一种基于分类精度的特征选择支持向量机

J4 ›› 2010, Vol. 45 ›› Issue (7): 119-121.

一种基于分类精度的特征选择支持向量机

易超群,李建平,朱成文

国防科学技术大学理学院, 湖南长沙 410073

收稿日期:2010-04-02 出版日期:2010-07-16 发布日期:2010-09-06
作者简介:易超群(1985-),男,硕士研究生,研究方向为支持向量机与数据挖掘.Email:chaoqun9527@163.com

A kind of feature selection based on classification accuracy of SVM

YI Chao-qun, LI Jian-ping, ZHU Cheng-wen

College of Science, National University of Defense Technology, Changsha 410073, Hunan, China

Received:2010-04-02 Online:2010-07-16 Published:2010-09-06

摘要/Abstract

摘要：

在综合序列前向选择(sequential forward selection,SFS)方法和广义序列前向选择(generalized sequential forward selection,GSFS)方法的基础上,提出了基于分类精度的特征选取(sequential forward selection based on classification accuracy, CA-SFS)方法。它依次改变GSFS方法中的r值,并以支持向量机(support vector machine,SVM)作为分类器,将得出的分类精度作为准则函数对特征进行取舍。仿真实验表明CA-SFS算法不但选择了较少的特征,而且取得了较好的分类效果。

关键词: 特征选择;支持向量机;分类精度;仿真

Abstract:

The sequential forward selection based on classification accuracy (CA-SFS) was proposed by associating sequential forward selection (SFS) with generalized sequential forward selection (GSFS). It varied the value of r in GSFS and employs SVM (support vector machine)as the classifier. The classification accuracy was taken as a criterion to decide the retention or elimination of features. Simulations showed that CA-SFS performed well both in selecting fewer features and classifying samples.

Key words: feature selection; support vector machine; classification accuracy; simulation

易超群,李建平,朱成文. 一种基于分类精度的特征选择支持向量机[J]. J4, 2010, 45(7): 119-121.

YI Chao-qun, LI Jian-ping, ZHU Cheng-wen. A kind of feature selection based on classification accuracy of SVM[J]. J4, 2010, 45(7): 119-121.

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