A combination scheme for fuzzy clustering

Abstract

In this paper we present a voting scheme for cluster algorithms. This voting method allows us to combine several runs of cluster algorithms resulting in a common partition. This helps us to tackle the problem of choosing the appropriate clustering method for a data set where we have no a priori information about it, and to overcome the problems of choosing an optimal result between different repetitions of the same method. Further on, we can improve the ability of a cluster algorithm to find structures in a data set and to validate the resulting partition.