This thesis analyzes the traditional ID3 decision tree classification algorithm and performance by using data mining, using the theory of differential knowledge in higher mathematics, improves and optimizes the operation speed and the test attribute selection bias problem in ID3 algorithm, and further gives the pseudo-code of the improved algorithm.