Model-based mixture discriminant analysis—an experimental study

The subject of this paper is an experimental study of a discriminant analysis (DA) based on Gaussian mixture estimation of the class-conditional densities. Five parameterizations of the covariance matrixes of the Gaussian components are studied. Recommendation for selection of the suitable parameter...

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Bibliographic Details
Published inPattern recognition Vol. 38; no. 3; pp. 437 - 440
Main Authors Halbe, Zohar, Aladjem, Mayer
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.03.2005
Subjects
Density estimation
Discriminant analysis
Gaussian mixture model
Model selection
Density estimation
Discriminant analysis
Model selection
Gaussian mixture model
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Summary:The subject of this paper is an experimental study of a discriminant analysis (DA) based on Gaussian mixture estimation of the class-conditional densities. Five parameterizations of the covariance matrixes of the Gaussian components are studied. Recommendation for selection of the suitable parameterization of the covariance matrixes is given.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2004.08.010