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Mining Frequent Patterns in Data Using Apriori and Eclat: A Comparison of the Algorithm Performance and Association Rule Generation

机译:使用Apriori和Eclat挖掘数据中的频繁模式:算法性能和关联规则生成的比较

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This paper aims to compare Apriori and Eclat algorithms for association rules mining by applying them on a real-world dataset. In addition to considering performance efficiency of the algorithms, the research takes into consideration the distribution of the support, as well as the number of rules generated by Apriori and Eclat.
机译:本文旨在通过将Apriori算法和Eclat算法应用于现实数据集进行比较,以进行关联规则挖掘。除了考虑算法的性能效率外,研究还考虑了支持的分布以及由Apriori和Eclat生成的规则的数量。

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