In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
Within the last two decades, Receiver Operating Characteristic (ROC) Curves have become a standard tool for the analysis and comparison of classifiers since they provide a conveni...
Stephan M. Winkler, Michael Affenzeller, Stefan Wa...
Abstract. Robustly estimating the state-transition probabilities of highorder Markov processes is an essential task in many applications such as natural language modeling or protei...