@inproceedings{bibcite_431,
  author = {Carlos Mantas and Joaqu{\'\i}n Abell{\'a}n and Javier Castellano and Jos{\'e} Ram{\'o}n Cano De Amo and Seraf{\'\i}n Moral},
  editor = {Jes{\'u}s Medina and Manuel Ojeda-Aciego and Jos{\'e} Verdegay and Irina Perfilieva and Bernadette Bouchon-Meunier and Ronald Yager},
  title = {Credal C4.5 with Refinement of~Parameters},
  abstract = {Recently, a classification method called Credal C4.5 (CC4.5) has been presented which combines imprecise probabilities and the C4.5 algorithm. The action of the CC4.5 algorithm depends on a parameter s. In previous works, it has been shown that this parameter has relation with the degree of overfitting of the model. The noise level of a data set can influence on the choice of a good value for s. In this paper, it is presented a new method based on the CC4.5 method with a refining of its parameter in the time of training. The new method has an equivalent performance than CC4.5 with the best value of s for each level noise.},
  year = {2018},
  pages = {739-747},
  publisher = {Springer International Publishing},
  address = {Cham},
  isbn = {978-3-319-91479-4},
}