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Unconstrained transductive Support Vector Machines and its application

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4 Author(s)
Yingjie Tian ; Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing, China ; 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:

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

Date of Conference:

1-8 June 2008