A method for feature selection based on the correlation analysis

摘要：

Feature selection is one of the important issues in the fields of machine learning and pattern classification. The classification ability of features is analyzed from the point of view of correlation and redundancy. Two types of correlation: C-correlation and F-correlation are presented. The Ccorrelation is applied to identify the relevant features to the category attribute, while the Fcorrelation is used to measure the redundancy among features. Finally, the dimension of input features is further reduced with the sequential forward search strategy. Thus a method for feature selection based on the correlation analysis of features is derived. The experimental results show that the proposed algorithm is an effective method for feature selection.

关键词： feature selection correlation redundancy dimension reduction

作者: Jinjie Huang Ningning Huang Luo Zhang HongmeiXu

作者单位: Department of Automation Harbin University of Science and Technology Harbin, China

会议类型: 国际会议

会议名称: 2012 International Conference on Measurement,Information and Control(2012测量、信息与控制国际会议 ICMIC2012)

会议地点: 哈尔滨

会议语种:英文

页码: 529-532

在线出版日期: 2012-05-18（万方平台首次上网日期，不代表论文的发表时间）