In view of the information gain model defects in the text classification

this article puts forward a text classification algorithm based on the grey relation and information gain. Firstly

we improved a method of x2 statistics in sort feature selection in order to express text. In this way

we improve the precision of the class center vector. Secondly

according to the IG model weights the low frequency words too bigger

we put forward an improved weighted method basing on frequency and position. Lastly

we put forward a new way in text similarity calculation in order to improve the shortcomings of the similarity calculation model that based on distance. Subsequent text categorization test shows that this paper puts forward an improved IG method and enhances the text classification efficiency.