There is much empirical evidence about the success of naive Bayesian classification (NBC) in medical applications of attribute-based machine learning. NBC assumes conditional inde...
Aleks Jakulin, Ivan Bratko, Dragica Smrke, Janez D...
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance b...
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh
Abstract. E-Learning grows on the fertile soil of the Internet technologies; it fails, however, to reach their full potential. With new, emerging technologies of the second generat...
Sebastian Ryszard Kruk, Adam Gzella, Jaroslaw Dobr...