Package de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic

Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence.

See: Description

Class Summary

Class	Description
ChiSquaredDistanceFunction	Chi-Squared distance function, symmetric version.
ChiSquaredDistanceFunction.Parameterizer	Parameterization class, using the static instance.
HellingerDistanceFunction	Hellinger kernel / Hellinger distance are used with SIFT vectors, and also known as Bhattacharyya distance / coefficient.
HellingerDistanceFunction.Parameterizer	Parameterization class.
JeffreyDivergenceDistanceFunction	Jeffrey Divergence Distance for NumberVectors.
JeffreyDivergenceDistanceFunction.Parameterizer	Parameterization class, using the static instance.
JensenShannonDivergenceDistanceFunction	Jensen-Shannon Divergence is essentially the same as Jeffrey divergence, only scaled by half.
JensenShannonDivergenceDistanceFunction.Parameterizer	Parameterization class, using the static instance.
KullbackLeiblerDivergenceAsymmetricDistanceFunction	Kullback-Leibler (asymmetric!)
KullbackLeiblerDivergenceAsymmetricDistanceFunction.Parameterizer	Parameterization class, using the static instance.
KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction	Kullback-Leibler (asymmetric!)
KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction.Parameterizer	Parameterization class, using the static instance.
SqrtJensenShannonDivergenceDistanceFunction	The square root of Jensen-Shannon divergence is metric.
SqrtJensenShannonDivergenceDistanceFunction.Parameterizer	Parameterization class, using the static instance.

Package de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic Description

Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence.

Author:

Erich Schubert