Survey
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 12
3534-3545

Survey of multi-class imbalanced data classification methods

Li Ang
Han Meng
Mu Dongliang
Gao Zhihui
Liu Shujuan
School of Computer Science & Engineering, North Minzu University, Yinchuan 750021, China
DOI: 10.19734/j.issn.1001-3695.2022.03.0198

Abstract

In reality, the data generated in many fields usually have multiple classes and are imbalanced. In multi-class imbalance classification, problems such as class overlap, noise and multiple minority classes reduce the capability of classifiers, and effective solution of multi-class imbalance problem has become an important research topic in the field of machine learning and data mining. Based on the recent literature on multi-class imbalance classification methods, this paper analyzed and summarized both data preprocessing and algorithm-level classification methods, and conducted a detailed analysis of all algorithms in terms of advantages, disadvantages and data sets. The data preprocessing methods introduced oversampling, undersampling, hybrid sampling and feature selection methods to compare the performance of the algorithms using the same datasets. In addition, the algorithm-level classification methods described and analyzed base classifier optimization, ensemble learning and multi-class decomposition techniques. Finally, this paper summarized the future development directions of the multi-class imbalanced data classification research field.

Foundation Support

国家自然科学基金资助项目(62062004)
宁夏自然科学基金资助项目(2020AAC03216,2022AAC03279)
北方民族大学研究生创新项目(YCX22191)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.03.0198
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 12
Section: Survey
Pages: 3534-3545
Serial Number: 1001-3695(2022)12-002-3534-12

Publish History

[2022-07-08] Accepted Paper
[2022-12-05] Printed Article

Cite This Article

李昂, 韩萌, 穆栋梁, 等. 多类不平衡数据分类方法综述 [J]. 计算机应用研究, 2022, 39 (12): 3534-3545. (Li Ang, Han Meng, Mu Dongliang, et al. Survey of multi-class imbalanced data classification methods [J]. Application Research of Computers, 2022, 39 (12): 3534-3545. )

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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