Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 85,01
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Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 99,48
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 85,00
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Aggiungi al carrelloCondizione: New.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 354.
Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Da: Revaluation Books, Exeter, Regno Unito
EUR 121,74
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 2012 edition. 353 pages. 9.00x6.25x0.80 inches. In Stock.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 80,24
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Rules - the clearest, most explored and best understood form of knowledge representation - are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning.The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 145,48
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 135,95
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: Like New. Like New. book.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 168,53
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 66,23
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Berlin Heidelberg Nov 2012, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 80,24
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Rules - the clearest, most explored and best understood form of knowledge representation - are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning.The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data. 352 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 115,82
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand pp. 354 94 Illus.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Da: moluna, Greven, Germania
EUR 70,33
Quantità: Più di 20 disponibili
Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fills a significant gap in the machine learning literatureExplains the most comprehensive knowledge representation formalismOffers researchers and graduate students a clear unifying terminologyProf. Dr. Johannes Fuernkranz .
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 114,88
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 354.
Lingua: Inglese
Editore: Springer, Springer Nov 2012, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 80,24
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Rules ¿ the clearest, most explored and best understood form of knowledge representation ¿ are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning.The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 352 pp. Englisch.