变精度粗糙集模型在决策树构造中的应用  

Application of variable precision rough set model in building decision tree

作　　者：孙洁[1] 周庆敏[1] 常志玲[1] 

机构地区：[1]南京工业大学信息科学与工程学院,南京210009

出　　处：《计算机工程与应用》2007年第7期195-197,共3页Computer Engineering and Applications

基　　金：江苏省教育厅自然科学基金(No.05KJB520048)

摘　　要：在应用变精度粗糙集模型构造决策树的研究基础上,提出了具有置信度规则的决策树的构造方法。该方法是对决策树生成方法的一个改进,所构造的决策树具有更强的实用性以及更高的可理解性。还针对两个甚至两个以上属性的分类质量量度相等的特殊情形,给出了如何选择较优的属性作为结点的方法。与传统的ID3算法相比,该方法所构造的决策树不仅结构简单,而且更加实用,利于理解。In this paper,on the basis of research on the application of variable precision rough set model in building decision tree,a method of building Decision Tree（DT） with rules that have definite confidence is proposed.h is an improvement to the method of building DT,decision tree built in this way is more practical and comprehensible.It also gives out the solution to the problem how to choose the better attribute as the node when two or more attributes have the same value of quality of classification.Compared to the traditional ID3 algorithm,decision tree built with this method is not only simple-structured,but also more practical and comprehensible.

关 键 词：决策树 变精度粗糙集 置信度 分类质量 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]