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Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables

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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, SYNthesizedCLUStering) for dealing with these two problems.

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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.

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DeSarbo, W.S., Carroll, J.D., Clark, L.A. et al. Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables. Psychometrika 49, 57–78 (1984).

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