Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 84,99
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Añadir al carritoCondición: New. In.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 99,52
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Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 84,98
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Añadir al carritoCondición: New.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 112,99
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. pp. 354.
Idioma: Inglés
Publicado por Springer-Verlag New York Inc, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Librería: Revaluation Books, Exeter, Reino Unido
EUR 121,79
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Añadir al carritoHardcover. Condición: Brand New. 2012 edition. 353 pages. 9.00x6.25x0.80 inches. In Stock.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 80,24
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: 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.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 145,45
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 135,93
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Añadir al carritoHardcover. Condición: Like New. Like New. book.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 167,54
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 66,23
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg Nov 2012, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 80,24
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Librería: moluna, Greven, Alemania
EUR 70,33
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Añadir al carritoGebunden. Condición: 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 .
Librería: Majestic Books, Hounslow, Reino Unido
EUR 115,20
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand pp. 354 94 Illus.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 114,88
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND pp. 354.
Idioma: Inglés
Publicado por Springer, Springer Nov 2012, 2012
ISBN 10: 3540751963 ISBN 13: 9783540751960
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 80,24
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: 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.