Description: MissSVM is a package for solving multi-instance learning problems using semi-supervised support vector machines. The purpose of MissSVM is to show that if the assumption of i.i.d. instances were taken, multi-instance learning can be viewed as a special case of semi-supervised learning, and the field of multi-instance learning might be merged into the field of semi-supervised learning. Thus, future multi-instance learning research should assume only i.i.d. bags and avoid the assumption of i.i.d. instances.
References:
•Z.-H. Zhou and J.-M. Xu. On the relation between multi-instance learning and semi-supervised learning. In: Proceedings of the 24th International Conference on Machine Learning (ICML'07), Corvallis, OR, 2007.
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 C++. The QP problem is solved by using Mosek 4.0, so you should include it as library of your project. You can get Mosek from http://www.mosek.com/.
ATTN2: This package was developed by Mr. Jun-Ming Xu (xujm@lamda.nju.edu.cn). For any problem concerning the code, please feel free to contact Mr. Xu.
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code (6.0Kb)