Abstract: In order to overcome the defect of high time complexity and wide search space for finding the minimal attribute set during attribute reduction.In this paper,the reduction of attributes is considered as a special optimization process by ant colony algorithm displayed good performance in solving complex problem of combinational optimization.First,an attribute is abstracted as a node and the lease combination of these nodes is found which can take place in all attribute node s but not change the degree of classified roughness.Base on these points,rough set theory and ant colony algorithm are combined according to the problem of ant colony algorithm with little information pheromone and slow convergence rate.The attribute core is determined through the correlative algorithms of rough set theory,which can be used as initial node of ant colony algorithm.Finally,the least attribute set is scanned by means of the search capacity of ant colony algorithm.Theory analysis and experimental results show that the algorithm proposed in this paper is feasible and effective.