Comparing Expert and Metric-Based Assessments of Association Rule Interestingness

Abstract

In association rule mining, interestingness refers to metrics that are applied to select association rules, beyond support and confidence. For example, Merceron & Yacef (2008) recommend that researchers use a combination of lift and cosine to select association rules, after first filtering out rules with low support and confidence. However, the empirical… (More)

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Cite this paper

@inproceedings{Bazaldua2014ComparingEA, title={Comparing Expert and Metric-Based Assessments of Association Rule Interestingness}, author={Diego Luna Bazaldua and Ryan Shaun Joazeiro de Baker and Maria Ofelia San Pedro}, booktitle={EDM}, year={2014} }