An Incremental Rule Acquisition Algorithm Based on Rough Set

摘要

Rough Set is a valid mathematical theory developed in recent years, which has the ability to deal with imprecise, uncertain, and vague information. This paper presents a new incremental rule acquisition algorithm based on rough set theory. First, the relation of the new instances with the original rule set is discussed. Then the change law of attribute reduction and value reduction are studied when a new instance is added. Follow, a new incremental learning algorithm for decision tables is presented within the framework of rough set. Finally, the new algorithm and the classical algorithm are analyzed and compared by theory and experiments.