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JACIII Vol.26 No.6 pp. 884-892
doi: 10.20965/jaciii.2022.p0884
(2022)

Paper:

Generalization of Tsallis Entropy-Based Fuzzy c-Means Clustering and its Behavior at the Infinity Point

Yuchi Kanzawa* and Sadaaki Miyamoto**

*Shibaura Institute of Technology
3-7-5 Toyosu, Koto-ku, Tokyo 135-8548, Japan

**University of Tsukuba
1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

Received:
March 19, 2022
Accepted:
June 5, 2022
Published:
November 20, 2022
Keywords:
Tsallis entropy-based fuzzy c-means clustering, fuzzy classification function
Abstract
Generalization of Tsallis Entropy-Based Fuzzy <i>c</i>-Means Clustering and its Behavior at the Infinity Point

FCF example of GTFCM

This study presents a generalized Tsallis entropy-based fuzzy c-means (GTFCM) clustering algorithm. Furthermore, the results of this study show that the behavior of GTFCM, at an infinity point of the fuzzy classification function, is similar to that of some conventional clustering algorithms. This result implies that such behavior is determined by a certain part of the GTFCM objective function.

Cite this article as:
Y. Kanzawa and S. Miyamoto, “Generalization of Tsallis Entropy-Based Fuzzy c-Means Clustering and its Behavior at the Infinity Point,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.6, pp. 884-892, 2022.
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Last updated on Dec. 01, 2022