Abstract. We describe EDRL-MD, an evolutionary algorithm-based system, for learning decision rules from databases. The main novelty of our approach lies in dealing with continuous ...
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Decision trees are widely disseminated as an effective solution for classification tasks. Decision tree induction algorithms have some limitations though, due to the typical strat...
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...