Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 3
702-704,709

WPLoss:weighted pairwise loss for class-imbalanced datasets

Yao Jiaqi
Xu Zhengguo
Yan Jikun
Wang Keren
National Key Laboratory of Science & Technology on Blind Signal Processing, Chengdu 610041, China
DOI: 10.19734/j.issn.1001-3695.2020.02.0041

Abstract

Class-imbalanced data refers to the large difference in the number of samples in different classes. AUC is an important metric to measure the performance of classifiers on the imbalanced datasets. Since AUC is not differentiable, researchers have proposed many surrogate pairwise loss functions to optimize AUC. The number of pairwise losses is the product of the number of positive and negative samples. Many positive and negative pairs with small pair loss affect the performance of classifiers. To solve this problem, this paper proposed a weighted pairwise loss function WPLoss. By assigning higher loss weights to the positive and negative samples with higher pairwise losses, WPLoss reduced the impact of positive and negative sample pairs with smaller pairwise losses. The experimental results on 20newsgroup and Reuters-21578 datasets verify the validity of WPLoss, indicating that WPLoss can improve the performance of the classifier for class-imbalanced data.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.02.0041
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 3
Section: Algorithm Research & Explore
Pages: 702-704,709
Serial Number: 1001-3695(2021)03-011-0702-03

Publish History

[2021-03-05] Printed Article

Cite This Article

姚佳奇, 徐正国, 燕继坤, 等. WPLoss:面向类别不平衡数据的加权成对损失 [J]. 计算机应用研究, 2021, 38 (3): 702-704,709. (Yao Jiaqi, Xu Zhengguo, Yan Jikun, et al. WPLoss:weighted pairwise loss for class-imbalanced datasets [J]. Application Research of Computers, 2021, 38 (3): 702-704,709. )

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)