A note on how Rényi entropy can create a spectrum of probabilistic merging operators
Kybernetika, Tome 55 (2019) no. 4, pp. 605-617
Cet article a éte moissonné depuis la source Czech Digital Mathematics Library
In this paper we present a result that relates merging of closed convex sets of discrete probability functions respectively by the squared Euclidean distance and the Kullback-Leibler divergence, using an inspiration from the Rényi entropy. While selecting the probability function with the highest Shannon entropy appears to be a convincingly justified way of representing a closed convex set of probability functions, the discussion on how to represent several closed convex sets of probability functions is still ongoing. The presented result provides a perspective on this discussion. Furthermore, for those who prefer the standard minimisation based on the squared Euclidean distance, it provides a connection to a probabilistic merging operator based on the Kullback-Leibler divergence, which is closely connected to the Shannon entropy.
In this paper we present a result that relates merging of closed convex sets of discrete probability functions respectively by the squared Euclidean distance and the Kullback-Leibler divergence, using an inspiration from the Rényi entropy. While selecting the probability function with the highest Shannon entropy appears to be a convincingly justified way of representing a closed convex set of probability functions, the discussion on how to represent several closed convex sets of probability functions is still ongoing. The presented result provides a perspective on this discussion. Furthermore, for those who prefer the standard minimisation based on the squared Euclidean distance, it provides a connection to a probabilistic merging operator based on the Kullback-Leibler divergence, which is closely connected to the Shannon entropy.
DOI :
10.14736/kyb-2019-4-0605
Classification :
52A99, 52C99
Keywords: probabilistic merging; information geometry; Kullback–Leibler divergence; Rényi entropy
Keywords: probabilistic merging; information geometry; Kullback–Leibler divergence; Rényi entropy
@article{10_14736_kyb_2019_4_0605,
author = {Adam\v{c}{\'\i}k, Martin},
title = {A note on how {R\'enyi} entropy can create a spectrum of probabilistic merging operators},
journal = {Kybernetika},
pages = {605--617},
year = {2019},
volume = {55},
number = {4},
doi = {10.14736/kyb-2019-4-0605},
mrnumber = {4043538},
zbl = {07177906},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.14736/kyb-2019-4-0605/}
}
TY - JOUR AU - Adamčík, Martin TI - A note on how Rényi entropy can create a spectrum of probabilistic merging operators JO - Kybernetika PY - 2019 SP - 605 EP - 617 VL - 55 IS - 4 UR - http://geodesic.mathdoc.fr/articles/10.14736/kyb-2019-4-0605/ DO - 10.14736/kyb-2019-4-0605 LA - en ID - 10_14736_kyb_2019_4_0605 ER -
Adamčík, Martin. A note on how Rényi entropy can create a spectrum of probabilistic merging operators. Kybernetika, Tome 55 (2019) no. 4, pp. 605-617. doi: 10.14736/kyb-2019-4-0605
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