Uses of Interface
elki.distance.PrimitiveDistance

Packages that use PrimitiveDistance

Package	Description
elki.application.greedyensemble	Greedy ensembles for outlier detection.
elki.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
elki.database.query.distance	Prepared queries for distances.
elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries.
elki.datasource.filter.transform	Data space transformations.
elki.distance	Distance functions for use within ELKI.
elki.distance.colorhistogram	Distance functions for color histograms.
elki.distance.correlation	Distance functions using correlations.
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.index.tree.spatial.kd	K-d-tree and variants.
elki.math.linearalgebra.pca	Principal Component Analysis (PCA) and eigenvector processing.
elki.outlier.spatial	Spatial outlier detection algorithms.
elki.outlier.subspace	Subspace outlier detection methods.
elki.similarity	Similarity functions.
elki.similarity.cluster	Similarity measures for comparing clusters.
elki.similarity.kernel	Kernel functions.
tutorial.distancefunction	Classes from the tutorial on implementing distance functions.

Uses of PrimitiveDistance in elki.application.greedyensemble

Methods in elki.application.greedyensemble that return PrimitiveDistance

Modifier and Type	Method	Description
private PrimitiveDistance<NumberVector>	GreedyEnsembleExperiment.getDistance(double[] estimated_weights)

Uses of PrimitiveDistance in elki.clustering.hierarchical

Methods in elki.clustering.hierarchical with parameters of type PrimitiveDistance

Modifier and Type	Method	Description
private void	SLINK.step2primitive(DBIDRef id, DBIDArrayIter it, int n, Relation<? extends O> relation, PrimitiveDistance<? super O> distance, WritableDoubleDataStore m)	Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.

Uses of PrimitiveDistance in elki.database.query.distance

Fields in elki.database.query.distance declared as PrimitiveDistance

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

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

Modifier and Type	Method	Description
PrimitiveDistance<? super O>	PrimitiveDistanceQuery.getDistance()

Constructors in elki.database.query.distance with parameters of type PrimitiveDistance

Constructor	Description
PrimitiveDistanceQuery(Relation<? extends O> relation, PrimitiveDistance<? super O> distanceFunction)	Constructor.
PrimitiveDistanceSimilarityQuery(Relation<? extends O> relation, PrimitiveDistance<? super O> distanceFunction, PrimitiveSimilarity<? super O> similarityFunction)	Constructor.

Uses of PrimitiveDistance in elki.database.query.knn

Fields in elki.database.query.knn declared as PrimitiveDistance

Modifier and Type	Field	Description
private PrimitiveDistance<? super O>	LinearScanPrimitiveKNNByObject.rawdist	Unboxed distance function.

Uses of PrimitiveDistance in elki.datasource.filter.transform

Fields in elki.datasource.filter.transform declared as PrimitiveDistance

Modifier and Type	Field	Description
(package private) PrimitiveDistance<? super I>	ClassicMultidimensionalScalingTransform.dist	Distance function to use.
(package private) PrimitiveDistance<? super I>	ClassicMultidimensionalScalingTransform.Par.dist	Distance function to use.
(package private) PrimitiveDistance<? super I>	FastMultidimensionalScalingTransform.dist	Distance function to use.
(package private) PrimitiveDistance<? super I>	FastMultidimensionalScalingTransform.Par.dist	Distance function to use.

Methods in elki.datasource.filter.transform with parameters of type PrimitiveDistance

Modifier and Type	Method	Description
protected static <I> double[][]	ClassicMultidimensionalScalingTransform.computeSquaredDistanceMatrix(java.util.List<I> col, PrimitiveDistance<? super I> dist)	Compute the squared distance matrix.

Constructors in elki.datasource.filter.transform with parameters of type PrimitiveDistance

Constructor	Description
ClassicMultidimensionalScalingTransform(int tdim, PrimitiveDistance<? super I> dist, NumberVector.Factory<O> factory)	Constructor.
FastMultidimensionalScalingTransform(int tdim, PrimitiveDistance<? super I> dist, NumberVector.Factory<O> factory, RandomFactory random)	Constructor.

Uses of PrimitiveDistance in elki.distance

Subinterfaces of PrimitiveDistance in elki.distance

Modifier and Type	Interface	Description
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	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 PrimitiveDistance

Modifier and Type	Class	Description
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	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.

Uses of PrimitiveDistance in elki.distance.colorhistogram

Classes in elki.distance.colorhistogram that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.correlation

Classes in elki.distance.correlation that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.geo

Classes in elki.distance.geo that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.histogram

Classes in elki.distance.histogram that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.minkowski

Classes in elki.distance.minkowski that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.probabilistic

Classes in elki.distance.probabilistic that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.set

Classes in elki.distance.set that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.strings

Classes in elki.distance.strings that implement PrimitiveDistance

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

Uses of PrimitiveDistance in elki.distance.subspace

Classes in elki.distance.subspace that implement PrimitiveDistance

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 PrimitiveDistance in elki.distance.timeseries

Classes in elki.distance.timeseries that implement PrimitiveDistance

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 PrimitiveDistance in elki.evaluation.clustering.internal

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

Modifier and Type	Field	Description
private PrimitiveDistance<? super NumberVector>	ConcordantPairsGammaTau.distance	Distance function to use.
private PrimitiveDistance<NumberVector>	ConcordantPairsGammaTau.Par.distance	Distance function to use.

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

Constructor	Description
ConcordantPairsGammaTau(PrimitiveDistance<? super NumberVector> distance, NoiseHandling noiseHandling)	Constructor.

Uses of PrimitiveDistance in elki.index.tree.spatial.kd

Fields in elki.index.tree.spatial.kd declared as PrimitiveDistance

Modifier and Type	Field	Description
private PrimitiveDistance<? super O>	MinimalisticMemoryKDTree.KDTreePrioritySearcher.distance	Distance to use.
private PrimitiveDistance<? super O>	SmallMemoryKDTree.KDTreePrioritySearcher.distance	Distance to use.

Constructors in elki.index.tree.spatial.kd with parameters of type PrimitiveDistance

Constructor	Description
KDTreePrioritySearcher(PrimitiveDistance<? super O> distance)	Constructor.
KDTreePrioritySearcher(PrimitiveDistance<? super O> distance)	Constructor.

Uses of PrimitiveDistance in elki.math.linearalgebra.pca

Fields in elki.math.linearalgebra.pca declared as PrimitiveDistance

Modifier and Type	Field	Description
private PrimitiveDistance<? super NumberVector>	WeightedCovarianceMatrixBuilder.weightDistance	Holds the distance function used for weight calculation.

Uses of PrimitiveDistance in elki.outlier.spatial

Fields in elki.outlier.spatial declared as PrimitiveDistance

Modifier and Type	Field	Description
protected PrimitiveDistance<O>	AbstractDistanceBasedSpatialOutlier.Par.distance	The distance function to use on the non-spatial attributes.

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

Constructor	Description
SLOM(NeighborSetPredicate.Factory<N> npred, PrimitiveDistance<O> nonSpatialDistance)	Constructor.
SOF(NeighborSetPredicate.Factory<N> npred, PrimitiveDistance<O> nonSpatialDistance)	Constructor.

Uses of PrimitiveDistance in elki.outlier.subspace

Methods in elki.outlier.subspace with parameters of type PrimitiveDistance

Modifier and Type	Method	Description
private DoubleDBIDList	OUTRES.initialRange(DBIDRef obj, DBIDs cands, PrimitiveDistance<? super NumberVector> df, double eps, OUTRES.KernelDensityEstimator kernel, ModifiableDoubleDBIDList n)	Initial range query.
private DoubleDBIDList	OUTRES.subsetNeighborhoodQuery(DoubleDBIDList neighc, DBIDRef dbid, PrimitiveDistance<? super NumberVector> df, double adjustedEps, OUTRES.KernelDensityEstimator kernel, ModifiableDoubleDBIDList n)	Refine neighbors within a subset.

Uses of PrimitiveDistance in elki.similarity

Classes in elki.similarity that implement PrimitiveDistance

Modifier and Type	Class	Description
class	Kulczynski1Similarity	Kulczynski similarity 1.

Fields in elki.similarity declared as PrimitiveDistance

Modifier and Type	Field	Description
protected PrimitiveDistance<? super O>	InvertedDistanceSimilarity.distanceFunction	Holds the similarity function.

Uses of PrimitiveDistance in elki.similarity.cluster

Subinterfaces of PrimitiveDistance in elki.similarity.cluster

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

Classes in elki.similarity.cluster that implement PrimitiveDistance

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 PrimitiveDistance in elki.similarity.kernel

Classes in elki.similarity.kernel that implement PrimitiveDistance

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 PrimitiveDistance in tutorial.distancefunction

Classes in tutorial.distancefunction that implement PrimitiveDistance

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.