Title :
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
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;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4633779
