Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
In rough set approaches, rules infering the membership of a single class have been induced, while rules infering the membership of a union of classes can also be induced in the same way. It is demonstrated that the classifier based on rules with unions of classes outperforms that based on single class rules. In this paper, from this fact, we investigate the way of building the classifier with a better performance based on rough set rule induction. Through numerical experiments, we show the effectiveness of union rule induction and the multiplication of explicable rule sets.
