Credal C4.5 with Refinement of~Parameters

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.