Title :
A maximizing model of Bezdek-like spherical fuzzy c-means clustering
Author_Institution :
Dept. of Commun. Eng., Shibaura Inst. of Technol., Tokyo, Japan
Abstract :
In this study, a maximizing model of Bezdek-type spherical fuzzy c-means clustering is proposed, which is based on the regularization of the maximizing model of spherical hard c-means. Using theoretical analysis and numerical experiments, it is shown that the proposed method is not equivalent to the minimizing model of Bezdek-type spherical fuzzy c-means, because the effect of its fuzzifier parameter is different from that found in conventional methods.
Keywords :
fuzzy set theory; pattern clustering; Bezdek-like spherical fuzzy c-means clustering; fuzzifier parameter; maximizing model; spherical hard c-means; Algorithm design and analysis; Clustering algorithms; Entropy; Kernel; Linear programming; Optimization; Vectors;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
DOI :
10.1109/FUZZ-IEEE.2014.6891670