Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Subgroup discovery aims at finding subsets of a population whose class distribution is significantly different from the overall distribution. It has previously predominantly been...
The success of simple methods for classification shows that is is often not necessary to model complex attribute interactions to obtain good classification accuracy on practical p...
Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhar...
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
Given a binary classification task, a ranker sorts a set of instances from highest to lowest expectation that the instance is positive. We propose a lexicographic ranker, LexRank,...