Uses of Class
de.lmu.ifi.dbs.elki.distance.DoubleDistance

Packages that use DoubleDistance

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.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.distance	Distances and (in subpackages) distance functions and similarity functions.
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.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.
de.lmu.ifi.dbs.elki.preprocessing	Preprocessors used for data preparation in a first step of various algorithms or distance and similarity measures.

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

Fields in de.lmu.ifi.dbs.elki.algorithm with type parameters of type DoubleDistance

private PCAFilteredRunner<V,DoubleDistance>

DependencyDerivator.pca Holds the object performing the pca.

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

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

protected DoubleDistance

ProjectedDBSCAN.epsilon Holds the value of ProjectedDBSCAN.EPSILON_PARAM.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering with type parameters of type DoubleDistance

private DistanceParameter<DoubleDistance>	ProjectedDBSCAN.EPSILON_PARAM Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to AbstractLocallyWeightedDistanceFunction.
private ObjectParameter<DistanceFunction<V,DoubleDistance>>	ProjectedDBSCAN.INNER_DISTANCE_FUNCTION_PARAM Parameter distance function
private DistanceFunction<V,DoubleDistance>	ProjectedDBSCAN.innerDistanceFunction The inner distance function.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

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

(package private) DoubleDistance

ORCLUS.ProjectedEnergy.projectedEnergy

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type parameters of type DoubleDistance

private PCARunner<V,DoubleDistance>

ORCLUS.pca The PCA utility object.

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

ORCLUS.ProjectedEnergy(int i, int j, ORCLUS.ORCLUSCluster cluster, DoubleDistance projectedEnergy)

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

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

private DoubleDistance

SUBCLU.epsilon Holds the value of SUBCLU.EPSILON_PARAM.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with type parameters of type DoubleDistance

private DistanceParameter<DoubleDistance>

SUBCLU.EPSILON_PARAM Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to AbstractDimensionsSelectingDoubleDistanceFunction.

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

private DoubleDistance

PROCLUS.manhattanSegmentalDistance(V o1, V o2, Set<Integer> dimensions) Returns the Manhattan segmental distance between o1 and o2 relative to the specified dimensions.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return types with arguments of type DoubleDistance

private Map<Integer,List<DistanceResultPair<DoubleDistance>>>

PROCLUS.getLocalities(Set<Integer> m_c, Database<V> database) Computes the localities of the specified medoids.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with type arguments of type DoubleDistance

private Map<Integer,Set<Integer>>

PROCLUS.findDimensions(Set<Integer> medoids, Database<V> database, Map<Integer,List<DistanceResultPair<DoubleDistance>>> localities) Determines the set of correlated dimensions for each medoid in the specified medoid set.

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

Classes in de.lmu.ifi.dbs.elki.algorithm.outlier with type parameters of type DoubleDistance

class	KNNOutlier<O extends DatabaseObject,D extends DoubleDistance> Outlier Detection based on the distance of an object to its k nearest neighbor.
class	KNNWeightOutlier<O extends DatabaseObject,D extends DoubleDistance> Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier with type parameters of type DoubleDistance

private ObjectParameter<DistanceFunction<O,DoubleDistance>>	LoOP.COMPARISON_DISTANCE_FUNCTION_PARAM The distance function to determine the reachability distance between database objects.
private ObjectParameter<KernelFunction<V,DoubleDistance>>	ABOD.KERNEL_FUNCTION_PARAM Parameter for Kernel function.
(package private) KernelFunction<V,DoubleDistance>	ABOD.kernelFunction Store the configured Kernel version
(package private) MaterializeKNNPreprocessor<O,DoubleDistance>	LDOF.knnPreprocessor Preprocessor for materialization of kNN queries.
private ClassParameter<MaterializeKNNPreprocessor<O,DoubleDistance>>	LoOP.PREPROCESSOR_PARAM The preprocessor used to materialize the kNN neighborhoods.
(package private) MaterializeKNNPreprocessor<O,DoubleDistance>	LoOP.preprocessorcompare Preprocessor Step 1
(package private) MaterializeKNNPreprocessor<O,DoubleDistance>	LoOP.preprocessorref Preprocessor Step 2
private ObjectParameter<DistanceFunction<O,DoubleDistance>>	LoOP.REFERENCE_DISTANCE_FUNCTION_PARAM The distance function to determine the reachability distance between database objects.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier that return types with arguments of type DoubleDistance

List<DistanceResultPair<DoubleDistance>>	ReferenceBasedOutlierDetection.computeDistanceVector(V refPoint, Database<V> database) Computes for each object the distance to one reference point.
private KNNList<DoubleDistance>	SOD.getKNN(Database<V> database, Integer queryObject) Provides the k nearest neighbors in terms of the shared nearest neighbor distance.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.outlier with type arguments of type DoubleDistance

double

ReferenceBasedOutlierDetection.computeDensity(List<DistanceResultPair<DoubleDistance>> referenceDists, int index) Computes the density of an object.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance

Methods in de.lmu.ifi.dbs.elki.distance that return DoubleDistance

DoubleDistance	DoubleDistance.infiniteDistance() An infinite DoubleDistance is based on Double.POSITIVE_INFINITY.
DoubleDistance	DoubleDistance.minus(DoubleDistance distance)
DoubleDistance	DoubleDistance.nullDistance() A null DoubleDistance is based on 0.
DoubleDistance	DoubleDistance.parseString(String val) As pattern is required a String defining a Double.
DoubleDistance	DoubleDistance.plus(DoubleDistance distance)
DoubleDistance	DoubleDistance.times(double lambda) Returns a new distance as the product of this distance and the given double value.
DoubleDistance	DoubleDistance.times(DoubleDistance distance) Returns a new distance as the product of this distance and the given distance.
DoubleDistance	DoubleDistance.undefinedDistance() An undefined DoubleDistance is based on Double.NaN.

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

int	DoubleDistance.compareTo(DoubleDistance other)
DoubleDistance	DoubleDistance.minus(DoubleDistance distance)
DoubleDistance	DoubleDistance.plus(DoubleDistance distance)
DoubleDistance	DoubleDistance.times(DoubleDistance distance) Returns a new distance as the product of this distance and the given distance.

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

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction with type parameters of type DoubleDistance

private ObjectParameter<KernelFunction<V,DoubleDistance>>	KernelBasedLocallyWeightedDistanceFunction.KERNEL_FUNCTION_PARAM Parameter for the kernel function
private KernelFunction<V,DoubleDistance>	KernelBasedLocallyWeightedDistanceFunction.kernelFunction The kernel function that is used.

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

DoubleDistance	LocallyWeightedDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	EuclideanDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	LocallyWeightedDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	EuclideanDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	LPNormDistanceFunction.distance(V v1, V v2) Returns the distance between the specified FeatureVectors as a LP-Norm for the currently set p.
DoubleDistance	KernelBasedLocallyWeightedDistanceFunction.distance(V v1, V v2) Computes the distance between two given DatabaseObjects according to this distance function.
DoubleDistance	WeightedDistanceFunction.distance(V o1, V o2) Provides the Weighted distance for feature vectors.
DoubleDistance	CosineDistanceFunction.distance(V v1, V v2) Computes the cosine distance for two given feature vectors.
DoubleDistance	MaximumDistanceFunction.distance(V v1, V v2)
DoubleDistance	ManhattanDistanceFunction.distance(V v1, V v2)
DoubleDistance	LocallyWeightedDistanceFunction.distance(V v1, V v2) Computes the distance between two given real vectors according to this distance function.
DoubleDistance	ArcCosineDistanceFunction.distance(V v1, V v2) Computes the cosine distance for two given feature vectors.
DoubleDistance	EuclideanDistanceFunction.distance(V v1, V v2) Provides the Euclidean distance between the given two vectors.
DoubleDistance	MinimumDistanceFunction.distance(V v1, V v2)
DoubleDistance	LocallyWeightedDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
DoubleDistance	EuclideanDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
DoubleDistance	LocallyWeightedDistanceFunction.minDist(HyperBoundingBox mbr, V v)
DoubleDistance	EuclideanDistanceFunction.minDist(HyperBoundingBox mbr, V v)

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

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter with type parameters of type DoubleDistance

protected ObjectParameter<NormalizedSimilarityFunction<V,DoubleDistance>>	SimilarityAdapterAbstract.SIMILARITY_FUNCTION_PARAM Parameter to specify the similarity function to derive the distance between database objects from.
protected NormalizedSimilarityFunction<V,DoubleDistance>	SimilarityAdapterAbstract.similarityFunction Holds the similarity function.

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

abstract DoubleDistance	SimilarityAdapterAbstract.distance(V v1, V v2) Distance implementation
DoubleDistance	SimilarityAdapterArccos.distance(V v1, V v2) Distance implementation
DoubleDistance	SimilarityAdapterLinear.distance(V v1, V v2) Distance implementation
DoubleDistance	SimilarityAdapterLn.distance(V v1, V v2) Distance implementation

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

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

DoubleDistance

HistogramIntersectionDistanceFunction.distance(V v1, V v2)

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

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

DoubleDistance	PearsonCorrelationDistanceFunction.distance(V v1, V v2) Computes the Pearson correlation distance for two given feature vectors.
DoubleDistance	SquaredPearsonCorrelationDistanceFunction.distance(V v1, V v2) Computes the squared Pearson correlation distance for two given feature vectors.

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

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction.external with type parameters of type DoubleDistance

private Map<Pair<Integer,Integer>,DoubleDistance>	FileBasedDoubleDistanceFunction.cache
private DistanceParser<V,DoubleDistance>	FileBasedDoubleDistanceFunction.parser
private ObjectParameter<DistanceParser<V,DoubleDistance>>	FileBasedDoubleDistanceFunction.PARSER_PARAM Optional parameter to specify the parsers to provide a database, must extend DistanceParser.

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

DoubleDistance	DiskCacheBasedDoubleDistanceFunction.distance(Integer id1, Integer id2) Returns the distance between the two objects specified by their objects ids.
DoubleDistance	FileBasedDoubleDistanceFunction.distance(Integer id1, Integer id2) Returns the distance between the two objects specified by their objects ids.
DoubleDistance	DiskCacheBasedDoubleDistanceFunction.distance(Integer id1, V o2) Returns the distance between the two specified objects.
DoubleDistance	FileBasedDoubleDistanceFunction.distance(Integer id1, V o2) Returns the distance between the two specified objects.
DoubleDistance	DiskCacheBasedDoubleDistanceFunction.distance(V o1, V o2) Computes the distance between two given DatabaseObjects according to this distance function.
DoubleDistance	FileBasedDoubleDistanceFunction.distance(V o1, V o2) Computes the distance between two given DatabaseObjects according to this distance function.

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

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

DoubleDistance	DimensionsSelectingEuclideanDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	DimensionSelectingDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	DimensionsSelectingEuclideanDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	DimensionSelectingDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
DoubleDistance	DimensionsSelectingEuclideanDistanceFunction.distance(V v1, V v2) Provides the Euclidean distance between two given feature vectors in the selected dimensions.
DoubleDistance	DimensionSelectingDistanceFunction.distance(V v1, V v2) Computes the distance between two given DatabaseObjects according to this distance function.
DoubleDistance	DimensionsSelectingEuclideanDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
DoubleDistance	DimensionSelectingDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
DoubleDistance	DimensionsSelectingEuclideanDistanceFunction.minDist(HyperBoundingBox mbr, V v)
DoubleDistance	DimensionSelectingDistanceFunction.minDist(HyperBoundingBox mbr, V v)

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

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

DoubleDistance	LCSSDistanceFunction.distance(V v1, V v2) Provides the Longest Common Subsequence distance between the given two vectors.
DoubleDistance	ERPDistanceFunction.distance(V v1, V v2) Provides the Edit Distance With Real Penalty distance between the given two vectors.
DoubleDistance	DTWDistanceFunction.distance(V v1, V v2) Provides the Dynamic Time Warping distance between the given two vectors.
DoubleDistance	EDRDistanceFunction.distance(V v1, V v2) Provides the Edit Distance on Real Sequence distance between the given two vectors.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.similarityfunction

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction that return DoubleDistance

DoubleDistance	FractionalSharedNearestNeighborSimilarityFunction.similarity(Integer id1, Integer id2)
DoubleDistance	FractionalSharedNearestNeighborSimilarityFunction.similarity(O o1, O o2)

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

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel that return DoubleDistance

DoubleDistance	ArbitraryKernelFunctionWrapper.distance(Integer id1, Integer id2) Returns the distance between the two objects specified by their object ids.
DoubleDistance	FooKernelFunction.distance(O fv1, O fv2)
DoubleDistance	LinearKernelFunction.distance(O fv1, O fv2)
DoubleDistance	ArbitraryKernelFunctionWrapper.distance(O o1, O o2) Returns the distance between the two specified objects.
DoubleDistance	PolynomialKernelFunction.distance(O fv1, O fv2)
DoubleDistance	FooKernelFunction.similarity(O o1, O o2) Provides an experimental kernel similarity between the given two vectors.
DoubleDistance	LinearKernelFunction.similarity(O o1, O o2) Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by V1^T*V2
DoubleDistance	ArbitraryKernelFunctionWrapper.similarity(O o1, O o2) Provides a wrapper for arbitrary kernel functions whose kernel matrix has already been precomputed.
DoubleDistance	PolynomialKernelFunction.similarity(O o1, O o2) Provides the linear kernel similarity between the given two vectors.

Constructor parameters in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel with type arguments of type DoubleDistance

KernelMatrix(KernelFunction<O,DoubleDistance> kernelFunction, Database<O> database)
Provides a new kernel matrix.

KernelMatrix(KernelFunction<O,DoubleDistance> kernelFunction, Database<O> database, List<Integer> ids)
Provides a new kernel matrix.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.math.linearalgebra.pca

Fields in de.lmu.ifi.dbs.elki.math.linearalgebra.pca with type parameters of type DoubleDistance

private DistanceFunction<V,DoubleDistance>

WeightedCovarianceMatrixBuilder.weightDistance Holds the distance function used for weight calculation

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.preprocessing

Fields in de.lmu.ifi.dbs.elki.preprocessing declared as DoubleDistance

static DoubleDistance	DiSHPreprocessor.DEFAULT_EPSILON The default value for epsilon.
private DoubleDistance[]	DiSHPreprocessor.epsilon The epsilon value for each dimension;
protected DoubleDistance	RangeQueryBasedLocalPCAPreprocessor.epsilon Holds the value of RangeQueryBasedLocalPCAPreprocessor.EPSILON_PARAM.

Fields in de.lmu.ifi.dbs.elki.preprocessing with type parameters of type DoubleDistance

protected DistanceParameter<DoubleDistance>	RangeQueryBasedLocalPCAPreprocessor.EPSILON_PARAM Parameter to specify the maximum radius of the neighborhood to be considered in the PCA, must be suitable to the distance function specified.
private PCAFilteredRunner<V,DoubleDistance>	LocalPCAPreprocessor.pca PCA utility object.
protected ObjectParameter<DistanceFunction<V,DoubleDistance>>	LocalPCAPreprocessor.PCA_DISTANCE_PARAM Parameter to specify the distance function used for running PCA.
protected DistanceFunction<V,DoubleDistance>	LocalPCAPreprocessor.pcaDistanceFunction Holds the instance of the distance function specified by LocalPCAPreprocessor.PCA_DISTANCE_PARAM.

Methods in de.lmu.ifi.dbs.elki.preprocessing that return DoubleDistance

DoubleDistance[]

DiSHPreprocessor.getEpsilon() Returns the value of the epsilon parameter.

Methods in de.lmu.ifi.dbs.elki.preprocessing that return types with arguments of type DoubleDistance

protected abstract List<DistanceResultPair<DoubleDistance>>	LocalPCAPreprocessor.objectsForPCA(Integer id, Database<V> database) Returns the objects to be considered within the PCA for the specified query object.
protected List<DistanceResultPair<DoubleDistance>>	RangeQueryBasedLocalPCAPreprocessor.objectsForPCA(Integer id, Database<V> database)
protected List<DistanceResultPair<DoubleDistance>>	KnnQueryBasedLocalPCAPreprocessor.objectsForPCA(Integer id, Database<V> database)