JACIII Vol.19 No.5 pp. 662-669
doi: 10.20965/jaciii.2015.p0662


A Maximizing Model of Bezdek-Like Spherical Fuzzy c-Means

Yuchi Kanzawa

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

January 31, 2015
June 16, 2015
Online released:
September 20, 2015
September 20, 2015
fuzzy c-means, spherical clustering

In this study, a maximizing model of Bezdek-like spherical fuzzy c-means clustering is proposed, which is based on the regularization of the maximizing model of spherical hard c-means. Such a maximizing model was unclear in Bezdek-like method, whereas other types of methods have been investigated well both in minimizing and maximizing model. Using theoretical analysis and numerical experiments, the classification rule of the proposed method is shown. Using numerical examples, the proposed method is shown to be valid for document clustering, because documents are represented as spherical data via term document-inverse document frequency weighting and normalization processing.

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Last updated on Mar. 22, 2017