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Incomplete Information System and Rough Set Theory

Models and Attribute Reductions

, (Autoren)

Buch | Hardcover
XIV, 232 Seiten
2012 | 2012
Springer Berlin (Verlag)
978-3-642-25934-0 (ISBN)
CHF 149,75 inkl. MwSt
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This study of the theory of generalizations of rough-set models in incomplete information systems discusses not only the regular attributes but also the criteria in these systems, and presents practical approaches to computing a number of reducts.

"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.

Part 1 Rough Sets in Complete Information System.- Indiscernibility Relation Based Rough Sets.- Dominance-based Rough Set Approach.- Part 2 Incomplete Information System with Unknown Values.- Generalized Binary Relations Based Rough sets.- Neighborhood Systems and Rough Sets.- Dominance-based Rough Set in incomplete system with "do not care" unknown values.- Dominance-based Rough Set in incomplete system with lost unknown values.- Rough Sets in Generalized Incomplete Information System.- Part 3 Set-valued And Interval-valued Information Systems.- Rough Sets And Dominance-based Rough Sets in Set-valued Information System.- Rough Sets And Dominance-based Rough Sets in Interval-valued Information System.

Erscheint lt. Verlag 7.5.2012
Zusatzinfo XIV, 232 p.
Verlagsort Berlin
Sprache englisch
Maße 155 x 235 mm
Gewicht 473 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Schlagworte attribute reduction • Dominance-based Rough Set • Incomplete Information System • rough set • Rough Set-Theorie • SCIPRESS
ISBN-10 3-642-25934-0 / 3642259340
ISBN-13 978-3-642-25934-0 / 9783642259340
Zustand Neuware
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