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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 2
488-492

Fast attribute reduction algorithm based on knowledge rough entropy

Wang Xiaoxue
Yin Feng
Yang Yawen
School of Computer Science & Engineering, Southwest Minzu University, Chengdu 610041, China
DOI: 10.19734/j.issn.1001-3695.2023.06.0258

Abstract

In order to address the problem of low algorithm efficiency caused by repeated calculation of the relative importance of attributes in the attribute reduction algorithm based on positive region, this paper proposed a fast attribute reduction algorithm based on knowledge rough entropy from the perspectives of attribute measurement and search strategy. Firstly, it introduced knowledge rough entropy into decision information systems by incorporating knowledge distance to measure the degree of knowledge roughness. Next, it employed knowledge rough entropy as the criterion for evaluating the significance of attributes, assessing the importance of individual attributes. Finally, it ranked all attributes based on attribute importance, and eliminated redundant attributes through dependency, so as to achieve rapid attribute reduction. The proposed algorithm was compared with other three algorithms in terms of running efficiency and classification accuracy on six publicly available datasets. The results demonstrate that the proposed algorithm improves running efficiency by 83.24%, 28.77%, and 59.92% respectively compared to other three algorithms. Among the three classifiers, the classification accuracy increases on average by 0.83%, 0.63%, and 1.37% respectively. Therefore, the proposed algorithm is able to achieve attribute reduction more quickly while ensuring classification performance.

Foundation Support

国家自然科学基金资助项目(61105061)
国家社会科学基金资助项目-重大招标项目(19ZDA284)
四川省科技资助项目-重点研发项目(2023YFN0026)
四川省教育信息技术研究资助项目(DSJ2022036)
成都市哲学社会科学规划资助项目(2022BS027)
西南民族大学中央高校基本科研业务费专项资金资助项目(2022SZL20)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.06.0258
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 2
Section: Algorithm Research & Explore
Pages: 488-492
Serial Number: 1001-3695(2024)02-025-0488-05

Publish History

[2023-08-21] Accepted Paper
[2024-02-05] Printed Article

Cite This Article

王小雪, 殷锋, 杨雅雯. 基于知识粗糙熵的快速属性约简算法 [J]. 计算机应用研究, 2024, 41 (2): 488-492. (Wang Xiaoxue, Yin Feng, Yang Yawen. Fast attribute reduction algorithm based on knowledge rough entropy [J]. Application Research of Computers, 2024, 41 (2): 488-492. )

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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