Title :
Unconstrained Transductive Support Vector Machines
Author :
Tian, Yingjie ; Yan, Manfu
Author_Institution :
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 transductive support vector machines (TSVM) for classification and construct a new algorithm - unconstrained transductive support vector machines (UTSVM). After researching on the special construction of primal problem in TSVM, we transform it to an unconstrained problem and then smooth the derived problem in order to apply usual optimization methods.
Keywords :
optimisation; support vector machines; machine learning; optimization methods; unconstrained problem; unconstrained transductive support vector machines; Artificial intelligence; Educational institutions; Machine learning; Machine learning algorithms; Medical services; Optimization methods; Predictive models; Static VAr compensators; Support vector machine classification; Support vector machines;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.599
