INITIAL-CLUSTERS-SPECIFIED CLUSTER ANALYSIS

Abstract

An initial-clusters-specified method in cluster analysis is proposed. In usual clustering process, the individuals are treated equally or with weights. As against this, the clustering begins with some specific subsets which are treated like the individuals in the proposed method. The discussion has been focused on three hierarchical clustering methods: group average method, centroid method and Ward method. The efficiency of the proposed method is shown as compared with the other methods, ordinary and object-weighted. And also through the artificial numerical examples and a medical data for the aged, it is shown that the result of the proposed method is available for practical applications.