关键词: 决策树, 多尺度粗糙集模型, 近似分类精度, 抑制因子

Abstract: Concerning the complicated structure and being sensitive to noise and other problems of decision tree constructed by classical decision tree algorithms, a new decision tree construction algorithm based on multiscale rough set model was proposed. This proposed algorithm introduced the concept of scale variable and scale function, the index of approximate classification accuracy in different scales was used to select test attributes and the holddown factor was put forward to prune the decision tree and removed the noise rules effectively. The results show that decision tree constructed by this algorithm is simple, and has certain degree of antiinterference and can meet the decision accuracy requirements from different users.

Key words: decision tree, multiscale rough set model, classification accuracy, hold-down factor