Model-based mixture discriminant analysis - an experimental study

doi:10.1016/j.patcog.2004.08.010

2005-03-01

PRE

Zohar Halbe

Mayer Aladjem

DOI：10.1016/j.patcog.2004.08.010

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摘要

En 中文

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. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Keyword:

discriminant analysis

Gaussian mixture model

density estimation

model selection