Relational and median variants of Possibilistic Fuzzy C-Means

Abstract

In this article we propose a relational and a median possibilistic clustering method. Both methods are modifications of Possibilistic Fuzzy C-Means as introduced by Pal et al. [1]. The proposed algorithms are applicable for abstract non-vectorial data objects where only the dissimilarities of the objects are known. For the relational version we assume a Euclidean data embedding. For data where this assumption is not feasible we introduce a median variant restricting prototypes to be data objects themselves.