Transactions on Rough Sets XIII (eBook, PDF)
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The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.Volume XIII contains 14 papers which introduce a number of new advances in both the foundations and the applications of rough sets. These are mathematical structur...
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.
Volume XIII contains 14 papers which introduce a number of new advances in both the foundations and the applications of rough sets. These are mathematical structures of generalized rough sets in infinite universes, approximations of arbitrary binary relations, and attribute reduction in decision-theoretic rough sets. Methodological advances introduce rough set-based and hybrid methodologies for learning theory, attribution reduction, decision analysis, risk assessment, and data mining tasks such as classification and clustering. In addition, this volume contains regular articles on mining temporal software metrics data, C-GAME discretization method, perceptual tolerance intersection as an example of a near set operation and compression of spatial data with quadtree structures.
Volume XIII contains 14 papers which introduce a number of new advances in both the foundations and the applications of rough sets. These are mathematical structures of generalized rough sets in infinite universes, approximations of arbitrary binary relations, and attribute reduction in decision-theoretic rough sets. Methodological advances introduce rough set-based and hybrid methodologies for learning theory, attribution reduction, decision analysis, risk assessment, and data mining tasks such as classification and clustering. In addition, this volume contains regular articles on mining temporal software metrics data, C-GAME discretization method, perceptual tolerance intersection as an example of a near set operation and compression of spatial data with quadtree structures.
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