A GENERALIZED ROUGH SET APPROACH TO ATTRIBUTE GENERALIZATION IN DATA MINING

摘要

This paper presents a generalized method for updating approximations of a concept incrementally, which can be used as an effective tool to deal with dynamic attribute generalization. By combining this method and the LERS inductive learning algorithm, it also introduces a generalized quasi-incremental algorithm for learning classification rules from data bases.