Xiaoyan Hu

Hunan University, Ch’ang-sha-shih, Hunan, China

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Publications (1)1.27 Total impact

  • Source
    Shutao Li · Xixian Wu · Xiaoyan Hu
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we present a gene selection method based on genetic algorithm (GA) and support vector machines (SVM) for cancer classification. First, the Wilcoxon rank sum test is used to filter noisy and redundant genes in high dimensional microarray data. Then, the different highly informative genes subsets are selected by GA/SVM using different training sets. The final subset, consisting of highly discriminating genes, is obtained by analyzing the frequency of appearance of each gene in the different gene subsets. The proposed method is tested on three open datasets: leukemia, breast cancer, and colon cancer data. The results show that the proposed method has excellent selection and classification performance, especially for breast cancer data, which can yield 100% classification accuracy using only four genes.
    Full-text · Article · Feb 2008 · Soft Computing

Publication Stats

32 Citations
1.27 Total Impact Points

Top Journals


  • 2008
    • Hunan University
      • College of Electrical and Information Engineering
      Ch’ang-sha-shih, Hunan, China