Joint Feature Selection Method Based on Relevance and Redundancy
基于相关性和冗余度的联合特征选择方法

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.