Sequential Extraction of Clusters by Possibilistic Clustering Algorithm

Abstract

The present study discusses an algorithm that extracts clusters sequentially. An advantage of the proposed method is that the number of clusters need not be given beforehand. An algorithm for this method is described and compared with the mountain clustering that also extracts clusters sequentially. The present method is shown to perform better than the mountain clustering in higher dimensional spaces.