利用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

2019 6th International Conference on Systems and Informatics (ICSAI) Pub Date : 2019-11-01 DOI:10.1109/ICSAI48974.2019.9010367

Vlad Robu, V. Santos

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引用次数: 8

摘要

本文旨在通过将Apriori和Eclat算法应用于真实数据集，比较它们在关联规则挖掘中的应用。除了考虑算法的性能效率外，研究还考虑了支持度的分布，以及Apriori和Eclat生成的规则数量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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2019 6th International Conference on Systems and Informatics (ICSAI)

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