On the influence of feature selection in fuzzy rule-based regression model generation

@article{Antonelli2016OnTI,
  title={On the influence of feature selection in fuzzy rule-based regression model generation},
  author={Michela Antonelli and Pietro Ducange and Francesco Marcelloni and Armando Segatori},
  journal={Inf. Sci.},
  year={2016},
  volume={329},
  pages={649-669}
}
Fuzzy rule-based models have been extensively used in regression problems. Besides high accuracy, one of the most appreciated characteristics of these models is their interpretability, which is generally measured in terms of complexity. Complexity is affected by the number of features used for generating the model: the lower the number of features, the lower the complexity. Feature selection can therefore considerably contribute not only to speed up the learning process, but also to improve the… CONTINUE READING

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