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KDD
2001
ACM

Real world performance of association rule algorithms

11 years 4 months ago
Real world performance of association rule algorithms
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improvements previously claimed by the authors on the artificial data, but some of these gains do not carry over to the real datasets, indicating overfitting of the algorithms to the IBM artificial dataset. More importantly, we found that the choice of algorithm only matters at support levels that generate more rules than would be useful in practice. For support levels that generate less than 1,000,000 rules, which is much more than humans can handle and is sufficient for prediction purposes where data is loaded into RAM, Apriori finishes processing in less than 10 minutes. On our datasets, we observed super-exponential growth in the number of rules. On one of our datasets, a 0.02% change in the support increased the number of rules from less than a million to over a billion, implying that outside a very narrow rang...
Zijian Zheng, Ron Kohavi, Llew Mason
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2001
Where KDD
Authors Zijian Zheng, Ron Kohavi, Llew Mason
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