Package elki.distance

Interface NumberVectorDistance<O>

Type Parameters:

O - vector type, usually NumberVector or a parent type

All Superinterfaces:

Distance<O>, PrimitiveDistance<O>

All Known Subinterfaces:

WeightedNumberVectorDistance<V>

All Known Implementing Classes:

AbsolutePearsonCorrelationDistance, AbsoluteUncenteredCorrelationDistance, AbstractEditDistance, AbstractNumberVectorDistance, ArcCosineDistance, ArcCosineUnitlengthDistance, BrayCurtisDistance, CanberraDistance, ChiDistance, ChiSquaredDistance, ClarkDistance, CosineDistance, CosineUnitlengthDistance, DerivativeDTWDistance, DimensionSelectingLatLngDistance, DTWDistance, EDRDistance, ERPDistance, EuclideanDistance, FisherRaoDistance, HammingDistance, HellingerDistance, HistogramIntersectionDistance, HistogramMatchDistance, HSBHistogramQuadraticDistance, JaccardSimilarityDistance, JeffreyDivergenceDistance, JensenShannonDivergenceDistance, KolmogorovSmirnovDistance, Kulczynski1Similarity, KullbackLeiblerDivergenceAsymmetricDistance, KullbackLeiblerDivergenceReverseAsymmetricDistance, LatLngDistance, LCSSDistance, LngLatDistance, LPIntegerNormDistance, LPNormDistance, MahalanobisDistance, ManhattanDistance, MatrixWeightedQuadraticDistance, MaximumDistance, MinimumDistance, MultiLPNorm, OnedimensionalDistance, PearsonCorrelationDistance, RGBHistogramQuadraticDistance, SqrtCosineDistance, SqrtCosineUnitlengthDistance, SqrtJensenShannonDivergenceDistance, SquaredEuclideanDistance, SquaredPearsonCorrelationDistance, SquaredUncenteredCorrelationDistance, SubspaceEuclideanDistance, SubspaceLPNormDistance, SubspaceManhattanDistance, SubspaceMaximumDistance, TriangularDiscriminationDistance, TriangularDistance, TutorialDistance, UncenteredCorrelationDistance, WeightedCanberraDistance, WeightedEuclideanDistance, WeightedLPNormDistance, WeightedManhattanDistance, WeightedMaximumDistance, WeightedPearsonCorrelationDistance, WeightedSquaredEuclideanDistance, WeightedSquaredPearsonCorrelationDistance

public interface NumberVectorDistance<O>
extends PrimitiveDistance<O>

Base interface for the common case of distance functions defined on numerical vectors.

Since:

0.5.0

Author:

Erich Schubert

Method Summary

Modifier and Type	Method	Description
double	distance(NumberVector o1, NumberVector o2)	Computes the distance between two given vectors according to this distance function.

Methods inherited from interface elki.distance.Distance

isMetric, isSquared, isSymmetric

Methods inherited from interface elki.distance.PrimitiveDistance

distance, getInputTypeRestriction, instantiate

Method Detail

distance

double distance(NumberVector o1,
                NumberVector o2)

Computes the distance between two given vectors according to this distance function.

Parameters:

o1 - first vector

o2 - second vector

Returns:

the distance between two given vectors according to this distance function