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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 4
1030-1036

Multi-label classification algorithm based on bidirectional mapping learning

Wang Qingpeng
Gao Qingwei
Lu Yixiang
Sun Dong
School of Electrical Engineering & Automation, Anhui University, Hefei 230601, China
DOI: 10.19734/j.issn.1001-3695.2021.10.0406

Abstract

The existing multi-label learning algorithms tend to focus on the forward projection from the instance space to the label space, and the problem of the loss of instance space information due to the reduction of the feature dimension during forward projection is often ignored. Hence, this paper proposed a multi-label classification algorithm with bidirectional mapping learning. Firstly, the method used the forward mapping loss from instance space to label space to established a linear multi-label classification model. Secondly, the bidirectional mapping model based on reconstruction loss regularization compensated for the discriminatory information loss in the forward mapping process. Finally, the bidirectional mapping model combined label correlation and instance correlation to fully exploit the potential relationship between labels and instances, and improved the ability of the model to handle nonlinear data through nonlinear kernel mapping. The experimental results show that compared with several other methods in recent years, the average performance improvements of the method in terms of Hamming loss, one error and ranking loss are 17.68%, 17.01% and 18.57%. Average performance improvement of 12.37% on six evaluation metrics, which verifies the effectiveness of the proposed method.

Foundation Support

国家自然科学基金资助项目(62071001)
安徽省自然科学基金资助项目(2008085MF183)
安徽省教育厅重点项目(KJ2018A0012)
安徽大学博士研究基金资助项目(J01003266)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.10.0406
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 4
Section: Algorithm Research & Explore
Pages: 1030-1036
Serial Number: 1001-3695(2022)04-012-1030-07

Publish History

[2021-12-08] Accepted Paper
[2022-04-05] Printed Article

Cite This Article

王庆鹏, 高清维, 卢一相, 等. 基于双向映射学习的多标签分类算法 [J]. 计算机应用研究, 2022, 39 (4): 1030-1036. (Wang Qingpeng, Gao Qingwei, Lu Yixiang, et al. Multi-label classification algorithm based on bidirectional mapping learning [J]. Application Research of Computers, 2022, 39 (4): 1030-1036. )

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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