Incomplete Information System and Rough Set Theory: Models and Attribute Reductions

Format Electronic
Publication InfoNew York : Springer La Vergne : MyiLibrary [Distributor]
Description238 p.
Supplemental ContentFull text available from Springer Nature - Springer Computer Science eBooks 2012 English International
Supplemental ContentFull text available from Springer Books

Summary Annotation '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.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
ISBN9781283934886
ISBN1283934884 (E-Book) Active Record
Standard identifier# 9781283934886
Stock number00024965

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