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There exist two classical linear methods for feature extraction, i.e. principal component analysis (PCA) and Fisher discriminant analysis (FDA). PCA best represents the data while FDA best separates the data in the least squares sense with different scatter measures from samples. This paper discusses a regularized scatter measure (RSM) as a linear combination of within-class and between-class scatters...
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