A Generalization of Linear Discriminant Analysis in Maximum Likelihood Framework
نویسندگان
چکیده
|The Fisher{Rao linear discriminant analysis (LDA) is a valuable tool for multi-class clas-siication and data reduction. We investigate LDA within the maximum likelihood framework and propose a general formulation to handle heteroscedastic-ity. Small size numerical experiments with randomly generated data verify the validity of our formulation.
منابع مشابه
On Generalizations of Linear Discriminant Analysis
Fisher{Rao Linear Discriminant Analysis (LDA), a valuable tool for multi-group classiication and data reduction, has been investigated in the maximum likelihood framework. It has been shown that the LDA solution is a special case from the more general class of solutions. Generalizations of the LDA formulation have been proposed to handle the case where the within class variances are unequal, an...
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