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决策树ID3算法的分析与优化
Analysis and Optimization of ID3 Decision Tree Algorithm
【摘要】 对ID3算法的基本概念和原理以及其分支策略和构造过程进行了详细阐述,针对ID3算法倾向于选择取值较多的属性的缺点,引进属性偏向阈和信息增益率对其做了改进,并利用凸函数的性质简化了ID3算法中信息增益的计算.通过实验对改进前后的算法进行了比较,实验表明,改进后的算法是有效的.
【Abstract】 The basic concepts and principles of ID3 algorithm and its branching strategy and construction process are elaborated. For the shortcoming that ID3 algorithm tends to choose attribute with many values,attribution deflection threshold and information gain ratio were introduced to improve ID3 algorithm,and the properties of convex function was used to simplify the information gain calculation in the ID3 algorithm. By comparing experiments,the results show that the improved algorithm is effective.
【关键词】 决策树;
ID3算法;
凸函数;
信息增益率;
属性偏向阈;
【Key words】 decision tree; ID3 algorithm; convex function; information gain ratio; attribution deflection threshold;
【Key words】 decision tree; ID3 algorithm; convex function; information gain ratio; attribution deflection threshold;
【基金】 辽宁省教育厅科学研究计划资助项目(L2012163)
- 【文献出处】 大连交通大学学报 ,Journal of Dalian Jiaotong University , 编辑部邮箱 ,2015年02期
- 【分类号】TP301.6
- 【被引频次】22
- 【下载频次】250