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

Wayne S. DeSarbo; J. Douglas Carroll; Linda A. Clark; Paul E. Green

doi:10.1007/BF02294206

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

Wayne S. DeSarbo
, J. Douglas Carroll
, Linda A. Clark
, Paul E. Green

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126 Scopus citations

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.

Original language	English (US)
Pages (from-to)	57-78
Number of pages	22
Journal	Psychometrika
Volume	49
Issue number	1
DOIs	https://doi.org/10.1007/BF02294206
State	Published - Mar 1984

All Science Journal Classification (ASJC) codes

General Psychology
Applied Mathematics

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10.1007/BF02294206

Cite this

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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.",

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AU - DeSarbo, Wayne S.

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AU - Clark, Linda A.

AU - Green, Paul E.

PY - 1984/3

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N2 - 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.

AB - 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.

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

Abstract

All Science Journal Classification (ASJC) codes

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