Parameter optimization in FCM clustering algorithms

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.