Feature Selection For Genomic Data By Combining Filter And Wrapper Approaches

  • A BDELJALIL E L O UARDIGHI, D RISS A BOUTAJDINE
  • Published 2009

Abstract

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 propose a two-stage selection algorithm for genomic data by combining MRMR (Minimum Redundancy Maximum… (More)

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