Feature Selection for Text Classification using OR+SVM-RFE

摘要：

Feature selection is the key issue in text classification because there are a large number of attributes. In this paper, we propose a new algorithm OR+SVM-RFE that integrates Odds Radio(OR) with recursive feature elimination based on SVM(SVM-RFE). Odds Radio is first used to roughly and rapidly select a feature subset. Then SVM-RFE is used to delicately select a smaller feature subset. Experiment results show the feature subset selected by OR+SVM-RFE obtains a good classification performance with less features.

关键词： Feature Selection Text Classification Odds Ratio SVM-RFE

作者: Meixiang Luo Linkai Luo

作者单位: College of Information Science and Technology, Xiamen University, Fujian, 361005

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 1648-1652

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）