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Incomplete Information System and Rough Set Theory: Models and Attribute Reductions
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Incomplete Information System and Rough Set Theory: Models and Attribute Reductions (Hardback)

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Synopsis

"Incomplete Information System and Rough Set Theory: Models and Attribute Reductions" covers theoretical study of generalizations of rough set model in various incomplete information systems. It discusses not only the regular attributes but also the criteria in the incomplete information systems. Based on different types of rough set models, the book presents the practical approaches to compute several reducts in terms of these models. The book is intended for researchers and postgraduate students in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, and granular computing.



Dr. Xibei Yang is a lecturer at the School of Computer Science and Engineering, Jiangsu University of Science and Technology, China; Jingyu Yang is a professor at the School of Computer Science, Nanjing University of Science and Technology, China.

Computing & ITComputer scienceArtificial intelligenceMachine learningComputing & ITComputer scienceMathematical theory of computationComputing & ITDatabasesData miningScience & MathematicsMathematicsScience & MathematicsMathematicsMathematical foundationsMathematical logic Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Publication Date: 07/05/2012 ISBN-13: 9783642259340  Details: Type: Hardback Format: Books
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