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Considering the limit that marginal fisher analysis(MFA) can't take advantage of the discriminant information in the training samples, this paper proposed a semi-supervised dimensionality reduction based on kernel marginal fisher analysis and sparsity preserving. The new algorithm firstly gets the sparse reconstruction of the samples. Secondly it uses the samples with labels to construct the intra-class...
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