New construction approach of decision tree

doi:10.3778/j.issn.1002-8331.2009.16.007

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (16): 28-30.DOI: 10.3778/j.issn.1002-8331.2009.16.007

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New construction approach of decision tree

GAO Jing¹,SONG Wei²,YANG Bing-ru³,XU Zhang-yan⁴

1.School of Information，Capital University of Economics and Business，Beijing 100070，China
2.School of Information Engineering，North China University of Technology，Beijing 100144，China
3.School of Information Engineering，University of Science and Technology Beijing，Beijing 100083，China
4.Department of Computer，Guangxi Normal University，Guilin，Guangxi 541004，China

Received:2009-02-13 Revised:2009-03-20 Online:2009-06-01 Published:2009-06-01
Contact: GAO Jing

新型决策树构造方法

高静¹,宋威²,杨炳儒³,徐章艳⁴

1.首都经济贸易大学信息学院，北京 100070
2.北方工业大学信息工程学院，北京 100144
3.北京科技大学信息工程学院，北京 100083
4.广西师范大学计算机系，广西桂林 541004

通讯作者: 高静

Abstract

Abstract: Decision tree is an important tool for data mining.However，the design of optimal decision tree is proved to be a NP-complete problem.A construction approach of decision tree based on association rule is proposed.Firstly，approximate exact rule with high confidence is defined.Then，an algorithm for mining approximate exact rules is proposed.Thirdly，approximate exact rules are used to generate new attributes.Fourthly，the method on new attribute evaluation is discussed.Finally，together with original attributes，new generated attributes are used for construction of decision tree.Experimental results show the accuracy of the proposed method is high.

Key words: association rule, approximate exact rule, decision tree

摘要： 决策树是一种重要的数据挖掘工具，但构造最优决策树是一个NP-完全问题。提出了一种基于关联规则挖掘的决策树构造方法。首先定义了高可信度的近似精确规则，给出了挖掘这类规则的算法；在近似精确规则的基础上产生新的属性，并讨论了新生成属性的评价方法；然后利用新生成的属性和数据本身的属性共同构造决策树；实验结果表明新的决策树构造方法具有较高的精度。

关键词: 关联规则, 近似精确规则, 决策树

GAO Jing¹,SONG Wei²,YANG Bing-ru³,XU Zhang-yan⁴. New construction approach of decision tree[J]. Computer Engineering and Applications, 2009, 45(16): 28-30.

高静¹,宋威²,杨炳儒³,徐章艳⁴. 新型决策树构造方法[J]. 计算机工程与应用, 2009, 45(16): 28-30.

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New construction approach of decision tree

新型决策树构造方法

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