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...
We describe a (meta) formalism for defining a variety of (object oriented) data models in a unified framework based on a variation of first-order logic. As specific example we use...
The instance-based k-nearest neighbor algorithm (KNN)[1] is an effective classification model. Its classification is simply based on a vote within the neighborhood, consisting o...
Abstract. We present The Cruncher, a simple representation framework and algorithm based on minimum description length for automatically forming an ontology of concepts from attrib...
For some years, data summarization techniques have been developed to handle the growth of databases. However these techniques are usually not provided with tools for enduserstoeffi...
W. Amenel Voglozin, Guillaume Raschia, Laurent Ugh...