%0 Journal Article
%T Joint Feature Selection Method Based on Relevance and Redundancy<br>基于相关性和冗余度的联合特征选择方法
%A ZHOU Cheng
%A GE Bin
%A TANG Jiu-yang
%A XIAO Wei-dong
%A <br>周城
%A 葛斌
%A 唐九阳
%A 肖卫东
%J 计算机科学
%D 2012
%I 
%X Based on a comparative study of four feature selection methods,including document frequency(DF) unrelated to class information,and information gain(IG),mutual information(MI) and chi-square statistic(CHI),which are relatedto class information,we analyzed the disadvantages of combining these two kinds of methods directly and proposed a joint feature selection method based on relevance and redundancy to joint DF and one of IG,MI and CHI.This approach aims to eliminate redundant features,find useful features for classification and consequently improve the accuracy of text sentiment classification.The results of the experiment show that the proposed method can not only improve the performance but also reduce the feature dimension.
%K Text sentiment classification
%K Joint feature selection
%K Rclevance
%K Redundant feature<br>文本情感分类
%K 联合特征选择
%K 相关性
%K 冗余特征
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=6CC4FADE9FC7EFEAFBD9BA6D8819566E&yid=99E9153A83D4CB11&vid=7C3A4C1EE6A45749&iid=E158A972A605785F&sid=7EBE588F611589FC&eid=798FBE8DE1A255B1&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0