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Data-level methods of imbalanced data classification: status and research development

Su Yi
Li Xiaojun
Yao Junping
Zhou Zhijie
Liu Shuaitong
Rocket Force University of Engineering, Xi'an 710025, China

Abstract

In the classification of imbalanced data, in order to optimize the overall classification error, the standard classifiers may sacrifice the classification accuracy of the minority class. But more attention be paid to the accurate recognition of the minority class in practical applications. Due to the unique advantages of its high independence from classifiers, strong generalization capability and simplicity, the data-level methods have become more effective strategies to solve the problems of imbalanced data classification. Focusing on the data-level methods of imbalanced data classification, this paper firstly analysed the influencing factors that caused the imbalanced data classification problem. Then it assessed the relevant researches on resampling methods and feature selection methods which corresponding to sample space optimization and feature space optimization respectively, and horizontally compared these two data-level methods. Finally it put forward the issues that need to be focused on and proposed some possible research opportunities, so as to provide references for the algorithm research and applications of imbalanced data classification.

Foundation Support

陕西省杰出青年科学基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.05.0250
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 1
Section: Survey
Pages: 11-19
Serial Number: 1001-3695(2023)01-002-0011-09

Publish History

[2022-08-26] Accepted Paper
[2023-01-05] Printed Article

Cite This Article

苏逸, 李晓军, 姚俊萍, 等. 不平衡数据分类数据层面方法:现状及研究进展 [J]. 计算机应用研究, 2023, 40 (1): 11-19. (Su Yi, Li Xiaojun, Yao Junping, et al. Data-level methods of imbalanced data classification: status and research development [J]. Application Research of Computers, 2023, 40 (1): 11-19. )

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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