Title :
A possibilistic type of alternative fuzzy c-means
Author :
Yang, Minn-Shen ; Wu, Kuo-Lung
Author_Institution :
Dept. of Math., Chung Yuan Christian Univ., Chung-li, Taiwan
fDate :
6/24/1905 12:00:00 AM
Abstract :
The alternative fuzzy c-means (AFCM) clustering algorithm proposed by Wu and Yang (2001) has shown more robustness than the fuzzy c-means (FCM) on the basis of the robust statistic and the influence function. We propose a possibilistic type of AFCM by relaxing the restriction Σi=1c μi(x)=1 for all data points x. The resulting cluster memberships constitute a possibilistic partition which is different to a fuzzy partition from AFCM. The comparisons of the proposed method to FCM, AFCM and possibilistic c-means are made
Keywords :
fuzzy set theory; pattern clustering; possibility theory; cluster memberships; clustering algorithm; influence function; possibilistic alternative fuzzy c-means; possibilistic partition; robust statistic; Capacitive sensors; Clustering algorithms; Equations; Fuzzy sets; Mathematics; Partitioning algorithms; Phase change materials; Power generation; Robustness; Statistics;
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
DOI :
10.1109/FUZZ.2002.1006719
