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LabCor: Multi-label classification using a label correction strategy

  • Published:2021-08-12 Issue: Volume: Page:
  • ISSN:0924-669X
  • Container-title:Applied Intelligence
  • language:en
  • Short-container-title:Appl Intell

Author:

Wu Chengkai,Zhou Tianshu,Wu Junya,Tian Yu,Li Jingsong

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Major Scientific Project of Zhejiang Lab

fundamental research funds for the central universities

the youth innovation team project of the college of biomedical engineering & instrument science, zhejiang university

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference36 articles.

1. Alali A, Kubat M (2015) Prudent: a pruned and confident stacking approach for multi-label classification. IEEE Trans Knowl Data Eng 27(9):2480–2493

2. Boutell MR, Luo J, Shen X, Brown CM (2004) Learning multi-label scene classification. Pattern Recog 37(9):1757–1771

3. Demšar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach learn Res 7(Jan):1–30

4. Elisseeff A, Weston J (2002) A kernel method for multi-labelled classification. In: Advances in neural information processing systems, pp 681–687

5. Friedman M (1940) A comparison of alternative tests of significance for the problem of m rankings. Ann Math Stat 11(1):86–92

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