2012/09/25 by Bin Yang, Yang, Bin, William Zhu +1
Computer Science · #Artificial Intelligence (cs.AI) #Data Mining Algorithms and Applications #FOS: Computer and information sciences #I.2.3 #Rough Sets and Fuzzy Logic
paper · pdf · doi:10.48550/arxiv.1209.5470
openalex publication_date 2012/09/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Rough sets are efficient for data pre-process in data mining. Lower and upper approximations are two core concepts of rough sets. This paper studies generalized rough sets based on symmetric and transitive relations from the operator-oriented view by matroidal approaches. We firstly construct a matroidal structure of generalized rough sets based on symmetric and transitive relations, and provide an approach to study the matroid induced by a symmetric and transitive relation. Secondly, this paper establishes a close relationship between matroids and generalized rough sets. Approximation quality and roughness of generalized rough sets can be computed by the circuit of matroid theory. At last, a symmetric and transitive relation can be constructed by a matroid with some special properties.