Incomplete Information Rough Set (36 results)

Hardcover. Condition: Very Good. pp.xii, 613 pages, a very good plus hardback, publisher's original orange and brown binding with white and brown lettering to the spine and front cover - as shown in the stock photo [3790810495].

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Condition: As New. Unread book in perfect condition.

Condition: New.

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Softcover. Octavo, xii, 613 pages. In Very Good condition. Spine is tan with white and brown print. Illustrated: b&w "With 54 Figures and 23 Tables"- title page. NOTE: Shelved in Netdesk Column I (ND-I). 1379442. FP New Rockville Stock.

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hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

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Condition: New. pp. xiv + 232.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - '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.…

Hardcover. Condition: Brand New. 2012 edition. 246 pages. 9.50x6.25x0.75 inches. In Stock.

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Taschenbuch. Condition: Neu. Incomplete Information: Rough Set Analysis | Ewa Orlowska | Taschenbuch | Studies in Fuzziness and Soft Computing | xii | Englisch | 2010 | Physica | EAN 9783790824575 | Verantwortliche Person für die EU: Physica Verlag in Springer Science + Business Media, Tiergartenstr. 15-17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Condition: New.

Condition: New. An up-to-date and highly authoritative account of the current status of the basic theory, extensions and applications of rough setsA must reading for anyone who has a serious interest in information processing and knowledge-based systemsIn 1982, Pro.

Condition: Sehr gut. Zustand: Sehr gut | Seiten: 613 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Condition: Sehr gut. Zustand: Sehr gut | Seiten: 613 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Condition: New.

hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Buch. Condition: Neu. Neuware - In 1982, Professor Pawlak published his seminal paper on what he called 'rough sets' - a work which opened a new direction in the development of theories of incomplete information. Today, a decade and a half later, the theory of rough sets has evolved into a far-reaching methodology for dealing with a wide variety of issues centering on incompleteness and imprecision of information - issues which playa key role in the conception and design of intelligent information systems. 'Incomplete Information: Rough Set Analysis' - or RSA for short - presents an up-to-date and highly authoritative account of the current status of the basic theory, its many extensions and wide-ranging applications. Edited by Professor Ewa Orlowska, one of the leading contributors to the theory of rough sets, RSA is a collection of nineteen well-integrated chapters authored by experts in rough set theory and related fields. A common thread that runs through these chapters ties the concept of incompleteness of information to those of indiscernibility and similarity.; The book presents rough set formalisms and methods of modeling and handling incomplete information and motivates their applicability to knowledge representation, knowledge discovery and machine learning. The book focuses on providing representational and inference mechanisms for dealing with two particular aspects of incompleteness, namely indiscernibility and similarity. Those manifestations of particular aspects of incompleteness are inherent in any data structure and any cognitive unit. Knowledge discovered from such an information is uncertain in that it can only be asserted with a tolerance. The methods developed in the book are capable of exposing the limits of that tolerance and of making reliable inferences in the environments where complete information is not available.…

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

paperback. Condition: New. Language:Chinese.Paperback. Publisher : Nanjing University.

paperback. Condition: New. Paperback. Pages Number The: 232 Language: English. Incomplete Information System and Rough Set Theory: Models and the Attribute Re-ductions provides evidence of the present growth in the rough set approach to the incom-plete information system at The topics discussed in this book have received significant attentions in recent years because researchers can apply new tools for problem solv-ing. This book reflects a number of approaches those were either directly or indirectly begun by the semi.…

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'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. 232 pp. Englisch.…

Condition: new. Questo è un articolo print on demand.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Considers not only the regular attributes but also the criteria in the incomplete information systemsPresents most of the important rough set models in the incomplete information systemsAddresses the practical approaches to compute reducts .…