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Laplacian linear discriminant analysis (LapLDA) and semi-supervised discriminant analysis (SDA) are two recently proposed LDA methods. They are developed independently with the aim to improve LDA by introducing a locality preserving regularization term, and they have proved their effectiveness experimentally on some benchmark datasets. However, both algorithms ignored comparison with much simpler...
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