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Model-based mixture discriminant analysis - an experimental study

delete2005-03-01
delete12
PRE
AI
Z
Zohar Halbe
M
Mayer Aladjem
DOI：10.1016/j.patcog.2004.08.010delete
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Abstract

Abstract

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.
Keywords:
discriminant analysis
Gaussian mixture model
density estimation
model selection
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Pattern Recognition cover
Pattern Recognition
IF:
7.6
Papers:
1.3W
Citations:
4.5W

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