We study cost-sensitive learning of decision trees that incorporate both test costs and misclassification costs. In particular, we first propose a lazy decision tree learning that ...
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...
The benefit of incorporating background knowledge in the learning process has been successfully demonstrated in numerous applications of ILP methods. Nevertheless the effect of inc...
Intentional behavior is a basic property of intelligence and it incorporates the cyclic operation of prediction, testing by action, sensing, perceiving, and assimilating the exper...
Robert Kozma, Terry Huntsberger, Hrand Aghazarian,...
Abstract. A variant of iterative learning in the limit (cf. [LZ96]) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target la...