Abstract. We present a rough set approach to vague concept approximation within the adaptive learning framework. In particular, the role of extensions of approximation spaces in se...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
The idea of using computer-based surgical simulators for training of prospective surgeons has been a topic of research for more than a decade. However, surgical simulation is still...
Raimundo Sierra, Michael Bajka, Celalettin Karadog...
The general dimension is a combinatorial measure that characterizes the number of queries needed to learn a concept class. We use this notion to show that any p-evaluatable concep...
This paper proposes a framework to learn concepts from di erent kinds of observations. We de ne a language to describe meta-concepts, that represent the sets of possible concepts ...