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

Packages that use PrimitiveDoubleDistanceFunction

Package	Description
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace	Subspace outlier detection methods.
de.lmu.ifi.dbs.elki.application.greedyensemble	Greedy ensembles for outlier detection.
de.lmu.ifi.dbs.elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries.
de.lmu.ifi.dbs.elki.database.query.range	Prepared queries for ε-range queries.
de.lmu.ifi.dbs.elki.datasource.filter.transform	Data space transformations.
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.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.index.tree.metrical.mtreevariants.query	Classes for performing queries (knn, range, ...) on metrical trees.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.
tutorial.distancefunction	Classes from the tutorial on implementing distance functions.

Uses of PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical

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

Modifier and Type	Method and Description
private void	SLINK.step2double(DBIDRef id, DBIDs processedIDs, Relation<? extends O> relation, PrimitiveDoubleDistanceFunction<? super O> distFunc, WritableDoubleDistanceDataStore m) Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.

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

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

Modifier and Type	Method and Description
protected double	KMeansPlusPlusInitialMeans.updateWeights(double[] weights, ArrayDBIDs ids, DBID latest, PrimitiveDoubleDistanceFunction<V> distF, Relation<V> rel) Update the weight list.

Uses of PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace

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

Modifier and Type	Method and Description
private DoubleDistanceDBIDList	OUTRES.subsetNeighborhoodQuery(DistanceDBIDList<DoubleDistance> neighc, DBIDRef dbid, PrimitiveDoubleDistanceFunction<? super V> df, double adjustedEps, OUTRES.KernelDensityEstimator kernel) Refine neighbors within a subset.

Uses of PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.application.greedyensemble

Methods in de.lmu.ifi.dbs.elki.application.greedyensemble that return PrimitiveDoubleDistanceFunction

Modifier and Type	Method and Description
private PrimitiveDoubleDistanceFunction<NumberVector<?>>	GreedyEnsembleExperiment.getDistanceFunction(double[] estimated_weights)

Uses of PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.database.query.knn

Fields in de.lmu.ifi.dbs.elki.database.query.knn declared as PrimitiveDoubleDistanceFunction

Modifier and Type	Field and Description
(package private) PrimitiveDoubleDistanceFunction<O>	DoubleOptimizedDistanceKNNQuery.rawdist Raw distance function.

Methods in de.lmu.ifi.dbs.elki.database.query.knn with parameters of type PrimitiveDoubleDistanceFunction

Modifier and Type	Method and Description
private static <O> void	DoubleOptimizedDistanceKNNQuery.linearScan(Relation<? extends O> relation, DBIDIter iter, PrimitiveDoubleDistanceFunction<? super O> rawdist, O obj, DoubleDistanceKNNHeap heap)

Uses of PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.database.query.range

Fields in de.lmu.ifi.dbs.elki.database.query.range declared as PrimitiveDoubleDistanceFunction

Modifier and Type	Field and Description
(package private) PrimitiveDoubleDistanceFunction<? super O>	DoubleOptimizedDistanceRangeQuery.rawdist Raw distance function.

Methods in de.lmu.ifi.dbs.elki.database.query.range with parameters of type PrimitiveDoubleDistanceFunction

Modifier and Type	Method and Description
private static <O> void	DoubleOptimizedDistanceRangeQuery.linearScan(Relation<? extends O> relation, DBIDIter iter, PrimitiveDoubleDistanceFunction<? super O> rawdist, O obj, double range, ModifiableDoubleDistanceDBIDList result)

Uses of PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.datasource.filter.transform

Fields in de.lmu.ifi.dbs.elki.datasource.filter.transform declared as PrimitiveDoubleDistanceFunction

Modifier and Type	Field and Description
(package private) PrimitiveDoubleDistanceFunction<? super O>	ClassicMultidimensionalScalingTransform.dist Distance function to use.
(package private) PrimitiveDoubleDistanceFunction<? super O>	ClassicMultidimensionalScalingTransform.Parameterizer.dist Distance function to use.

Constructors in de.lmu.ifi.dbs.elki.datasource.filter.transform with parameters of type PrimitiveDoubleDistanceFunction

Constructor and Description
ClassicMultidimensionalScalingTransform(int tdim, PrimitiveDoubleDistanceFunction<? super O> dist) Constructor.

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

Subinterfaces of PrimitiveDoubleDistanceFunction 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	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 PrimitiveDoubleDistanceFunction

Modifier and Type	Class and Description
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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.geo

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.histogram

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.distance.similarityfunction

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

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

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

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

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 PrimitiveDoubleDistanceFunction in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query

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

Modifier and Type	Field and Description
protected PrimitiveDoubleDistanceFunction<? super O>	DoubleDistanceMetricalIndexRangeQuery.distf Distance function
protected PrimitiveDoubleDistanceFunction<? super O>	DoubleDistanceMetricalIndexKNNQuery.distf Distance function

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

Constructor and Description
DoubleDistanceMetricalIndexKNNQuery(AbstractMTree<O,DoubleDistance,?,?,?> index, DistanceQuery<O,DoubleDistance> distanceQuery, PrimitiveDoubleDistanceFunction<? super O> distf) Constructor.
DoubleDistanceMetricalIndexRangeQuery(AbstractMTree<O,DoubleDistance,?,?,?> index, DistanceQuery<O,DoubleDistance> distanceQuery, PrimitiveDoubleDistanceFunction<? super O> distf) Constructor.

Uses of PrimitiveDoubleDistanceFunction in tutorial.clustering

Fields in tutorial.clustering declared as PrimitiveDoubleDistanceFunction

Modifier and Type	Field and Description
protected PrimitiveDoubleDistanceFunction<? super NumberVector<?>>	SameSizeKMeansAlgorithm.Parameterizer.distanceFunction Distance function

Methods in tutorial.clustering with parameters of type PrimitiveDoubleDistanceFunction

Modifier and Type	Method and Description
protected void	SameSizeKMeansAlgorithm.updateDistances(Relation<V> relation, List<? extends NumberVector<?>> means, WritableDataStore<SameSizeKMeansAlgorithm.Meta> metas, PrimitiveDoubleDistanceFunction<NumberVector<?>> df) Compute the distances of each object to all means.

Constructors in tutorial.clustering with parameters of type PrimitiveDoubleDistanceFunction

Constructor and Description
SameSizeKMeansAlgorithm(PrimitiveDoubleDistanceFunction<? super NumberVector<?>> distanceFunction, int k, int maxiter, KMeansInitialization<V> initializer) Constructor.

Uses of PrimitiveDoubleDistanceFunction in tutorial.distancefunction

Classes in tutorial.distancefunction that implement PrimitiveDoubleDistanceFunction

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