DocumentCode :
226694
Title :
A maximizing model of Bezdek-like spherical fuzzy c-means clustering
Author :
Kanzawa, Yuchi
Author_Institution :
Dept. of Commun. Eng., Shibaura Inst. of Technol., Tokyo, Japan
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
2482
Lastpage :
2488
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2014.6891670
Filename :
6891670
Link To Document :
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