smile.math.distance

Class JensenShannonDistance

java.lang.Object

smile.math.distance.JensenShannonDistance

All Implemented Interfaces:

java.io.Serializable, Distance<double[]>, Metric<double[]>

public class JensenShannonDistance
extends java.lang.Object
implements Metric<double[]>, java.io.Serializable

The Jensen-Shannon divergence is a popular method of measuring the similarity between two probability distributions. It is also known as information radius or total divergence to the average.

The Jensen-Shannon divergence is a symmetrized and smoothed version of the Kullback-Leibler divergence . It is defined by

J(P||Q) = (D(P||M) + D(Q||M)) / 2

where M = (P+Q)/2 and D(·||·) is KL divergence. Different from the Kullback-Leibler divergence, it is always a finite value.

The square root of the Jensen-Shannon divergence is a metric, which is calculated by this class.

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
double	d(double[] x, double[] y) Returns the distance measure between two objects.
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Method Detail

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

d

public double d(double[] x,
                double[] y)

Description copied from interface: Distance

Returns the distance measure between two objects.

Specified by:

d in interface Distance<double[]>