ML Anthology

QuantMiner for Mining Quantitative Association Rules

Ansaf Salleb-Aouissi, Christel Vrain, Cyril Nortet, Xiangrong Kong, Vivek Rathod, Daniel Cassard
MLOSS 2013 pp. 3153-3157
/mloss/2013/sallebaouissi2013jmlr-quantminer/

Abstract

In this paper, we propose QuantMiner, a mining quantitative association rules system. This system is based on a genetic algorithm that dynamically discovers âgoodâ 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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Cite

Text

Salleb-Aouissi et al. "QuantMiner for Mining Quantitative Association Rules." Machine Learning Open Source Software, 2013.

Markdown

[Salleb-Aouissi et al. "QuantMiner for Mining Quantitative Association Rules." Machine Learning Open Source Software, 2013.](https://mlanthology.org/mloss/2013/sallebaouissi2013jmlr-quantminer/)

BibTeX

@article{sallebaouissi2013jmlr-quantminer,
  title     = {{QuantMiner for Mining Quantitative Association Rules}},
  author    = {Salleb-Aouissi, Ansaf and Vrain, Christel and Nortet, Cyril and Kong, Xiangrong and Rathod, Vivek and Cassard, Daniel},
  journal   = {Machine Learning Open Source Software},
  year      = {2013},
  pages     = {3153-3157},
  volume    = {14},
  url       = {https://mlanthology.org/mloss/2013/sallebaouissi2013jmlr-quantminer/}
}