Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
389339 | Fuzzy Sets and Systems | 2016 | 16 Pages |
Abstract
The f-divergence evaluates the dissimilarity between two probability distributions defined in terms of the Radon–Nikodym derivative of these two probabilities. The f-divergence generalizes the Hellinger distance and the Kullback–Leibler divergence among other divergence functions. In this paper we define an analogous function for non-additive measures. We discuss them for distorted Lebesgue measures and give examples. Examples focus on the Hellinger distance.
Keywords
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Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Vicenç Torra, Yasuo Narukawa, Michio Sugeno,