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Psychol Methods. 2011 Mar;16(1):80-1; discussion 89-92. doi: 10.1037/a0021141.

Commentary on Steinley and Brusco (2011): recommendations and cautions.

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  • 1Department of Mathematics and Institute for Molecular Bioscience, University of Queensland, St. Lucia, Brisbane 4072, Queensland, Australia. g.mclachlan@uq.edu.au

Abstract

I discuss the recommendations and cautions in Steinley and Brusco's (2011) article on the use of finite models to cluster a data set. In their article, much use is made of comparison with the K-means procedure. As noted by researchers for over 30 years, the K-means procedure can be viewed as a special case of finite mixture modeling in which the components are in equal (fixed) proportions and are taken to be normal with a common spherical covariance matrix. In this commentary, I pay particular attention to this link and to the use of normal mixture models with arbitrary component-covariance matrices.

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PMID:
21381818
[PubMed - indexed for MEDLINE]
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