The main task of granular computing (GrC) is about representing, constructing, and
processing information granules. Information granules are formalized in many different …

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A rough set approximates a subset of a universal set on the basis of some binary relation
and is significant for the reduction of attributes of an information system. On the other hand, a …

Probabilistic approaches have been applied to the theory of rough set in several forms,
including decision-theoretic analysis, variable precision analysis, and information-theoretic …

The basic ideas and principles of granular computing (GrC) have been studied explicitly or
implicitly in many fields in isolation. With the recent renewed and fast growing interest, it is …

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 …

Granular computing and knowledge reduction are two basic issues in knowledge
representation and data mining. Granular structure of concept lattices with application in …

Granular computing and acquisition of if-then rules are two basic issues in knowledge
representation and data mining. A formal approach to granular computing with multi-scale …

Decision-theoretic rough set provides a new perspective to handle decision-making
problems under uncertainty and risk. The three-way decision theory proposed by Yao is …

Feature subset selection has become an important challenge in areas of pattern recognition,
machine learning and data mining. As different semantics are hidden in numerical and …