Genetic algorithm approach to cluster analysis

Abstract

In this paper, performance of Genetic Algorithm based clustering method has been compared with conventional clustering methods that are K-means and Ward’s clustering methods. The cluster quality has been compared using three cluster validity indices that are Calinski-Harabasz, Dunn and Average Silhouette Width. The results showed that genetic algorithm based clustering method performed better than other clustering methods under all the three cluster validity measures.