We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Abstract. This article introduces structural aspects in an ontology of approximate reason. The basic assumption in this ontology is that approximate reason is a capability of an ag...
James F. Peters, Andrzej Skowron, Jaroslaw Stepani...
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...
1 In web-related applications of image categorization, it is desirable to derive an interpretable classification rule with high accuracy. Using the bag-of-words representation and...
Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku K...