Research on Chinese Public Policy Decision Model Based on Decision Tree Algorithm

Abstract

In this paper, the decision tree classification algorithm is used to establish the prediction model of Chinese public policy decision. This paper selects characteristic attributes based on the principle of policy making. Then, taking the result of public policy decision as the target label, this paper optimizes the model by adjusting the maximum depth of decision tree, the minimum number of leaf samples and the decision threshold. The test set verifies that the optimized decision tree model has a good predictive effect on the result prediction of the public policy decision model. The value of AUC was 0.848 and the model had strong generalization ability. The AUC difference between training set and test set is less than 0.04.