QuantMiner for Mining Quantitative Association Rules

Abstract : In this paper, we propose QUANTMINER, a mining quantitative association rules system. This system is based on a genetic algorithm that dynamically discovers "good" intervals in association rules by optimizing both the support and the confidence. The experiments on real and artificial databases have shown the usefulness of QUANTMINER as an interactive, exploratory data mining tool.
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https://hal.archives-ouvertes.fr/hal-00912453
Contributor : Christel Vrain <>
Submitted on : Monday, December 2, 2013 - 10:36:46 AM
Last modification on : Thursday, June 27, 2019 - 1:36:49 PM

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Ansaf Salleb-Aouissi, Christel Vrain, Cyril Nortet, Xiangrong Kong, Vivek Rathod, et al.. QuantMiner for Mining Quantitative Association Rules. Journal of Machine Learning Research, Microtome Publishing, 2013, 14, pp.3153-3157. ⟨hal-00912453⟩

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