$\ell_{1}$ -Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS(2019)

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摘要
Fisher's criterion is one of the most popular discriminant criteria for feature extraction. It is defined as the generalized Rayleigh quotient of the between-class scatter distance to the within-class scatter distance. Consequently, Fisher's criterion does not take advantage of the discriminant information in the class covariance differences, and hence, its discriminant ability largely depends on ...
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关键词
Feature extraction,Covariance matrices,Learning systems,Gaussian distribution,Image color analysis,Data mining,Upper bound
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