关键词: C4.5算法, 边界定理, Gini指标, 奥卡姆剃刀, 再带入估计

Abstract: C4.5 is the most influential decision tree classified algorithm, but it still has some deficiencies. To improve the deficiency of consuming more time in discretizing continuous-valued attributes using C4.5 algorithm, a new simplified algorithm is proposed by using Gini index to replace information entropy after discretizing continuous-valued attributes based on Fayyad and Irani boundary theory. To solving the over fitting problem in decision tree method, the improved algorithm is considered by using resubstitution estimate based on Occam’s razor. Applying the idea above to financial loan data, experimental results show that the execution time is reduced by an average of 8.74%, and that the model complexity is reduced by an average of 6.26% by using the improved C4.5 algorithm under the premise of guaranteeing the accuracy. Finally, the experimental results verify the validity of this algorithm.

Key words: C4.5 algorithm, boundary theorem, Gini index, Occam’s razor, resubstitution estimate