关键词: 决策树, 粗糙集, 决策分类熵, 抑制参数

Abstract: In order to better complete the task of classification mining on financial datasets, decision classify-entropy concept was put forward based on the rough set theory; and based on this concept, a novel decision tree construction algorithm was proposed. To overcome over-fitting, inhibiting factor was introduced to control decision tree construction. The case study and experimental results in financial datasets show that, compared with the classical C4.5 algorithm, the new algorithm can resolve the drawbacks of the traditional algorithm and could construct a suboptimal decision tree effectively. The application in financial field also proves that the new algorithm can finish the objective task much better.

Key words: decision tree, rough set, decision classify-entropy, inhibiting factor