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Gene Selection Algorithm By Combining Relieff And Mrmr, Yi Zhang, Chris Ding, Tao Li
Gene Selection Algorithm By Combining Relieff And Mrmr, Yi Zhang, Chris Ding, Tao Li
School of Computing and Information Sciences
Background: Gene expression data usually contains a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best discriminate biological samples of different types. In this paper, we present a two-stage selection algorithm by combining ReliefF and mRMR: In the first stage, ReliefF is applied to find a candidate gene set; In the second stage, mRMR method is applied to directly and explicitly reduce redundancy for selecting a compact yet effective gene subset from the candidate set. Results: We perform comprehensive experiments to compare the mRMR-ReliefF …