Feature selection is the process of selecting a subset of the terms occurring in the training set and using only this subset as features in classification process of data mining. Feature selection algorithm can be evaluated from mutually efficiency and effectiveness points of view. The authors' proposed algorithm FAST is experimentally evaluated in this paper. FAST algorithm has three steps. In the first step irrelevant features are removed. In the second step, features are divided into clusters that possess features with redundant features.