Jensen-Shannon Divergence

Question

I have another question that I was hoping someone could help me with.

I\'m using the Jensen-Shannon-Divergence to measure the similarity between two probability distribu

Answer 1

Note that the scipy entropy call below is the Kullback-Leibler divergence.

See: http://en.wikipedia.org/wiki/Jensen%E2%80%93Shannon_divergence

#!/usr/bin/env python
from scipy.stats import entropy
from numpy.linalg import norm
import numpy as np

def JSD(P, Q):
    _P = P / norm(P, ord=1)
    _Q = Q / norm(Q, ord=1)
    _M = 0.5 * (_P + _Q)
    return 0.5 * (entropy(_P, _M) + entropy(_Q, _M))

Also note that the test case in the Question looks erred?? The sum of the p distribution does not add to 1.0.

See: http://www.itl.nist.gov/div898/handbook/eda/section3/eda361.htm