© 1977 by British Computer Society
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Hierarchical grouping methods and stopping rules: an evaluation*
Department of Management Science, University of Rhode Island, Kingston, Rhode Island, USA
Hierarchical clustering procedures have received a great deal of emphasis in recent years, yet research has lagged in their empirical evaluation and in objective means to aid the user in selecting good partitions (rather than good hierarchies). The present paper aims to correct both of these deficiencies, first by empirically testing selected methods which have become popular and, second by proposing and evaluating statistical stopping rules. Results indicate: 1. that methods vary widely in their performance and 2. that the proposed stopping rules can aid the user in selecting partitions.
Received February 1975.
* Partially funded by a Grant-in-Aid from the University Research Committee of the University of Rhode Island. The author appreciates the efforts of the referee in providing helpful comments for the revision of the original draft.
Department of Management Science, University of Rhode Island, Kingston, Rhode Island 02881, USA
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