Incrementally Updating Method in Dominance- Based Rough Set Approach

Yan LI, Xiaoqing LIU, Jiajia HOU

Key Lab. In Machine Learning and Computational Intelligence, College of Mathematics and Computer Science, Hebei University, Baoding City, Hebei Province, China

Abstract: Dominance-based rough set approach (DRSA) can handle the attributes with preference orders, and therefore it has been widely applied in multi-criteria decision making problems. In real applications, the collected information is updated from time to time which results in dynamic information systems, especially when the attributes ｏｒ objects are inserted ｏｒ deleted. The traditional DRSA needs to ｕｐｄａｔｅ the set approximations whenever the information systems change, which decreases the method efficiency greatly. For classification problems with multiple criteria, this paper presents incremental algorithms to ｕｐｄａｔｅ set approximations when an object is inserted ｏｒ deleted, which is expected to be more efficient than computing the approximations from the scratch. The related theoretical results are presented with proofs, and illustrative examples are also given to support the effectiveness of the proposed incremental method.

Keywords: Rough Set; Dominance Relation; Set Approximation; Dynamic Information Systems; Incremental ｕｐｄａｔｅ