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Synthesized Clustering: A method for Amalgamating Alternative Clustering Bases with Differential Weighting of Variables

Published online by Cambridge University Press:  01 January 2025

Wayne S. DeSarbo*
Affiliation:
Bell Laboratories
J. Douglas Carroll
Affiliation:
Bell Laboratories
Linda A. Clark
Affiliation:
Bell Laboratories
Paul E. Green
Affiliation:
University of Pennsylvania
*
Requests for reprints should be sent to Wayne DeSarbo, Bell Laboratories, Room 2C-256, 600 Mountain Avenue, Murray Hill, New Jersey 07974.

Abstract

In the application of clustering methods to real world data sets, two problems frequently arise: (a) how can the various contributory variables in a specific battery be weighted so as to enhance some cluster structure that may be present, and (b) how can various alternative batteries be combined to produce a single clustering that “best” incorporates each contributory set. A new method is proposed (SYNCLUS, SYNthesized CLUStering) for dealing with these two problems.

Type
Original Paper
Copyright
Copyright © 1984 The Psychometric Society

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Footnotes

We wish to thank Anne Freeny and Deborah Art for their computer assistance, and Ed Fowlkes for his helpful technical discussion. We would also like to acknowledge the insightful and helpful comments from the editor and reviewers.

References

Reference Notes

DeSarbo, W. S. and Mahajan, V. (1982). Constrained classification, Working Paper, Murray Hill, N.J.: Bell Laboratories.Google Scholar
Fowlkes, E. (1981). Variable selection in clustering, presented at Bell Laboratories Work Seminar, Murray Hill, N.J.Google Scholar
Fowlkes, E., Gnanadesikan, R., and Kettenring, J. R. (1982). Variable selection in clustering, Work in Progress, Murray Hill, N.J.: Bell Laboratories.Google Scholar
Green, P. E. and Goldberg, S. M. (1981). The beta drug company case, Wharton-School Publication, University of Pennsylvania.Google Scholar

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