Algorithm Research & Explore
|
395-398

New APSO algorithm for gene selection combined with Relief-F and decision tree

Ye Chaochao
Pan Julong
College of Information Engineering, China Jiliang University, Hangzhou 310018, China

Abstract

Due to the characteristics of gene expression data in high dimension, high noise and small sample, gene selection had been one of the major challenges in tumor classification. In order to improve the accuracy of tumor classification and ensure the efficiency of gene selection, this paper developed a new algorithm R-C-APSO using an adaptive particle swarm optimization(APSO) combined with Relief-F and CART decision tree. The algorithm utilized Relief-F to quickly filter a large number of irrelevant genes and noises, narrowing the gene selection range. The R-C-APSO used the CART decision tree as a fitness function, and APSO algorithm performed the final search of the genes. Based on the analysis of 6 data sets, the experimental results show that R-C-APSO can obtain high classification accuracy and fast gene selection speed, and has good stability.

Foundation Support

国家自然科学基金资助项目(61272315)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.08.0872
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Algorithm Research & Explore
Pages: 395-398
Serial Number: 1001-3695(2019)02-018-0395-04

Publish History

[2019-02-05] Printed Article

Cite This Article

叶超超, 潘巨龙. 面向基因选择的结合Relief-F和决策树的APSO算法 [J]. 计算机应用研究, 2019, 36 (2): 395-398. (Ye Chaochao, Pan Julong. New APSO algorithm for gene selection combined with Relief-F and decision tree [J]. Application Research of Computers, 2019, 36 (2): 395-398. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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