$\ell_{1}$ -Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS(2019)
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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