Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
Special Issue on Recent Progress in Nonlinear Theory and Its Applications
An equivalence between log-sum-exp approximation and entropy regularization in K-means clustering
Kohei InoueKenji Hara
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JOURNAL FREE ACCESS

2020 Volume 11 Issue 4 Pages 446-453

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Abstract

In this paper, we show an equivalence between log-sum-exp approximation and entropy regularization in K-means clustering, which is a well-known algorithm for partitional clustering. We derive an identical equation for updating centroids of clusters from the two formulations. Additionally, we derive an alternative equation suitable for another formulation of entropy regularization, maximum entropy method. We also show experimental results which support the theoretical results.

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© 2020 The Institute of Electronics, Information and Communication Engineers
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