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Reconstructive discriminant analysis (RDA) is an effective dimensionality reduction method that can match well with linear regression classification (LRC). RDA seeks to find projections that can minimize the intra-class reconstruction scatter and simultaneously maximize the inter-class reconstruction scatter of samples. However, RDA needs to select the k heterogeneous nearest subspaces of each sample...
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