Dimension reducing is very important in VSM based text classification system. Feature selection is more suitable for text data because of its efficiency. A new feature selection algorithm is proposed in this paper on the basis of Fisher linear discriminant model, which converts the solution process to feature optimization problem and avoids the complex matrix operations. The experiment shows that the new algorithm has good performance and is better than IG and CHI method.