DocumentCode :
950620
Title :
Improved possibilistic C-means clustering algorithms
Author :
Zhang, Jiang-She ; Leung, Yiu-Wing
Author_Institution :
Dept. of Inf. Sci., Xi´´an Jiaotong Univ., China
Volume :
12
Issue :
2
fYear :
2004
fDate :
4/1/2004 12:00:00 AM
Firstpage :
209
Lastpage :
217
Abstract :
A possibilistic approach was proposed in a previous paper for C-means clustering, and two algorithms realizing this approach were reported in two previous papers. Although the possibilistic approach is sound, these two algorithms tend to find identical clusters. In this paper, we modify and improve these algorithms to overcome their shortcoming. The numerical results demonstrate that the improved algorithms can determine proper clusters and they can realize the advantages of the possibilistic approach.
Keywords :
pattern clustering; possibility theory; C-means clustering; possibilistic approach; Acoustic noise; Clustering algorithms; Computer science; Information science; Partitioning algorithms; Prototypes; Research and development; Robustness;
fLanguage :
English
Journal_Title :
Fuzzy Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6706
Type :
jour
DOI :
10.1109/TFUZZ.2004.825079
Filename :
1284323
Link To Document :
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