Genetic learning of the membership functions for mining fuzzy association rules from low quality data

@article{Palacios2015GeneticLO,
  title={Genetic learning of the membership functions for mining fuzzy association rules from low quality data},
  author={Ana M. Palacios and Jos{\'e} Luis Palacios and Luciano S{\'a}nchez and Jes{\'u}s Alcal{\'a}-Fdez},
  journal={Inf. Sci.},
  year={2015},
  volume={295},
  pages={358-378}
}
  • Ana M. Palacios, José Luis Palacios, +1 author Jesús Alcalá-Fdez
  • Published in Inf. Sci. 2015
  • Mathematics, Computer Science
  • Many methods have been proposed to mine fuzzy association rules from databases with crisp values in order to help decision-makers make good decisions and tackle new types of problems. However, most real-world problems present a certain degree of imprecision. Various studies have been proposed to mine fuzzy association rules from imprecise data but they assume that the membership functions are known in advance and it is not an easy task to know a priori the most appropriate fuzzy sets to cover… CONTINUE READING

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