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关于关联规则挖掘和因果关系发现之间的关系,较为全面地分析比较结果目前尚不多见。本文在说明关联规则与因果规则各自特点的基础上,从方向性、对人类行为的指导意义以及如何将他们联系起来三个方面进行了理论上的分析比较。分析结果表明因果发现能够找出事物间的内在机制性联系,并且可以据此对关联规则进行推理和检验。最后,将两种数据挖掘方法应用于一个人口统计数据集,并比较了挖掘结果,从而进一步验证理论分析的结论。
With regard to the relationship between association rules mining and causality discovery, it is not so common to analyze the comparative results more comprehensively. Based on the characteristics of association rules and causation rules, this paper makes theoretical analysis and comparison on the three aspects of directionality, the guiding significance to human behavior and how to connect them. The results of the analysis show that causality discovery can find out the intrinsic mechanism connection between things, and can reason and test the association rules accordingly. Finally, the two data mining methods are applied to a demographic data set, and the results of the mining are compared to further verify the conclusions of the theoretical analysis.