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Unconstrained transductive Support Vector Machines and its application

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4 Author(s)
Yingjie Tian ; Res. Center on Fictitious Econ. & Data Sci., Chinese Acad. of Sci., Beijing ; Yunchuan Sun ; Chuan-Liang Chen ; Zhan Zhang

Support vector machines have been extensively used in machine learning because of its efficiency and its theoretical background. This paper focuses on nu-transductive support vector machines for classification (nu-TSVC) and construct a new algorithm - Unconstrained nu-Transductive Support Vector Machines (Unu-TSVM). After researching on the special construction of primal problem in nu-TSVM, we transform it to an unconstrained problem and then smooth the derived problem in order to apply usual optimization methods. Numerical experiments prove its successful application in real life credit card dataset.

Published in:

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Date of Conference:

1-8 June 2008