Abstract
As a quantitative index of processing uncertain information by rough set theory, roughness measure is the basis of many decision-making problems such as resource management, system optimization etc. Therefore constructing roughness measure reflecting different decision preference has important theoretical and practical value. In this paper, we first analyze the characteristics and deficiencies of Pawlak roughness, and further propose the concepts of lower (upper) accuracy. We second establish an description ability-based roughness measure (DRD) by combining with two basic measure factors-lower (upper) accuracy. We third analyze the characteristics of DRD and further give some sufficient and necessary conditions. Finally, we propose a DRD-based reduction method (DRD-RM), and discuss the difference and relation between DRD-RM and the existing reduction methods by experimental analysis for UCI data. The experimental results show that DRD-RM is an effective technique.
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