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A Monte Carlo Study of Thirty Internal Criterion Measures for Cluster Analysis

Published online by Cambridge University Press:  01 January 2025

Glenn W. Milligan
Glenn W. Milligan*
Affiliation:
The Ohio State University
*
Requests for reprints should be sent to Glenn W. Milligan, Faculty of Management Sciences, 356 Hagerty Hall, The Ohio State University, Columbus, Ohio 43210.
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Abstract

A Monte Carlo evaluation of thirty internal criterion measures for cluster analysis was conducted. Artificial data sets were constructed with clusters which exhibited the properties of internal cohesion and external isolation. The data sets were analyzed by four hierarchical clustering methods. The resulting values of the internal criteria were compared with two external criterion indices which determined the degree of recovery of correct cluster structure by the algorithms. The results indicated that a subset of internal criterion measures could be identified which appear to be valid indices of correct cluster recovery. Indices from this subset could form the basis of a permutation test for the existence of cluster structure or a clustering algorithm.

Keywords

classificationnumerical taxonomypermutation tests
Type
Original Paper
Information
Psychometrika , Volume 46 , Issue 2 , June 1981 , pp. 187 - 199
Copyright
Copyright © 1981 The Psychometric Society

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References

Reference Notes

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