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% Robust Multi-label Feature Selection with Missing Labels, Version 1.0
% Copyright(c) 2016 P. Zhu et al. 
% All Rights Reserved.
% 
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% It includes:
% 1 -- Matlab codes of our method and evaluation metrics.
% 2 -- Five datasets include Artificial, Birds, Reference, Social and Yeast under different missing labels.
% 
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% Permission to use, copy, or modify this software and its documentation
% for educational and research purposes only and without fee is here
% granted, provided that this copyright notice and the original authors'
% names appear on all copies and supporting documentation. This program
% shall not be used, rewritten, or adapted as the basis of a commercial
% software or hardware product without first obtaining permission of the
% authors. The authors make no representations about the suitability of
% this software for any purpose. It is provided "as is" without express
% or implied warranty.
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% 
% Please refer to the following paper
@article{zhu2018multi,
  title={Multi-label feature selection with missing labels},
  author={Zhu, Pengfei and Xu, Qian and Hu, Qinghua and Zhang, Changqing and Zhao, Hong},
  journal={Pattern Recognition},
  volume={74},
  pages={488--502},
  year={2018},
  publisher={Elsevier}
}
% 
% Contact: {zhupengfei,xuqian912}@tju.edu.cn
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