Credal-C4.5: Decision tree based on imprecise probabilities to classify noisy data
A new algorithm inspired by C4.5 and imprecise probabilities is defined. This algorithm (Credal-C4.5) assumes unreliable data sets when the tree is built. Pruning process is also incorporated to Credal-C4.5. Several experiments are made to compare algorithms. The new method is especially suitable to classify data sets with noise.
imprecise probabilities noisy data imprecise dirichlet model uncertainty measures credal decision trees c4.5 algorithm