Rapid and brief communication: Model-based mixture discriminant analysis-an experimental study

Authors:
Zohar Halbe;Mayer Aladjem
Affiliations:
Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev P.O.Box 653, Beer-Sheva 84105, Israel;Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev P.O.Box 653, Beer-Sheva 84105, Israel
Venue:
Pattern Recognition
Year:
2005

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Abstract

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.