A possibilistic type of alternative fuzzy c-means
Miin‐Shen Yang, Kuo-Lung Wu · 2003
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 /spl Sigma//sub i=1//sup c/ /spl mu//sub i/(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.