Description: The package includes the MATLAB code of the safe multi-label algorithm SAFEML which towards avoiding performance deterioration using weakly labeled data, or Learning safe multi-label prediction for weakly labeled data [1]. You will find an example of using this code in the 'example.m' function. The example data is yeast data set (Life area). In our MLJ'17 experiment, all the features and labels are normalized to [0,1] in advanced.
Reference:
[1] Tong Wei, Lan-Zhe Guo, Yu-Feng Li, Wei Gao. Learning safe multi-label prediction for weakly labeled data. Machine Learning, 2017.
ATTN: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Prof. Zhi-Hua Zhou (zhouzh@nju.edu.cn).
Requirement: The package was developed with MATLAB(v2008a).
ATTN2: This package was developed by Mr. Tong Wei (weit@lamda.nju.edu.cn), Mr. Lan-Zhe Guo (guolz@lamda.nju.edu.cn) and Dr. Yu-Feng Li (liyf@lamda.nju.edu.cn). For any problem concerning the code, please feel free to contact Dr. Li or Mr. Wei or Mr. Guo.
Download:
code (2.1 MB) (version September 27, 2017)