This paper reviews probabilistic approaches to rough sets in granulation, approximation, and rule induction. The Shannon entropy function is used to quantitatively characterize pa...
The original rough-set model is primarily concerned with the approximations of sets described by a single equivalence relation on a given universe. With granular computing point of...
Abstract. Subsystem based generalizations of rough set approximations are investigated. Instead of using an equivalence relation, an arbitrary binary relation is used to construct ...
Abstract. Many learning methods ignore domain knowledge in synthesis of concept approximation. We propose to use hierarchical schemes for learning approximations of complex concept...
Jan G. Bazan, Sinh Hoa Nguyen, Hung Son Nguyen, An...
An attribute-oriented rough set method for knowledgediscovery in databases is described. Themethodis based on information generalization, whichexaminesthe data at various levels o...
Ning Shan, Wojciech Ziarko, Howard J. Hamilton, Ni...