Abstract
Attribute reduction is one of the core contents in the theoretical research of rough sets. However, the inefficiency of attribute reduction algorithms limits the application of rough set. In this paper, we first point out some problems existing in the significance measure of attribute. Then a new measure, that is relative discernibility degree, is presented and proven to have the monotonicity property. Finally, a simplified consistent decision table is defined, based on which an efficient attribute reduction algorithm is designed. Theoretical analysis and experimental results show the effectiveness and practicability of this algorithm on the UCI data sets.
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