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RBRL

This repository implements the RBRL method, proposed in our following paper:
Guoqiang Wu, Ruobing Zheng, Yingjie Tian and Dalian Liu. Joint Ranking SVM and Binary Relevance with Robust Low-Rank Learning for Multi-Label Classification. Neural Networks, 2020, 122: 24-39.

Run

run the demo.m in MATLAB, RBRL will run as its default parameters on sample datasets.

Contact

If you have any problem with the code, please do not hesitate to contact Guoqiang Wu (guoqiangwu90@gmail.com).

Cite

If you find this code is useful, please cite our paper:

@article{wu2020joint,
  title={Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification},
  author={Wu, Guoqiang and Zheng, Ruobing and Tian, Yingjie and Liu, Dalian},
  journal={Neural Networks},
  volume={122},
  pages={24--39},
  year={2020},
  publisher={Elsevier}
}

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