Fuzzy Rule Base Generation through Genetic Algorithms and Bayesian Classifiers A Comparative Approach

@article{Cintra2007FuzzyRB,
  title={Fuzzy Rule Base Generation through Genetic Algorithms and Bayesian Classifiers A Comparative Approach},
  author={Marcos E. Cintra and Heloisa A. Camargo and Estevam R. Hruschka and Maria do Carmo Nicoletti},
  journal={Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007)},
  year={2007},
  pages={315-322}
}
The definition of the fuzzy rule base is one of the most important and difficult tasks when designing fuzzy systems. This paper discusses the results of two different hybrid methods investigated earlier, for the automatic generation of fuzzy rules from numerical data. One of the methods proposes the creation of fuzzy rule bases using genetic algorithms in association with a heuristic for preselecting candidate rules. The other, named Bayes fuzzy, induces a Bayes classifier using a dataset… CONTINUE READING

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