Double-quantitative rough approximation,containing two types of quantitative information,indicated stronger generalization ability and more accurate data processing capacity than the single-quantitative rough approxim...Double-quantitative rough approximation,containing two types of quantitative information,indicated stronger generalization ability and more accurate data processing capacity than the single-quantitative rough approximation.In this paper,the neighborhood-based double-quantitative rough set models are firstly presented in a set-valued information system.Secondly,the attribute reduction method based on the lower approximation invariant is addressed,and the relevant algorithm for the approximation attribute reduction is provided in the set-valued information system.Finally,to illustrate the superiority and the effectiveness of the proposed reduction approach,experimental evaluation is performed using three datasets coming from the University of California-Irvine(UCI)repository.展开更多
基金Supported by the College Students Innovation and Entrepreneurship Training Program project(Grant No.101202010635586)National Natural Science Foundation of China(Grant No.61772002,61976245)+2 种基金Fundamental Research Funds for the Central Universities(Grant No.SWU119063)Scientific and Technological Project of Construction of Double City Economic Circle in Chengdu-Chongqing Area(Grant No.KJCX2020009)Science and Technology Research Program of Chongqing Education Commission(Grant No.KJQN202003806)。
文摘Double-quantitative rough approximation,containing two types of quantitative information,indicated stronger generalization ability and more accurate data processing capacity than the single-quantitative rough approximation.In this paper,the neighborhood-based double-quantitative rough set models are firstly presented in a set-valued information system.Secondly,the attribute reduction method based on the lower approximation invariant is addressed,and the relevant algorithm for the approximation attribute reduction is provided in the set-valued information system.Finally,to illustrate the superiority and the effectiveness of the proposed reduction approach,experimental evaluation is performed using three datasets coming from the University of California-Irvine(UCI)repository.
