The research based on GA-SVM feature selection algorithm

摘要：

　　To make feature subset which can gain the higher classification accuracy rate,the method based on genetic algorithms and the feature selection of support vector machine is proposed.Firstly,the ReliefF algorithm provides a priori information to GA,the parameters of the support vector machine mixed into the genetic encoding,and then using genetic algorithm finds the optimal feature subset and support vector machines parameter combination.Finally,experimental results show that the proposed algorithm can gain the higher classification accuracy rate based on the smaller feature subset.

关键词： genetic algorithm support vector machines feature feature selection

作者: Li Hongmei Yang Lingen Zou lihua

作者单位: Department of Computer, Guangdong Baiyun University, Guangdong, 510450, China

会议类型: 国际会议

会议名称: 2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

会议地点: 西安

会议语种:英文

页码: 1497-1502

在线出版日期: 2012-08-24（万方平台首次上网日期，不代表论文的发表时间）