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

Class JensenShannonDivergenceDistanceFunction

java.lang.Object

de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractVectorDoubleDistanceFunction

de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractSpatialDoubleDistanceFunction

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

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

All Implemented Interfaces:

DistanceFunction<NumberVector<?>,DoubleDistance>, NumberVectorDistanceFunction<DoubleDistance>, PrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>, PrimitiveDoubleDistanceFunction<NumberVector<?>>, SpatialPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>, SpatialPrimitiveDoubleDistanceFunction<NumberVector<?>>, Parameterizable

public class JensenShannonDivergenceDistanceFunction
extends JeffreyDivergenceDistanceFunction

Jensen-Shannon Divergence is essentially the same as Jeffrey divergence, only scaled by half.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	JensenShannonDivergenceDistanceFunction.Parameterizer Parameterization class, using the static instance.

Field Summary

Fields

Modifier and Type	Field and Description
static JensenShannonDivergenceDistanceFunction	STATIC Static instance.

Constructor Summary

Constructors

Constructor and Description
JensenShannonDivergenceDistanceFunction() Deprecated. Use static instance!

Method Summary

Methods

Modifier and Type	Method and Description
double	doubleDistance(NumberVector<?> v1, NumberVector<?> v2) Computes the distance between two given Objects according to this distance function.
String	toString()

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.JeffreyDivergenceDistanceFunction

doubleMinDist, equals

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractSpatialDoubleDistanceFunction

instantiate, minDist

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractVectorDoubleDistanceFunction

dimensionality, dimensionality, dimensionality, dimensionality, distance, getDistanceFactory, getInputTypeRestriction

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPrimitiveDistanceFunction

isMetric, isSymmetric

Methods inherited from class java.lang.Object

clone, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.distancefunction.PrimitiveDistanceFunction

distance, getInputTypeRestriction

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction

getDistanceFactory, isMetric, isSymmetric

Field Detail

STATIC

public static final JensenShannonDivergenceDistanceFunction STATIC

Static instance. Use this!

Constructor Detail

JensenShannonDivergenceDistanceFunction

@Deprecated
public JensenShannonDivergenceDistanceFunction()

Deprecated. Use static instance!

Constructor for the Jensen-Shannon divergence.

Method Detail

doubleDistance

public double doubleDistance(NumberVector<?> v1,
                    NumberVector<?> v2)

Description copied from interface: PrimitiveDoubleDistanceFunction

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

Specified by:

doubleDistance in interface PrimitiveDoubleDistanceFunction<NumberVector<?>>

Overrides:

doubleDistance in class JeffreyDivergenceDistanceFunction

Parameters:

v1 - first Object

v2 - second Object

Returns:

the distance between two given Objects according to this distance function

toString

public String toString()

Overrides:

toString in class JeffreyDivergenceDistanceFunction