Title :
Parameter optimization in FCM clustering algorithms
Author :
Xinbo, Gao ; Jie, LI ; Weixin, Xie
Author_Institution :
Sch. of Electron. Eng., Xidian Univ., Xi´´an, China
Abstract :
Weighting exponent m is an important parameter in fuzzy c-means (FCM) clustering algorithm, which directly affects the performance of the algorithm and the validity of fuzzy cluster analysis. However, so far the optimal choice of m is still an open problem. A method of selecting the optimal m is proposed in this paper, which is based on the fuzzy decision theory. The experimental results obtained demonstrate its effectiveness and arrive a conclusion that the optimal range of m is [1.5, 2.5] in practical applications
Keywords :
decision theory; fuzzy set theory; optimisation; pattern clustering; fuzzy c-means clustering; fuzzy decision theory; parameter optimization; pattern recognition; weighting exponent; Algorithm design and analysis; Clustering algorithms; Decision theory; Entropy; Fuzzy control; Fuzzy set theory; Fuzzy sets; Partitioning algorithms; Pattern recognition; Performance analysis;
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
DOI :
10.1109/ICOSP.2000.893376
