Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 4
1118-1123,1131

Improved feature selection method combining discernibility matrix and ant colony optimization algorithm

Yang Zhenyu1
Ye Jun1,2
Ji Yuxuan1
Ao Jiaxin1
Wang Lei1,2
1. College of Information Engineering, Nanchang Institute of Technology, Nanchang 330000, China
2. Jiangxi Province Key Laboratory of Water Information Cooperative Sensing & Intelligent Processing, Nanchang 330000, China
DOI: 10.19734/j.issn.1001-3695.2021.08.0360

Abstract

At present, the existing feature selection methods based on ant colony algorithm optimization mostly use attribute dependence and information entropy attribute importance as the heuristic search factor on the path. However, this kind of search method has premature convergence in some decision tables or the searched feature subset contains redundant features, which leads to a significant decrease in selection accuracy. Aiming at such problems, this paper proposed an attribute importance measurement method based on the proportion of conditional attributes in the discernibility matrix. Taking the importance of the discernibility matrix as the heuristic factor on the path, this article designed a feature subset search method based on the discernibility matrix and ant colony algorithm optimization. The algorithm started from the feature core, and the ant colony selected features with high probability in turn to add to the feature core set, until the ant found the smallest feature subset. Validation of examples and experimental results of UCI data set show that compared with the feature selection method based on attribute dependence and information entropy attribute importance, under normal circumstances, this algorithm can find the smallest feature subset at a lower cost.

Foundation Support

江西省教育厅科技项目(GJJ211920,GJJ170995)
国家自然科学基金资助项目(61562061)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.08.0360
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 4
Section: Algorithm Research & Explore
Pages: 1118-1123,1131
Serial Number: 1001-3695(2022)04-027-1118-06

Publish History

[2021-11-29] Accepted Paper
[2022-04-05] Printed Article

Cite This Article

杨震宇, 叶军, 季雨瑄, 等. 结合分辨矩阵与蚁群优化算法改进的特征选择方法 [J]. 计算机应用研究, 2022, 39 (4): 1118-1123,1131. (Yang Zhenyu, Ye Jun, Ji Yuxuan, et al. Improved feature selection method combining discernibility matrix and ant colony optimization algorithm [J]. Application Research of Computers, 2022, 39 (4): 1118-1123,1131. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

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.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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