Fuzzy and possibilistic clustering algorithms based on generalized reformulation

This paper presents a new approach to fuzzy and possibilistic clustering based on reformulation. The reformulation of fuzzy c-means (FCM) algorithms provides the basis for reformulating entropy constrained fuzzy clustering (ECFC) algorithms. This paper also proposes a generalized reformulation function and interprets both FCM and ECFC algorithms as special cases of the broad family of fuzzy and possibilistic clustering algorithms resulting from this approach. New clustering algorithms are also developed and compared experimentally with FCM and ECFC algorithms