Subgroup discovery aims at finding interesting subsets of a classified example set that deviates from the overall distribution. The search is guided by a so-called utility function...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
A correlation-based similarity measure is derived for generalized relevance learning vector quantization (GRLVQ). The resulting GRLVQ-C classifier makes Pearson correlation availa...
Marc Strickert, Udo Seiffert, Nese Sreenivasulu, W...
We describe the implementation of an interaction technique which allows users to store and retrieve information and computational functionality on different parts of their body. W...
Steven Strachan, Roderick Murray-Smith, Ian Oakley...