Pages 739-747
Cite this publication
Mantas, C. J., Abellán, J., Castellano, J. G., Cano De Amo, J. R., & Moral, S. (2018). Credal C4.5 with Refinement of~Parameters (J. Medina, M. Ojeda-Aciego, J. L. Verdegay, I. Perfilieva, B. Bouchon-Meunier, & R. R. Yager, Eds.). Cham: Springer International Publishing.
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.
Details
- Editors
- Jesús Medina, Manuel Ojeda-Aciego, José Verdegay, Irina Perfilieva, Bernadette Bouchon-Meunier, Ronald Yager
- Publisher
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Springer International Publishing
- Conference Location
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Cham
- ISBN Number
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978-3-319-91479-4