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Label enhancement with label-specific feature learning

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Abstract

Label distribution learning (LDL) is a novel machine learning paradigm. It addresses the problem of label ambiguity by emphasizing the relevance of each label to a particular instance. Unlike the simple logic vectors in single label learning (SLL) and multi-label learning (MLL), LDL assigns descriptive labels to each instance. Since it is often difficult to collect training sets with precise labels, label enhancement (LE) can be used to recover label distributions from logical labels. Most existing LE models construct label distributions based on a mapping from the feature space to the label space and include two main assumptions: (1) the relationship between features and labels is linear, and (2) all features are shared by all labels. However, in reality, the relationship between features and labels is not purely linear, and different labels may be determined by different features. To solve this problem, in this paper, we propose a new algorithm, that first maps features to a high-dimensional space to explore the nonlinear mapping relationship between features and labels, and then takes full advantage of the labels’ properties determined by specific features, while considering the correlation between labels. The experimental comparison with the existing algorithms verifies the effectiveness of the algorithm proposed in this paper.

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (Grant Nos. 61906090, 62176123).

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Authors and Affiliations

  1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Weiwei Li, Jin Chen & Peixue Gao

  2. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Weiwei Li & Zhiqiu Huang

  3. Ministry Key Laboratory for Safety-Critical Software Development and Verification, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Weiwei Li & Zhiqiu Huang

Authors
  1. Weiwei Li
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  2. Jin Chen
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  3. Peixue Gao
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  4. Zhiqiu Huang
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Correspondence to Weiwei Li.

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Li, W., Chen, J., Gao, P. et al. Label enhancement with label-specific feature learning. Int. J. Mach. Learn. & Cyber. 13, 2857–2867 (2022). https://doi.org/10.1007/s13042-022-01567-x

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