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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 12
3566-3571,3577

Classification design method of unbalanced data sets considering unbalanced index

Zhou Yu
Yue Xuezhen
Sun Hongyu
School of Electrical Engineering, North China University of Water Resources & Electric Power, Zhengzhou 450011, China
DOI: 10.19734/j.issn.1001-3695.2023.04.0163

Abstract

The imbalance of data sets category is one of the important problems in the classification field. The unbalanced index of each data set is closely related to itself, it is a key indicator of data sets. To deal with the classification design of unbalanced data sets, this paper proposed an enhanced AdaBoost(E-AdaBoost) algorithm. In the process of iteration, the algorithm took into account unbalanced index, and the classification accuracy of the minority classed that was more important in unbalanced data sets improving the weight updating strategy of the base classifier, and thus promoting the classification performance of unbalanced data sets. The classification design method of unbalanced data sets based on E-AdaBoost could determine the weight parameters of the base classifier according to the sample unbalanced index, so as to improve the performance of the classifier. With this method that was combined with multiple classical classifiers, this paper carried out experimental analysis in terms of artificial data sets and standard data sets, and compared with relevant methods. The results show that the classification design method of unbalanced data sets based on E-AdaBoost can effectively improve the classification performance of unbalanced data sets.

Foundation Support

国家自然科学基金资助项目(U1504622,31671580)
河南省高等学校青年骨干教师培养计划项目(2018GGJS079)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.04.0163
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 12
Section: Algorithm Research & Explore
Pages: 3566-3571,3577
Serial Number: 1001-3695(2023)12-007-3566-06

Publish History

[2023-07-10] Accepted Paper
[2023-12-05] Printed Article

Cite This Article

周玉, 岳学震, 孙红玉. 考虑不平衡指数的不平衡数据集分类设计方法 [J]. 计算机应用研究, 2023, 40 (12): 3566-3571,3577. (Zhou Yu, Yue Xuezhen, Sun Hongyu. Classification design method of unbalanced data sets considering unbalanced index [J]. Application Research of Computers, 2023, 40 (12): 3566-3571,3577. )

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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