A partitional clustering algorithm validated by a clustering tendency index based on graph theory

摘要

Applying graph theory to clustering, we propose a partitional clustering method and a clustering tendency index. No initial assumptions about the data set are requested by the method. The number of clusters and the partition that best fits the data set, are selected according to the optimal clustering tendency index value. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.