Abstract
A new technique for automatic clustering of multivariate data is proposed. In this approach a performance index for determining optimal clusters is introduced. This performance index is expressed in terms of the ratio of the minimum interset distance to maximum intraset distance. The optimal clusters are found when the performance index reaches a global maximum. If there are alternative groupings with equal number of clusters, the one with the largest performance index is chosen.
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Tou, J.T. Dynoc—A dynamic optimal cluster-seeking technique. International Journal of Computer and Information Sciences 8, 541–547 (1979). https://doi.org/10.1007/BF00995502
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DOI: https://doi.org/10.1007/BF00995502