mcKLR

Description: mcKLR is a package for multi-class cost-sensitive learning. It has been applied to face recognition with success in our CVPR'08 paper. In that paper we argue that face recognition is inherently a task involving unequal misclassification costs, and therefore we should try to minimize the costs instead of minimizing the number of mistakes, yet almost all previous face recognition research focus only on minimizing the number of mistakes! The mcKLR method, however, can also be applied to other tasks which involve multi-class cost-sensitive learning.

References:  

• Y. Zhang and Z.-H. Zhou. Cost-sensitive face recognition. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'08), Anchorage, AK, 2008.

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. The Java routines can be called in MATLAB environment.

ATTN2:       This package was developed by Mr. Yin Zhang (zhangyin@lamda.nju.edu.cn). For any problem concerning the code, please feel free to contact Mr. Zhang.

Download:   [code] (5Kb)