Unconstrained transductive Support Vector Machines and its application

Author

Tian, Yingjie ; Sun, Yunchuan ; Chen, Chuan-Liang ; Zhang, Zhan

Author_Institution

Res. Center on Fictitious Econ. & Data Sci., Chinese Acad. of Sci., Beijing

fYear

2008

fDate

1-8 June 2008

Firstpage

137

Lastpage

141

Abstract

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.

Keywords

learning (artificial intelligence); numerical analysis; support vector machines; credit card dataset; machine learning; optimization methods; transductive support vector machines; Artificial intelligence; Credit cards; Machine learning; Machine learning algorithms; Optimization methods; Power system modeling; Static VAr compensators; Sun; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Hong Kong

ISSN

1098-7576

Print_ISBN

978-1-4244-1820-6

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2008.4633779

Filename

4633779