Description: cisLDM is a package which tries to optimize the margin distribution on both labeled and unlabeled data when minimizing the worst-case total-cost and the mean total-cost simultaneously according to the cost interval. The package includes the MATLAB code of the algorithm cisLDM and one example data set.
References: Yu-Hang Zhou and Zhi-Hua Zhou. Large margin distribution learning with cost interval and unlabeled data. IEEE Transactions on Knowledge and Data Engineering, in press.
ATTN: This package is free for academic usage. You can run it at your own disk. For other purposes, please contact Prof. Zhi-Hua Zhou (zhouzh@nju.edu.cn).
Requirement: The package was developed with MATLAB R2014a.
ATTN2: This package was developed by Mr. Yu-Hang Zhou (zhouyh@lamda.nju.edu.cn). For any problem concerning the code, please feel free to contact Mr. Zhou.
Download:
code (721 KB)