Optimality of reassignment rules in dynamic clustering

摘要

The paper is concerned with reassignment rules for the dynamic clustering algorithm family which includes ISODATA. It is shown that contrary to popular belief these iterative clustering algorithms do not guarantee that each stable partition is locally optimal. The main result derived herein is a multiple-point reassignment rule which assumes a Gaussian density model for each cluster. The new rule should reduce the chances of the iterative optimisation algorithm yielding partitions which do not correspond to local minima of the clustering criterion.