Regularized Fuzzy c-Means Clustering and its Behavior at Point of Infinity

Regularized Fuzzy c-Means Clustering and its Behavior at Point of Infinity
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正则化模糊 c 均值聚类及其在无穷远点的行为

DOI:
10.20965/jaciii.2019.p0485
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发表时间:
2019
期刊:
J. Adv. Comput. Intell. Intell. Informatics
影响因子:
--
通讯作者:
S. Miyamoto
S. Miyamoto
中科院分区:
--
文献类型:
--
作者:
Y. Kanzawa;S. Miyamoto

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研究表明,如果给定的正则化函数值、其导函数值和逆导函数值能够被计算出来,则可以构造一个通用的正则化模糊c-均值(RFCM)聚类算法,包括一些传统的聚类算法。此外,研究结果表明,rFCM的模糊分类函数在无穷远点处的行为类似于一些传统的聚类算法。
This study shows that a general regularized fuzzy c-means (rFCM) clustering algorithm, including some conventional clustering algorithms, can be constructed if a given regularizer function value, its derivative function value, and its inverse derivative function value can be calculated. Furthermore, the results of the study show that the behavior of the fuzzy classification function for rFCM at an infinity point is similar to that for some conventional clustering algorithms.
DOI: 10.1002/int.20263
发表时间: 2008-02
影响因子: 7
作者:
Kiyotaka Mizutani;R. Inokuchi;S. Miyamoto
通讯作者: Kiyotaka Mizutani;R. Inokuchi;S. Miyamoto