Subspace Semi-supervised Fisher Discrimi
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Wu-Yi YANG; Wei LIANG; Le XIN; Shu-Wu ZHANG
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Article
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2009
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Elsevier
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Fisher discriminant analysis (FDA) is a popular method for supervised dimensionality reduction. FDA seeks for an embedding transformation such that the ratio of the between-class scatter to the within-class scatter is maximized. Labeled data, however, often consume much time and are expensive to obt