A Study of Reducing Calculation Cost in Possibilistic Clustering

Abstract

Possibilistic clustering method identify the membership function without probabilistic constraint. Because each cluster is independent, the cluster center will converge to the same point when initial points are close to each other. Therefore, completeness of cluster is assured by assuming all data the center of cluster in possibilistic clustering. But, in this algorithm, processing time increases in proportion to the number of the data. This paper shows a method to reduce a calculation cost with completeness of cluster.