Abstract—Attribute reduction of information system is one of the most important applications of rough set theory. This paper focuses on generalized decision system and aims at studying positive region reduction and distribution reduction based on generalized indiscernibility relation. The judgment theorems for attribute reductions and attribute reduction approaches are presented. Our approaches improved the existed discernibility matrix and discernibility conditions. Furthermore, the reduction algorithms based on discernible degree are proposed. Keywords—Rough set; generalized indiscernibility relation; positive region reduction; distribution reduction I
AbstractAttribute reduction is one of the key issues in rough set theory. Many heuristic attribute r...
AbstractThe theory of rough set is a new mathematical tool to deal with the uncertain problems, and ...
AbstractFeature selection is a challenging problem in areas such as pattern recognition, machine lea...
AbstractThe theory of rough set is a new mathematical tool to deal with the uncertain problems, and ...
Abstract:- Rough sets theory is an effective mathematical tool dealing with vagueness and uncertaint...
Traditional rough set theory is mainly used to reduce attributes and extract rules in databases in w...
Traditional rough set theory is mainly used to reduce attributes and extract rules in databases in w...
Attribute reduction is one of the most important problems in rough set theory. However, from the gra...
AbstractIn rough set theory, attribute reduction is an important mechanism for knowledge discovery. ...
A rough set approach for attribute reduction is an important research subject in data mining and mac...
In this paper, attribute reduction of incomplete information system is studied. Firstly, optimistic ...
AbstractComputing the core of decision information system and designing efficient relative attributi...
The genetic algorithm is used to optimize the algorithm of attribute reduction in data preprocessing...
This paper proposes the concept of general relation decision systems and studies attribute reduction...
a b s t r a c t An improved discernibility function for rough set based attribute reduction is defin...
AbstractAttribute reduction is one of the key issues in rough set theory. Many heuristic attribute r...
AbstractThe theory of rough set is a new mathematical tool to deal with the uncertain problems, and ...
AbstractFeature selection is a challenging problem in areas such as pattern recognition, machine lea...
AbstractThe theory of rough set is a new mathematical tool to deal with the uncertain problems, and ...
Abstract:- Rough sets theory is an effective mathematical tool dealing with vagueness and uncertaint...
Traditional rough set theory is mainly used to reduce attributes and extract rules in databases in w...
Traditional rough set theory is mainly used to reduce attributes and extract rules in databases in w...
Attribute reduction is one of the most important problems in rough set theory. However, from the gra...
AbstractIn rough set theory, attribute reduction is an important mechanism for knowledge discovery. ...
A rough set approach for attribute reduction is an important research subject in data mining and mac...
In this paper, attribute reduction of incomplete information system is studied. Firstly, optimistic ...
AbstractComputing the core of decision information system and designing efficient relative attributi...
The genetic algorithm is used to optimize the algorithm of attribute reduction in data preprocessing...
This paper proposes the concept of general relation decision systems and studies attribute reduction...
a b s t r a c t An improved discernibility function for rough set based attribute reduction is defin...
AbstractAttribute reduction is one of the key issues in rough set theory. Many heuristic attribute r...
AbstractThe theory of rough set is a new mathematical tool to deal with the uncertain problems, and ...
AbstractFeature selection is a challenging problem in areas such as pattern recognition, machine lea...