A convex cluster merging algorithm using support vector machines

Abstract

In this paper, we propose a fast and reliable distance measure between two convex clusters using support vector machines (SVM). In doing so, the optimal hyperplane obtained by the SVM is used to calculate the minimal distance between the two clusters. As a result, an effective cluster merging algorithm that groups convex clusters resulted from the fuzzy convex clustering (FCC) method in is developed using this optimal distance. Hence, the number of clusters can be further reduced without losing its representation of the data. Several experimental results are given.