关键词: 文本分类, 特征选择, 交叉熵, 信息增益, 互信息最大化

Abstract: With the guide of mutual information maximization principles，this paper proposes a new feature selection algorithm which is based on the information theory models，namely，mutual information maximization based feature selection algorithm（MaxMI）.The basic idea is after the feature selection，the information of the categories should be retained as much as possible.This algorithm is a little similar with the traditional information gain，mutual information and cross entropy in the expression format，but is not the same essentially.From the experiments，We can see that our algorithm is superior to the other three algorithms.

Key words: text classification, feature selection, cross-entropy, information gain, mutual information maximization