Abstract
It is crucial to evaluate the clustering quality in cluster analysis. In this paper, a new internal cluster validity index based on the cluster centre and the nearest neighbour cluster is designed according to the geometric distribution of objects. Moreover, a method for determining the optimal number of clusters is proposed. The new methodology can evaluate the clustering results produced by a certain clustering algorithm and determine the optimal number of clusters for a given dataset. Theoretical research and experimental results indicate the validity and good performance of the proposed index and method.
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