郑州轻工业学院学报(自然科学版)Issue(1)：50-54,5.DOI:10.3969/j.issn.2095-476X.2015.01.011
基于粗糙集的ID3决策树算法改进
Improved ID3 decision tree algorithm based on rough set
摘要
Abstract
The traditional decision tree algorithms such as ID3 usually uses a single attribute as the basis of branching judgment.The scale of the tree generated by ID3 is very large and rules formed are difficult to understand.Aiming at the problems described above,an algorithm was proposed using multi-variable as the judging conditions of node attributes.By using the property of attribute dependency in rough set and choo-sing nuclear properties of condition attributes relative to decision attributes in the information system as multi-variable node attributes,the algorithm used the concept of relative generalization to aid the branching process and generated a multi-variable decision tree.Through the analysis of example and by comparing with the conventional ID3 algorithm,the high efficiency of the improved algorithm was verified.关键词
粗糙集/ID3算法/决策树/相对泛化/等价关系Key words
rough set/ID3 algorithm/decision tree/relative generalization/equivalent relationship分类
信息技术与安全科学引用本文复制引用
朱付保,霍晓齐,徐显景..基于粗糙集的ID3决策树算法改进[J].郑州轻工业学院学报(自然科学版),2015,(1):50-54,5.基金项目
河南省科技攻关计划项目(122102210492) （122102210492）
