I discuss the recommendations and cautions in article on the use of finite models to cluster a data set. In their article, much use is made of comparison with the -means procedure. As noted by researchers for over 30 years, the -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.
Commentary on
Abstract
I discuss the recommendations and cautions in article on the use of finite models to cluster a data set. In their article, much use is made of comparison with the -means procedure. As noted by researchers for over 30 years, the -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.Preview Only. This article cannot be rented because we do not currently have permission from the publisher.
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McLachlan, Geoffrey J.
Follow Psychological Methods
, Volume 16 (1): 80
PsycARTICLES® – Mar 1, 2011
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