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

Authors:
Liquan Mei;Shujuan Zhang
Affiliations:
School of Science, Xi'an Jiaotong University, Xi'an, P.R. China 710049;School of Science, Xi'an Jiaotong University, Xi'an, P.R. China 710049
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

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.