DocumentCode
496684
Title
Comparative study of EFCM algorithm
Author
Chengjia Li
Author_Institution
Institute of Operational Research & Cybernetics, Hangzhou Dianzi University, 310018, China
fYear
2006
fDate
6-9 Nov. 2006
Firstpage
1
Lastpage
4
Abstract
Clustering is a procedure through which objects are distinguished or classified in accordance with their similarity. A new clustering algorithm (EFCM) is proposed by extending the criterion function, which includes the well-known fuzzy c-means method as its special case. Convergence of EFCM algorithm is also proposed in this paper. Numerical experiments show that the new clustering algorithm is less sensitive than the traditional FCM method and robust to outliers.
Keywords
criterion function; fuzzy c-means; fuzzy clustering;
fLanguage
English
Publisher
iet
Conference_Titel
Wireless, Mobile and Multimedia Networks, 2006 IET International Conference on
Conference_Location
hangzhou, China
ISSN
0537-9989
Print_ISBN
0-86341-644-6
Type
conf
Filename
5195636
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