Generalized Fuzzy c-Means Clustering and its Property of Fuzzy Classification Function
Generalized Fuzzy c-Means Clustering and its Property of Fuzzy Classification Function
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广义模糊c均值聚类及其模糊分类函数的性质
DOI：
10.20965/jaciii.2021.p0073
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
S. Miyamoto
中科院分区：
文献类型：
--
作者：
Y. Kanzawa;S. Miyamoto
这项研究表明，一个广义模糊c-均值（gFCM）聚类算法，它涵盖了标准和指数模糊c-均值聚类，可以构造，如果一个给定的模糊化函数，其导数，其逆导数可以计算。此外，我们的研究结果表明，gFCM的模糊分类功能表现出类似的行为，标准和指数模糊c-均值聚类。
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.