: The performance of a statistical machine translation (SMT) system heavily depends on the quantity and quality of the bilingual language resource. However, the pervious work mainl...
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
This paper solves an important problem left open in the literature by showing that U-shapes are unnecessary in iterative learning. A U-shape occurs when a learner first learns, t...
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...