Abstract
Recently, the applications of rough set theory to real problems have been studied actively. However, when the number of induced decision rules by rough set approach is large, finding useful decision rules becomes often a formidable task. This fact may become a bottlenek in actual use of induced decision rules. In this study, we develop the decision rule visualization system for supporting the discovery of useful decision rules. The system visualizes decision rules having same conclusions in three-dimensional space using co-occurrence rates between atomic formulae and conclusions, those between atomic formulae and Hayashi's quantification method IV. An evaluation experiment is conducted. The results show that useful decision rules are discovered efficiently from many decision rules induced by the rough set approach. Some additional functions are implemented to the system in order to overcome the problems pointed out by examinees.
