USE OF RADIUS WEIGHTED MEAN TO CLUSTER 2-CLASS DATA

Abstract

A new method using the radius weighted mean to cluster two-class data is proposed. Experiments show that the clustering results are good, the computation is fast, and the method is easy to implement. The method can be applied to block truncation coding, codebook generation, and decision tree construction.