决策树算法的改进

决策树算法是数据挖掘中非常活跃的研究领域。通过对数据挖掘中决策树的基本思想进行阐述,讨论了决策树经典算法(ID3算法)的计算复杂度问题,并针对这一问题提出了利用统计理论知识和条件概率的思想来改进构造决策树的算法。实验表明,这种构造决策树算法的计算复杂度明显优于传统的算法,其效率也有很大的提高。

The Improvement of Decision Tree Algorithm

Decision Tree Algorithm data mining is a very active research field.Through the Data Mining Decision Tree on the basic thinking,discussed the complexity problem of classic Decision Tree Algorithm(ID3 algorithm),and in response to this issue and the use of statistical theory of conditional probability knowledge and thinking to improve the structure of the Decision Tree Algorithm.Experimental results show that the structure of the decision tree algorithm is superior to the traditional complexity of the algorithm,its efficiency also improved greatly.