A Validity Index for Fuzzy and Possibilistic C-means Algorithm
Chunhui Zhang, Yiming Zhou, Trevor Martin · 2008
This paper proposes a novel valid-ity index for fuzzy-possibilistic c-means(FPCM) algorithm, it com-bines extended partition entropy and inter class similarity which is cal-culated from the fuzzy set point of view. The proposed index only re-quires the membership matrix and possibilistic(typicality) matrix, and is free from heavy distance comput-ing. We also extend Xie-Beni index and Kwon index to evaluate FPCM. Experiments are done to compare the three indices and the results show its effectiveness.