An efficient genetic algorithm for automated mining of both positive and negative quantitative association rules

@article{Alatas2006AnEG,
  title={An efficient genetic algorithm for automated mining of both positive and negative quantitative association rules},
  author={Bilal Alatas and Erhan Akin},
  journal={Soft Comput.},
  year={2006},
  volume={10},
  pages={230-237}
}
In this paper, a genetic algorithm (GA) is proposed as a search strategy for not only positive but also negative quantitative association rule (AR) mining within databases. Contrary to the methods used as usual, ARs are directly mined without generating frequent itemsets. The proposed GA performs a database-independent approach that does not rely upon the minimum support and the minimum confidence thresholds that are hard to determine for each database. Instead of randomly generated initial… CONTINUE READING

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