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中文摘要：
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。
英文摘要：
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.
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