New Inter-Cluster Proximity Index for Fuzzy c-Means Clustering

Abstract

This letter presents a new inter-cluster proximity index for fuzzy partitions obtained from the fuzzy c-means algorithm. It is defined as the average proximity of all possible pairs of clusters. The proximity of each pair of clusters is determined by the overlap and the separation of the two clusters. The former is quantified by using concepts of Fuzzy Rough sets theory and the latter by computing the distance between cluster centroids. Experimental results indicate the efficiency of the proposed index.