关键词: 文本分类, 特征选择, 互信息, 特征降维

Abstract: This paper puts forward a kind of optimizing Mutual Information（MI） text characteristic selection method. Aiming at the MI’s deficiencies, it puts forward three approaches to improvement. The positive and negative features with the weight factors are distinguished. Through the introduction of the correct factors way, the low-frequency word is realized to restrain. According to the features position in the text, a further weighted method is put forward. In this way, the paper has improved the efficiency of MI model. Subsequent text classification experimental results show the proposed optimization MI and rationality of the method is effective.

Key words: Text Categorization（TC）, feature selection, Mutual Information（MI）, feature reduction