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

Packages that use PrimitiveDistanceFunction

Package	Description
de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality	Quality measures for k-Means results.
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial	Spatial outlier detection algorithms
de.lmu.ifi.dbs.elki.database.query.distance	Prepared queries for distances.
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
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.geo	Geographic (earth) distance functions.
de.lmu.ifi.dbs.elki.distance.distancefunction.histogram	Distance functions for one-dimensional histograms.
de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski	Minkowski space L_p norms such as the popular Euclidean and Manhattan distances.
de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic	Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence.
de.lmu.ifi.dbs.elki.distance.distancefunction.strings	Distance functions for strings.
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	Similarity functions.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Kernel functions.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca	Principal Component Analysis (PCA) and Eigenvector processing.
tutorial.distancefunction	Classes from the tutorial on implementing distance functions.

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

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

Modifier and Type	Field and Description
protected PrimitiveDistanceFunction<? super O,D>	AbstractPrimitiveDistanceBasedAlgorithm.distanceFunction Holds the instance of the distance function specified by DistanceBasedAlgorithm.DISTANCE_FUNCTION_ID.
protected PrimitiveDistanceFunction<O,D>	AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer.distanceFunction Distance function to use.

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

Modifier and Type	Method and Description
PrimitiveDistanceFunction<? super O,D>	AbstractPrimitiveDistanceBasedAlgorithm.getDistanceFunction() Returns the distanceFunction.

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

Constructor and Description
AbstractPrimitiveDistanceBasedAlgorithm(PrimitiveDistanceFunction<? super O,D> distanceFunction) Constructor.
DependencyDerivator(PrimitiveDistanceFunction<V,D> distanceFunction, NumberFormat nf, PCAFilteredRunner<V> pca, int sampleSize, boolean randomsample) Constructor.

Uses of PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

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

Modifier and Type	Method and Description
List<V>	KMeansInitialization.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction) Choose initial means
List<V>	RandomlyChosenInitialMeans.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction)
List<V>	RandomlyGeneratedInitialMeans.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction)
List<V>	FirstKInitialMeans.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction)
List<V>	KMeansPlusPlusInitialMeans.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction)
List<V>	SampleKMeansInitialization.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction)
List<V>	PAMInitialMeans.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction)
List<V>	FarthestPointsInitialMeans.chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction)
void	KMeansBisecting.setDistanceFunction(PrimitiveDistanceFunction<? super NumberVector<?>,D> distanceFunction)
void	KMeans.setDistanceFunction(PrimitiveDistanceFunction<? super NumberVector<?>,D> distanceFunction) Set the distance function to use.
void	BestOfMultipleKMeans.setDistanceFunction(PrimitiveDistanceFunction<? super NumberVector<?>,D> distanceFunction)
void	AbstractKMeans.setDistanceFunction(PrimitiveDistanceFunction<? super NumberVector<?>,D> distanceFunction)

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

Constructor and Description
AbstractKMeans(PrimitiveDistanceFunction<? super NumberVector<?>,D> distanceFunction, int k, int maxiter, KMeansInitialization<V> initializer) Constructor.
KMeansBatchedLloyd(PrimitiveDistanceFunction<NumberVector<?>,D> distanceFunction, int k, int maxiter, KMeansInitialization<V> initializer, int blocks, RandomFactory random) Constructor.
KMeansHybridLloydMacQueen(PrimitiveDistanceFunction<NumberVector<?>,D> distanceFunction, int k, int maxiter, KMeansInitialization<V> initializer) Constructor.
KMeansLloyd(PrimitiveDistanceFunction<NumberVector<?>,D> distanceFunction, int k, int maxiter, KMeansInitialization<V> initializer) Constructor.
KMeansMacQueen(PrimitiveDistanceFunction<NumberVector<?>,D> distanceFunction, int k, int maxiter, KMeansInitialization<V> initializer) Constructor.
KMediansLloyd(PrimitiveDistanceFunction<NumberVector<?>,D> distanceFunction, int k, int maxiter, KMeansInitialization<V> initializer) Constructor.
KMedoidsEM(PrimitiveDistanceFunction<? super V,D> distanceFunction, int k, int maxiter, KMedoidsInitialization<V> initializer) Constructor.
KMedoidsPAM(PrimitiveDistanceFunction<? super V,D> distanceFunction, int k, int maxiter, KMedoidsInitialization<V> initializer) Constructor.

Uses of PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality with parameters of type PrimitiveDistanceFunction

Modifier and Type	Method and Description
<V extends O> double	KMeansQualityMeasure.calculateCost(Clustering<? extends MeanModel<V>> clustering, PrimitiveDistanceFunction<? super V,? extends D> distanceFunction, Relation<V> relation) Calculates and returns the quality measure.
<V extends NumberVector<?>> double	WithinClusterVarianceQualityMeasure.calculateCost(Clustering<? extends MeanModel<V>> clustering, PrimitiveDistanceFunction<? super V,? extends NumberDistance<?,?>> distanceFunction, Relation<V> relation)
<V extends NumberVector<?>> double	WithinClusterMeanDistanceQualityMeasure.calculateCost(Clustering<? extends MeanModel<V>> clustering, PrimitiveDistanceFunction<? super V,? extends NumberDistance<?,?>> distanceFunction, Relation<V> relation)

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

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

Modifier and Type	Field and Description
protected PrimitiveDistanceFunction<O,D>	AbstractDistanceBasedSpatialOutlier.Parameterizer.distanceFunction The distance function to use on the non-spatial attributes.

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

Constructor and Description
SLOM(NeighborSetPredicate.Factory<N> npred, PrimitiveDistanceFunction<O,D> nonSpatialDistanceFunction) Constructor.
SOF(NeighborSetPredicate.Factory<N> npred, PrimitiveDistanceFunction<O,D> nonSpatialDistanceFunction) Constructor.

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

Fields in de.lmu.ifi.dbs.elki.database.query.distance declared as PrimitiveDistanceFunction

Modifier and Type	Field and Description
protected PrimitiveDistanceFunction<? super O,D>	PrimitiveDistanceQuery.distanceFunction The distance function we use.

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

Modifier and Type	Method and Description
PrimitiveDistanceFunction<? super O,D>	PrimitiveDistanceQuery.getDistanceFunction()

Constructors in de.lmu.ifi.dbs.elki.database.query.distance with parameters of type PrimitiveDistanceFunction

Constructor and Description
PrimitiveDistanceQuery(Relation<? extends O> relation, PrimitiveDistanceFunction<? super O,D> distanceFunction) Constructor.
PrimitiveDistanceSimilarityQuery(Relation<? extends O> relation, PrimitiveDistanceFunction<? super O,D> distanceFunction, PrimitiveSimilarityFunction<? super O,D> similarityFunction) Constructor.

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

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

Modifier and Type	Interface and Description
interface	DoubleNorm<O> Interface for norms in the double domain.
interface	NumberVectorDistanceFunction<D extends Distance<D>> Base interface for the common case of distance functions defined on numerical vectors.
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 PrimitiveDistanceFunction

Modifier and Type	Class and Description
class	AbstractPrimitiveDistanceFunction<O,D extends Distance<D>> AbstractDistanceFunction provides some methods valid for any extending class.
class	AbstractSpatialDoubleDistanceFunction Abstract base class for typical distance functions that allow rectangle-to-rectangle lower bounds.
class	AbstractSpatialDoubleDistanceNorm Abstract base class for typical distance functions that allow rectangle-to-rectangle lower bounds.
class	AbstractVectorDoubleDistanceFunction Abstract base class for the most common family of distance functions: defined on number vectors and returning double values.
class	AbstractVectorDoubleDistanceNorm Abstract base class for double-valued number-vector-based distances based on norms.
class	ArcCosineDistanceFunction Cosine distance function for feature vectors.
class	BrayCurtisDistanceFunction Bray-Curtis distance function / Sørensen–Dice coefficient for continuous spaces.
class	CanberraDistanceFunction Canberra distance function, a variation of Manhattan distance.
class	ClarkDistanceFunction Clark distance function for vector spaces.
class	CosineDistanceFunction Cosine distance function for feature vectors.
class	Kulczynski1DistanceFunction Kulczynski similarity 1, in distance form.
class	LorentzianDistanceFunction Lorentzian distance function for vector spaces.
class	WeightedCanberraDistanceFunction Weighted Canberra distance function, a variation of Manhattan distance.
class	WeightedDistanceFunction Provides the Weighted distance for feature vectors.

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

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

Modifier and Type	Class and Description
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 PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation

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

Modifier and Type	Class and Description
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 PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.geo

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

Modifier and Type	Class and Description
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 PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.histogram

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

Modifier and Type	Class and Description
class	HistogramMatchDistanceFunction Distance function based on histogram matching, i.e.
class	KolmogorovSmirnovDistanceFunction Distance function based on the Kolmogorov-Smirnov goodness of fit test.

Uses of PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski

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

Modifier and Type	Class and Description
class	EuclideanDistanceFunction Provides the Euclidean distance for FeatureVectors.
class	LPIntegerNormDistanceFunction Provides a LP-Norm for number vectors.
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	SparseEuclideanDistanceFunction Euclidean distance function.
class	SparseLPNormDistanceFunction Provides a LP-Norm for FeatureVectors.
class	SparseManhattanDistanceFunction Manhattan distance function.
class	SparseMaximumDistanceFunction Maximum distance function.
class	SquaredEuclideanDistanceFunction Provides the squared Euclidean distance for FeatureVectors.
class	WeightedEuclideanDistanceFunction Provides the Euclidean distance for FeatureVectors.
class	WeightedLPNormDistanceFunction Weighted version of the Minkowski L_p metrics distance function.
class	WeightedManhattanDistanceFunction Weighted version of the Minkowski L_p metrics distance function.
class	WeightedMaximumDistanceFunction Weighted version of the Minkowski L_p metrics distance function.
class	WeightedSquaredEuclideanDistanceFunction Provides the squared Euclidean distance for FeatureVectors.

Uses of PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic

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

Modifier and Type	Class and Description
class	ChiSquaredDistanceFunction Chi-Squared distance function, symmetric version.
class	JeffreyDivergenceDistanceFunction Provides the Jeffrey Divergence Distance for FeatureVectors.
class	JensenShannonDivergenceDistanceFunction Jensen-Shannon Divergence is essentially the same as Jeffrey divergence, only scaled by half.
class	KullbackLeiblerDivergenceAsymmetricDistanceFunction Kullback-Leibler (asymmetric!)
class	KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction Kullback-Leibler (asymmetric!)
class	SqrtJensenShannonDivergenceDistanceFunction The square root of Jensen-Shannon divergence is metric.

Uses of PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.strings

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

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

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

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

Modifier and Type	Class and Description
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	DimensionSelectingDistanceFunction Provides a distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension.
class	SubspaceEuclideanDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.
class	SubspaceLPNormDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.
class	SubspaceManhattanDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.
class	SubspaceMaximumDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.

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

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

Modifier and Type	Class and Description
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 PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.distance.similarityfunction

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

Modifier and Type	Class and Description
class	JaccardPrimitiveSimilarityFunction<O extends FeatureVector<?>> A flexible extension of Jaccard similarity to non-binary vectors.

Fields in de.lmu.ifi.dbs.elki.distance.similarityfunction declared as PrimitiveDistanceFunction

Modifier and Type	Field and Description
protected PrimitiveDistanceFunction<? super O,? extends NumberDistance<?,?>>	InvertedDistanceSimilarityFunction.distanceFunction Holds the similarity function.

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

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

Modifier and Type	Class and Description
class	LinearKernelFunction 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 PrimitiveDistanceFunction in de.lmu.ifi.dbs.elki.math.linearalgebra.pca

Fields in de.lmu.ifi.dbs.elki.math.linearalgebra.pca declared as PrimitiveDistanceFunction

Modifier and Type	Field and Description
private PrimitiveDistanceFunction<? super V,DoubleDistance>	WeightedCovarianceMatrixBuilder.weightDistance Holds the distance function used for weight calculation.

Uses of PrimitiveDistanceFunction in tutorial.distancefunction

Classes in tutorial.distancefunction that implement PrimitiveDistanceFunction

Modifier and Type	Class and Description
class	MultiLPNorm Tutorial example for ELKI.
class	TutorialDistanceFunction Tutorial example for ELKI.