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cisLDM

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)
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