Granular Correlation-based Label-specific Feature Augmentation for Multi-label Classification
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Published:2024-09
Issue:
Volume:
Page:121473
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ISSN:0020-0255
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Container-title:Information Sciences
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language:en
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Short-container-title:Information Sciences
Author:
Zhao TiannaORCID, Zhang YuanjianORCID, Miao DuoqianORCID
Reference50 articles.
1. X.Y. Che, D.G. Chen, J. Deng, et al. Exploiting local label correlation from sample perspective for multi-label classification via three-way decision theory, Applied Soft Computing, 2023, 149: 110950. 2. X.Y. Che, D.G. Chen, J.S. Mi, Feature distribution-based label correlation in multi-label classification, International Journal of Machine Learning and Cybernetics, 2021, 12: 1705-1719. 3. X.Y. Che, D.G. Chen, J.S. Mi, Learning instance-level label correlation distribution for multilabel classification with fuzzy rough sets, IEEE Transactions on Fuzzy Systems, 2023, 31(8): 2871-2884. 4. J.F. Chen, R.C. Zhang, J. Xu, et al. A neural expectation-maximization framework for noisy multi-label text classification, IEEE Transactions on Knowledge and Data Engineering, 2023, 35(11): 10992-11003. 5. J. Demsar, Statistical comparisons of classifiers over multiple data sets, Journal of Machine Learning Research, 2006, 7: 1-30.
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