关键词: 特征选择, 卡方检验（CHI）, 信息增益（IG）, 支持向量机（SVM）

Abstract: Feature selection is a crucial process of spam filtering. The result of feature selection not only affects the accuracy of classification, but also affects the computational burden. The popular feature selection methods such as CHI selection, information gain, mutual information and SVM feature selection are compared and a mixed email feature selection method is proposed based on information gain using the conditional probability and classification discrimination between features to rudce redundancy among features to overcome their shortcoming that only pay attention to sorting yet ignore the redundancy among features. Experimental results show that: the new method is promising and improves classification accuracy of spam.

Key words: feature selection, CHI, Information Gain（IG）, Support Vector Machine（SVM）