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作者:

Li, Jiangeng (Li, Jiangeng.) | Li, Hui (Li, Hui.) | Ruan, Xiaogang (Ruan, Xiaogang.)

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摘要:

A novel selection method (PLS_VIP_CFFS) was presented, which combines partial least squares variable importance in projection with heuristic forward search (PLS_VIP_CFFS). To prove the advantage of PLS_VIP_CFFS, it was applied to the selection of feature genes using lung cancer, colon cancer, gastric cancer and leukemia data sets. Then, the feature genes were used in classifiers, such as SVM and CLUSTER. The specificity sensibility and balance accuracy of the classifiers and the major biological function of the feature genes were provided. The results show that PLS_VIP_CFFS is a reliable selection technique.

关键词:

Diseases Feature extraction Genes Heuristic methods Least squares approximations Support vector machines

作者机构:

  • [ 1 ] [Li, Jiangeng]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Li, Hui]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Ruan, Xiaogang]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

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来源 :

Journal of Central South University (Science and Technology)

ISSN: 1672-7207

年份: 2013

期: SUPPL.2

卷: 44

页码: 284-288

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