Paper:

# Generalized Fuzzy *c*-Means Clustering and its Property of Fuzzy Classification Function

*c*

## Yuchi Kanzawa^{*} and Sadaaki Miyamoto^{**}

^{*}Shibaura Institute of Technology

3-7-5 Toyosu, Koto, Tokyo 135-8548, Japan

^{**}University of Tsukuba

1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

*c*-means clustering, fuzzy classification function

This study shows that a generalized fuzzy *c*-means (gFCM) clustering algorithm, which covers both standard and exponential fuzzy *c*-means clustering, can be constructed if a given fuzzified function, its derivative, and its inverse derivative can be calculated. Furthermore, our results show that the fuzzy classification function for gFCM exhibits a behavior similar to that of both standard and exponential fuzzy *c*-means clustering.

**-Means Clustering and its Property of Fuzzy Classification Function,”**

*c**J. Adv. Comput. Intell. Intell. Inform.*, Vol.25 No.1, pp. 73-82, 2021.

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