Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (3): 38-40.DOI: 10.3778/j.issn.1002-8331.2011.03.011

• 研究、探讨 • Previous Articles     Next Articles

Method of determining Gaussian kernel parameter by clustering

LIU Qiongsun,FAN Ruiya   

  1. College of Mathematics and Physics,Chongqing University,Chongqing 400030,China
  • Received:2010-05-05 Revised:2010-07-23 Online:2011-01-21 Published:2011-01-21
  • Contact: LIU Qiongsun



  1. 重庆大学 数理学院,重庆 400030
  • 通讯作者: 刘琼荪

Abstract: The selection of Gaussian kernel parameterσdirectly affects the classification of Gaussian kernel SVM(Support Vector Machine).Togethering the clustering method and minimum distance,an optimization algorithm is constructed to determine the parameterσ,which adapts Gaussian kernel SVM to classify the test set,whose correct classification rate contributes the selection of parameterσ.Experimental results show that this method is suitable for a broader data type,furthermore,the method has a good generalization ability,and efficiently develops results of the classification.

Key words: Gaussian kernel parameter, clustering, minimum distance, Support Vector Machine(SVM)



关键词: 高斯核参数, 聚类, 最小距离, 支持向量机

CLC Number: