中北大学学报（自然科学版）Issue(4)：402-406,5.DOI:10.3969/j.issn.1673-3193.2014.04.009
一种基于属性相关的 C4．5决策树改进算法
An Improved Algorithm of C4 .5 Decision Tree Based on Attributes Correlation
魏浩 1丁要军1
作者信息
- 1. 咸阳师范学院信息工程学院，陕西咸阳712000
- 折叠
摘要
Abstract
In view of the disadvantage that the chose of test attribute don ’t consider the interaction between the attributes in the construction process of C4 .5 decision tree ,an improved C4 .5 decision algorithm was pro-posed .Redundancy of the test attribute with other attributes was represented by average information gain . Then redundancy of the test attribute with other attributes was added to the algorithm .The algorithm select-ed the test attribute with high information gain ratio and low redundancy by information gain ,split entropy and redundancy three evaluation factors .The experimental results illustrate that the improved C4 .5 decision tree algorithm increases average classification accuracy on selected experimental data sets .关键词
C4 .5决策树/属性相关/信息熵/信息增益率/冗余度Key words
C4 .5 decision tree/attributes correlation/information entropy/information gain ratio/redun-dancy分类
信息技术与安全科学引用本文复制引用
魏浩,丁要军..一种基于属性相关的 C4．5决策树改进算法[J].中北大学学报（自然科学版）,2014,(4):402-406,5.
