A novel clustering algorithm using voronoi diagram
Damodar Reddy Edla, Prasanta K. Jana · 2012
Clustering is an indispensable solution for many problems in a wide variety of domains. In this paper, we propose a new clustering algorithm which is based on Voronoi diagram. The algorithm uses a real valued function defined by the radii of Voronoi circles. This function enables to deal with the inner points of the clusters followed by the boundary points. The proposed scheme is applied on various artificial and biological data. The experimental results of the proposed method are also compared with K-means and a few existing clustering techniques. For the sake of evaluation of multi-dimensional data, we have used Normalized Information Gain (NIG). It is observed from the experimental results that the proposed method outperforms the existing methods.