Journal of Guangxi Normal University(Natural Science Edition) ›› 2011, Vol. 29 ›› Issue (2): 114-118.

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Optimizing Parameters of SVM Based on Combined Bionic Algorithm

YAN Xiao-ming, ZHENG Zhi   

  1. School of Mathematics and Computer Science,Fujian Normal University,Fuzhou Fujian 350108,China
  • Received:2011-05-18 Published:2018-11-19

Abstract: A new method in optimizing SVM classification's parameter is proposed.Following steps are applied:firstly,applying the GA to optimizethe SVM parameters in a rough range,then expanding nearby section of the best result of theGA,finally,using PSO algorithm optimized SVM parameters with new searching section,to improve the generalization ability of SVM and reduce the time consumptionof optimizing.Experiment results show that the proposed method has better generalization ability even in condition of losing sample data.

Key words: parameter optimization, GA, PSO, support vector machine

CLC Number: 

  • TP181
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