The invention provides a feature extraction method for text categorization. The feature extraction method is used for solving the problem that the accuracy rate and the recall rate of text categorization need to be increased further. The feature extraction method is a strategic method. In consideration of the concept of entropy in statistical thermodynamics, entropy is used for describing the degree of disorder of a system and is significantly applied to the fields of cybernetics, probability theory, number theory, astrophysics, bioscience, information theory and the like. According to the feature extraction method, entropy can also be used in text categorization, a feature is regarded as an event, a category set of text is a system, and therefore entropy can be used for measuring the degree of disorder of features and categories and converted into the closeness degree of the relation between the features and the categories. According to the feature extraction method, on the basis of improved mutual information, the concept of entropy is combined, a new feature evaluation function is provided, feature extraction is conducted on the basis of the function, a superior feature subset can be selected for showing the text and building a categorizer, and therefore the accuracy rate and the recall rate of text categorization are increased.