Abstract: Traditional classification rules take the positive form as C→D. A new method of retrieving the negative ¬C→5D form is introduced in this paper. Negative rules can improve the classification quality in some case. We propose a classification algorithm named Rule Generation based on Classification Attribute (RGCA) to deduct negative and positive rules. The RGCA algorithm won’t need processing records item by item. The real dataset are used to verify the presented algorithm. The result shows the negative rules is more than positive rules based on RGCA algorithm, the classification accuracy of RGCA algorithm is better than traditional positive based algorithm.