Credal C4.5 with Refinement of~Parameters

Comunicación en congreso 2018

Autores: Carlos Mantas, Joaquín Abellán, Javier Castellano, José Ramón Cano De Amo, Serafín Moral

Páginas 739-747

Cómo citar esta publicación

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.
BibTeX

Resumen

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.

Detalles

Editorial
Springer International Publishing
Lugar del congreso
Cham
ISBN
978-3-319-91479-4