>	MinKDistance.parentDistance The distance function to determine the exact distance.
protected DistanceFunction<? super O,D>	MinKDistance.Parameterizer.parentDistance The distance function to determine the exact distance.

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction that return DistanceFunction

DistanceFunction<? super O,D>	AbstractDatabaseDistanceFunction.Instance.getDistanceFunction()
DistanceFunction<? super T,D>	MinKDistance.Instance.getDistanceFunction()
static <V,T extends V,D extends Distance<D>> DistanceFunction<? super V,D>	ProxyDistanceFunction.unwrapDistance(DistanceFunction<V,D> dfun) Helper function, to resolve any wrapped Proxy Distances

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction with parameters of type DistanceFunction

static <V,T extends V,D extends Distance<D>> DistanceFunction<? super V,D>

ProxyDistanceFunction.unwrapDistance(DistanceFunction<V,D> dfun) Helper function, to resolve any wrapped Proxy Distances

Constructors in de.lmu.ifi.dbs.elki.distance.distancefunction with parameters of type DistanceFunction

AbstractDatabaseDistanceFunction.Instance(Relation<O> database, DistanceFunction<? super O,D> parent)
Constructor.

MinKDistance.Instance(Relation<T> relation, int k, DistanceFunction<? super O,D> parentDistance)
Constructor.

MinKDistance(DistanceFunction<? super O,D> parentDistance, int k)
Full constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter that implement DistanceFunction

class	AbstractSimilarityAdapter<O> Adapter from a normalized similarity function to a distance function.
class	SimilarityAdapterArccos<O> Adapter from a normalized similarity function to a distance function using arccos(sim).
class	SimilarityAdapterLinear<O> Adapter from a normalized similarity function to a distance function using 1 - sim.
class	SimilarityAdapterLn<O> Adapter from a normalized similarity function to a distance function using -log(sim).

Constructors in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter with parameters of type DistanceFunction

AbstractSimilarityAdapter.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<? super O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

SimilarityAdapterArccos.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

SimilarityAdapterLinear.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<? super O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

SimilarityAdapterLn.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram that implement DistanceFunction

class	HistogramIntersectionDistanceFunction Intersection distance for color histograms.
class	HSBHistogramQuadraticDistanceFunction Distance function for HSB color histograms based on a quadratic form and color similarity.
class	RGBHistogramQuadraticDistanceFunction Distance function for RGB color histograms based on a quadratic form and color similarity.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation that implement DistanceFunction

class	ERiCDistanceFunction Provides a distance function for building the hierarchy in the ERiC algorithm.
class	PCABasedCorrelationDistanceFunction Provides the correlation distance for real valued vectors.
class	PearsonCorrelationDistanceFunction Pearson correlation distance function for feature vectors.
class	SquaredPearsonCorrelationDistanceFunction Squared Pearson correlation distance function for feature vectors.
class	WeightedPearsonCorrelationDistanceFunction Pearson correlation distance function for feature vectors.
class	WeightedSquaredPearsonCorrelationDistanceFunction Squared Pearson correlation distance function for feature vectors.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.external

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.external that implement DistanceFunction

class	DiskCacheBasedDoubleDistanceFunction Provides a DistanceFunction that is based on double distances given by a distance matrix of an external file.
class	DiskCacheBasedFloatDistanceFunction Provides a DistanceFunction that is based on float distances given by a distance matrix of an external file.
class	FileBasedDoubleDistanceFunction Provides a DistanceFunction that is based on double distances given by a distance matrix of an external file.
class	FileBasedFloatDistanceFunction Provides a DistanceFunction that is based on float distances given by a distance matrix of an external file.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.geo

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.geo that implement DistanceFunction

class	DimensionSelectingLatLngDistanceFunction Distance function for 2D vectors in Latitude, Longitude form.
class	LatLngDistanceFunction Distance function for 2D vectors in Latitude, Longitude form.
class	LngLatDistanceFunction Distance function for 2D vectors in Longitude, Latitude form.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace that implement DistanceFunction

class	AbstractDimensionsSelectingDoubleDistanceFunction<V extends FeatureVector<?,?>> Provides a distance function that computes the distance (which is a double distance) between feature vectors only in specified dimensions.
class	AbstractPreferenceVectorBasedCorrelationDistanceFunction<V extends NumberVector<?,?>,P extends PreferenceVectorIndex<V>> Abstract super class for all preference vector based correlation distance functions.
class	DimensionSelectingDistanceFunction Provides a distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension.
class	DimensionsSelectingEuclideanDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.
class	DiSHDistanceFunction Distance function used in the DiSH algorithm.
class	HiSCDistanceFunction<V extends NumberVector<?,?>> Distance function used in the HiSC algorithm.
class	SubspaceDistanceFunction Provides a distance function to determine a kind of correlation distance between two points, which is a pair consisting of the distance between the two subspaces spanned by the strong eigenvectors of the two points and the affine distance between the two subspaces.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries that implement DistanceFunction

class	AbstractEditDistanceFunction Provides the Edit Distance for FeatureVectors.
class	DTWDistanceFunction Provides the Dynamic Time Warping distance for FeatureVectors.
class	EDRDistanceFunction Provides the Edit Distance on Real Sequence distance for FeatureVectors.
class	ERPDistanceFunction Provides the Edit Distance With Real Penalty distance for FeatureVectors.
class	LCSSDistanceFunction Provides the Longest Common Subsequence distance for FeatureVectors.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Classes in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel that implement DistanceFunction

class	FooKernelFunction Provides an experimental KernelDistanceFunction for NumberVectors.
class	LinearKernelFunction<O extends NumberVector<?,?>> Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 defined by V1^T*V2.
class	PolynomialKernelFunction Provides a polynomial Kernel function that computes a similarity between the two feature vectors V1 and V2 defined by (V1^T*V2)^degree.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix

Fields in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix declared as DistanceFunction

private DistanceFunction<? super O,? extends NumberDistance<?,?>>	ComputeSimilarityMatrixImage.distanceFunction The distance function to use
private DistanceFunction<O,? extends NumberDistance<?,?>>	ComputeSimilarityMatrixImage.Parameterizer.distanceFunction The distance function to use

Constructors in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix with parameters of type DistanceFunction

ComputeSimilarityMatrixImage(DistanceFunction<? super O,? extends NumberDistance<?,?>> distanceFunction, ScalingFunction scaling, boolean skipzero)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.preprocessed.knn

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.knn declared as DistanceFunction

protected DistanceFunction<? super O,D>	AbstractMaterializeKNNPreprocessor.distanceFunction The distance function to be used.
protected DistanceFunction<? super O,D>	AbstractMaterializeKNNPreprocessor.Factory.distanceFunction Hold the distance function to be used.
protected DistanceFunction<? super O,D>	AbstractMaterializeKNNPreprocessor.Factory.Parameterizer.distanceFunction Hold the distance function to be used.

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.knn that return DistanceFunction

DistanceFunction<? super O,D>

AbstractMaterializeKNNPreprocessor.Factory.getDistanceFunction() Get the distance function.

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.knn with parameters of type DistanceFunction

AbstractMaterializeKNNPreprocessor.Factory(int k, DistanceFunction<? super O,D> distanceFunction)
Index factory.

AbstractMaterializeKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k)
Constructor.

MaterializeKNNAndRKNNPreprocessor.Factory(int k, DistanceFunction<? super O,D> distanceFunction)
Constructor.

MaterializeKNNAndRKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k)
Constructor.

MaterializeKNNPreprocessor.Factory(int k, DistanceFunction<? super O,D> distanceFunction)
Index factory.

MaterializeKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k)
Constructor with preprocessing step.

MaterializeKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k, boolean preprocess)
Constructor.

MetricalIndexApproximationMaterializeKNNPreprocessor.Factory(int k, DistanceFunction<? super O,D> distanceFunction)
Constructor.

MetricalIndexApproximationMaterializeKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k)
Constructor

PartitionApproximationMaterializeKNNPreprocessor.Factory(int k, DistanceFunction<? super O,D> distanceFunction, int partitions)
Constructor.

PartitionApproximationMaterializeKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k, int partitions)
Constructor

SpatialApproximationMaterializeKNNPreprocessor.Factory(int k, DistanceFunction<? super NumberVector<?,?>,D> distanceFunction)
Constructor.

SpatialApproximationMaterializeKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k)
Constructor

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.localpca declared as DistanceFunction

protected DistanceFunction<NV,DoubleDistance>	AbstractFilteredPCAIndex.Factory.pcaDistanceFunction Holds the instance of the distance function specified by AbstractFilteredPCAIndex.Factory.PCA_DISTANCE_ID.
protected DistanceFunction<NV,DoubleDistance>	AbstractFilteredPCAIndex.Factory.Parameterizer.pcaDistanceFunction Holds the instance of the distance function specified by AbstractFilteredPCAIndex.Factory.PCA_DISTANCE_ID.

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.localpca with parameters of type DistanceFunction

AbstractFilteredPCAIndex.Factory(DistanceFunction<NV,DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<NV> pca)
Constructor.

KNNQueryFilteredPCAIndex.Factory(DistanceFunction<V,DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<V> pca, Integer k)
Constructor.

RangeQueryFilteredPCAIndex.Factory(DistanceFunction<V,DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<V> pca, DoubleDistance epsilon)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.preprocessed.snn

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.snn declared as DistanceFunction

protected DistanceFunction<O,D>	SharedNearestNeighborPreprocessor.distanceFunction Hold the distance function to be used.
protected DistanceFunction<O,D>	SharedNearestNeighborPreprocessor.Factory.distanceFunction Hold the distance function to be used.
protected DistanceFunction<O,D>	SharedNearestNeighborPreprocessor.Factory.Parameterizer.distanceFunction Hold the distance function to be used.

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.snn with parameters of type DistanceFunction

SharedNearestNeighborPreprocessor.Factory(int numberOfNeighbors, DistanceFunction<O,D> distanceFunction)
Constructor.

SharedNearestNeighborPreprocessor(Relation<O> relation, int numberOfNeighbors, DistanceFunction<O,D> distanceFunction)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj declared as DistanceFunction

protected DistanceFunction<NV,D>	AbstractSubspaceProjectionIndex.rangeQueryDistanceFunction The distance function for the variance analysis.
protected DistanceFunction<NV,D>	AbstractSubspaceProjectionIndex.Factory.rangeQueryDistanceFunction The distance function for the variance analysis.
protected DistanceFunction<NV,D>	AbstractSubspaceProjectionIndex.Factory.Parameterizer.rangeQueryDistanceFunction The distance function for the variance analysis.

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj with parameters of type DistanceFunction

protected void

AbstractSubspaceProjectionIndex.Factory.Parameterizer.configEpsilon(Parameterization config, DistanceFunction<NV,D> rangeQueryDistanceFunction)

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj with parameters of type DistanceFunction

AbstractSubspaceProjectionIndex.Factory(D epsilon, DistanceFunction<NV,D> rangeQueryDistanceFunction, int minpts)
Constructor.

AbstractSubspaceProjectionIndex(Relation<NV> relation, D epsilon, DistanceFunction<NV,D> rangeQueryDistanceFunction, int minpts)
Constructor.

FourCSubspaceIndex.Factory(D epsilon, DistanceFunction<V,D> rangeQueryDistanceFunction, int minpts, PCAFilteredRunner<V> pca)
Constructor.

FourCSubspaceIndex(Relation<V> relation, D epsilon, DistanceFunction<V,D> rangeQueryDistanceFunction, int minpts, PCAFilteredRunner<V> pca)
Full constructor.

PreDeConSubspaceIndex.Factory(D epsilon, DistanceFunction<V,D> rangeQueryDistanceFunction, int minpts, double delta)
Constructor.

PreDeConSubspaceIndex(Relation<V> relation, D epsilon, DistanceFunction<V,D> rangeQueryDistanceFunction, int minpts, double delta)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical that return DistanceFunction

abstract DistanceFunction<? super O,D>

MetricalIndexTree.getDistanceFunction() Returns the distance function of this metrical index.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants

Fields in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants declared as DistanceFunction

protected DistanceFunction<O,D>	AbstractMTreeFactory.distanceFunction Holds the instance of the distance function specified by AbstractMTreeFactory.DISTANCE_FUNCTION_ID.
protected DistanceFunction<O,D>	AbstractMTreeFactory.Parameterizer.distanceFunction
protected DistanceFunction<O,D>	AbstractMTree.distanceFunction Holds the instance of the trees distance function

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants that return DistanceFunction

DistanceFunction<O,D>

AbstractMTree.getDistanceFunction()

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants with parameters of type DistanceFunction

AbstractMTree(PageFile<N> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

AbstractMTreeFactory(String fileName, int pageSize, long cacheSize, DistanceFunction<O,D> distanceFunction)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees with parameters of type DistanceFunction

AbstractMkTree(PageFile<N> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

AbstractMkTreeUnified(PageFile<N> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

AbstractMkTreeUnifiedFactory(String fileName, int pageSize, long cacheSize, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp with parameters of type DistanceFunction

MkAppTree(PageFile<MkAppTreeNode<O,D>> pageFile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max, int p, boolean log)
Constructor.

MkAppTreeFactory(String fileName, int pageSize, long cacheSize, DistanceFunction<O,D> distanceFunction, int k_max, int p, boolean log)
Constructor.

MkAppTreeIndex(Relation<O> relation, PageFile<MkAppTreeNode<O,D>> pageFile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max, int p, boolean log)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with parameters of type DistanceFunction

MkCoPTree(PageFile<MkCoPTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkCopTreeFactory(String fileName, int pageSize, long cacheSize, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkCoPTreeIndex(Relation<O> relation, PageFile<MkCoPTreeNode<O,D>> pageFile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax with parameters of type DistanceFunction

MkMaxTree(PageFile<MkMaxTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkMaxTreeFactory(String fileName, int pageSize, long cacheSize, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkMaxTreeIndex(Relation<O> relation, PageFile<MkMaxTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab with parameters of type DistanceFunction

MkTabTree(PageFile<MkTabTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkTabTreeFactory(String fileName, int pageSize, long cacheSize, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkTabTreeIndex(Relation<O> relation, PageFile<MkTabTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree with parameters of type DistanceFunction

MTree(PageFile<MTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

MTreeFactory(String fileName, int pageSize, long cacheSize, DistanceFunction<O,D> distanceFunction)
Constructor.

MTreeIndex(Relation<O> relation, PageFile<MTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

Uses of DistanceFunction in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters

Constructors in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters with parameters of type DistanceFunction

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist)
Constructs a double parameter with the given optionID.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, boolean optional)
Constructs a double parameter with the given optionID and optional flag.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, D defaultValue)
Constructs a double parameter with the given optionID and default value.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, List<ParameterConstraint<D>> constraints)
Constructs a double parameter with the given optionID, and parameter constraints.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, List<ParameterConstraint<D>> cons, boolean optional)
Constructs a double parameter with the given optionID, parameter constraints, and optional flag.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, List<ParameterConstraint<D>> cons, D defaultValue)
Constructs a double parameter with the given optionID, parameter constraints, and default value.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, ParameterConstraint<D> constraint)
Constructs a double parameter with the given optionID, and parameter constraint.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, ParameterConstraint<D> constraint, boolean optional)
Constructs a double parameter with the given optionID, parameter constraint, and optional flag.

DistanceParameter(OptionID optionID, DistanceFunction<?,D> dist, ParameterConstraint<D> constraint, D defaultValue)
Constructs a double parameter with the given optionID, parameter constraint, and default value.