A New Method for Constructing Decision Tree Based on Rough Sets Theory

查看全文 作　　者：Longjun [1]Huang;Caiying [2]Zhou;Minghe [1]Huang;Zhiming [1]Zhuang

机构地区：[1]College of Software, Jiangxi Normal University, Nanchang 330000, China;[2]Faculty of Science Jiangxi University of Science and Technology, Ganzhou 341000, China

出　　处：《南昌工程学院学报》索引2006年第25卷第2期,共4页

基　　金：Key AttackProjectofJiangxiProvinceYouth Funds ofJiangxiNormal Universtiy 摘　　要：Decision trees induction algorithms have been used for classification in a wide range of application domains. In the process of constructing a tree, the criteria of selecting test attributes will influence the classification accuracy of the tree.In this paper,the degree of dependency of decision attribute to condition attribute,based on rough set theory,is used as a heuristic for selecting the attribute that will best separate the samples into individual classes.The result of an example shows that compared with the entropy-based approach,our approach is a better way to select nodes for constructing decision trees. 关键词：rough sets dependency of attributes classification decision tree

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A New Method for Constructing Decision Tree Based on Rough Sets Theory

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