Induction of Condensed Determinations

In this paper we suggest determinations as a representation of knowledge that should be easy to understand. We brieey review determinations, which can be displayed in a tabular format, and their use in prediction , which involves a simple matching process. We describe ConDet, an algorithm that uses feature selection to construct determinations from training data, augmented by a condensation process that collapses rows to produce simpler structures. We report experiments that show condensation reduces complexity with no loss of accuracy, then discuss ConDet's relation to other work and outline directions for future studies.