Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
836-841

Three-way neighborhood attribute reduction algorithm based on test cost

Zhang Xinrui1
Wan Renxia1
Yue Xiaodong2
Chen Ruidian3
1. College of Mathematics & Information Science, North Minzu University, Yinchuan 750021, China
2. School of Computer Engineering & Science, Shanghai University, Shanghai 200444, China
3. Institute for Big Data in Health Fujian Hongyang Software Co. , Ltd. , Fuzhou 350002, China
DOI: 10.19734/j.issn.1001-3695.2023.06.0306

Abstract

In order to address the issue of test cost being rarely considered in rough set attribute reduction, this paper proposed a three-way neighborhood attribute reduction algorithm based on test cost. The proposed algorithm calculated the attri-bute importance according to the frequency and proportion of each attribute in the neighborhood resolution matrix, and combined the test cost of the attributes to construct the the cost performance index to guide the selection of attributes. Three-way decision-making method was employed to partition attribute sets, which provided data support for the attribute reduction process. Comparative experiments were conducted on seven UCI public datasets, which demonstrate that the proposed algorithm yields a smaller attribute reduction set compared to the comparison algorithm. Moreover, the proposed algorithm exhibited a shorter running time and lower test cost without compromising classification accuracy. Furthermore, it provided an application example based on fiscal revenue prediction to further validate the effectiveness and practicality of the proposed algorithm.

Foundation Support

国家自然科学基金资助项目(62066001,61662001)
宁夏自然科学基金资助项目(2021AAC03203)
中央高校基本科研业务费专项资金资助项目(FWNX04)
北方民族大学研究生创新项目(YCX22088)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.06.0306
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: Algorithm Research & Explore
Pages: 836-841
Serial Number: 1001-3695(2024)03-028-0836-06

Publish History

[2023-11-17] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

张欣蕊, 万仁霞, 岳晓冬, 等. 基于测试代价的三支邻域属性约简算法 [J]. 计算机应用研究, 2024, 41 (3): 836-841. (Zhang Xinrui, Wan Renxia, Yue Xiaodong, et al. Three-way neighborhood attribute reduction algorithm based on test cost [J]. Application Research of Computers, 2024, 41 (3): 836-841. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)