Induction of descriptive fuzzy classifiers with the Logitboost algorithm

@article{Otero2006InductionOD,
  title={Induction of descriptive fuzzy classifiers with the Logitboost algorithm},
  author={Jos{\'e} Otero and Luciano S{\'a}nchez},
  journal={Soft Comput.},
  year={2006},
  volume={10},
  pages={825-835}
}
Recently, Adaboost has been regarded as a particular case of a previous statistical method: greedy backfitting of extended additive models in logistic regression problems, or “Logitboost”. The application of Logitboost to learn fuzzy classifiers from data should improve the performance of the fuzzy classifier in multiclass problems, and reduce the size of the fuzzy rule base. In this work, we propose a GA-based version of Logitboost and discuss some preliminary numerical results of this method. 
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