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I'm beginner in probability and statistics. I came across the concept of comparing two probability distributions. KL-Divergence and Bhattacharya(Hellinger) Distance are used to compare two probability distributions. But which one is better among these two?

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  • $\begingroup$ Welcome to DataScienceSE. None of them is better than the other in general, they just correspond to different ways to calculate the distance. Usually it's a good idea to test both and see which one works better with the task. $\endgroup$
    – Erwan
    Aug 2 at 12:51

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