A New Weighted Support Vector Machine for Regression and Its Parameters Optimization

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• 作者：Liquan Mei ; Shujuan Zhang
• 关键词：WSVM ; singularity ; regression ; parameters optimization
• 刊名：Lecture Notes in Computer Science
• 出版年：2008
• 出版时间：2008
• 年：2008
• 卷：5227
• 期：1
• 页码：597-604
• 全文大小：344.3 KB

文摘

In this paper what we study is twofold. Firstly a new weighted support vector machine(WSVM) is introduced, in which different roles of samples are considered. It better processes the singularity in the sample than SVM. Secondly based on grid search and the solution path algorithm, a new algorithm is given to quickly find the optimum parameters. Numerical results show the effectiveness and the stability of the algorithm.