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In this paper we propose an effective and efficient random projection ensemble classifier with multiple empirical kernels. For the proposed classifier, we first randomly select a subset from the whole training set and use the subset to construct multiple kernel matrices with different kernels. Then through adopting the eigendecomposition of each kernel matrix, we explicitly map each sample into a...
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