Articoli correlati a Relational Knowledge Discovery
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Introductory textbook presenting relational methods in machine learning.
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M. E. Mueller is a Professor of Computer Science at the Bonn-Rhein-Sieg University of Applied Sciences.
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Relational Knowledge Discovery (Lecture Notes on Machine Learning)
Da: Labyrinth Books, Princeton, NJ, U.S.A.
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Relational Knowledge Discovery
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Paperback. Condizione: Brand New. 1st edition. 288 pages. 9.61x6.77x0.63 inches. In Stock. This item is printed on demand. Codice articolo __052112204X
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Relational Knowledge Discovery
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Cambridge University Press, 2012
ISBN 10: 052112204X
ISBN 13: 9780521122047
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Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 550. Codice articolo C9780521122047
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Relational Knowledge Discovery (Lecture Notes on Machine Learning)
Da: California Books, Miami, FL, U.S.A.
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Relational Knowledge Discovery (Lecture Notes on Machine Learning)
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Relational Knowledge Discovery
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. What is knowledge and how is it represented? This introductory textbook presents relational methods in machine learning. Its clear and precise presentation is ideal for undergraduate computer science students and it will also interest those who study artifi. Codice articolo 446926809
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Relational Knowledge Discovery (Lecture Notes on Machine Learning)
Editore:
Cambridge University Press 2012-06-21, 2012
ISBN 10: 052112204X
ISBN 13: 9780521122047
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Da: Chiron Media, Wallingford, Regno Unito
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Paperback. Condizione: New. Codice articolo 6666-IUK-9780521122047
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Relational Knowledge Discovery (Paperback)
Editore:
Cambridge University Press, Cambridge, 2012
ISBN 10: 052112204X
ISBN 13: 9780521122047
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Paperback. Condizione: new. Paperback. What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches. What is knowledge and how is it represented? This introductory textbook presents relational methods in machine learning. Its clear and precise presentation is ideal for undergraduate computer science students and it will also interest those who study artificial intelligence or machine learning at the graduate level. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9780521122047
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Relational Knowledge Discovery
Editore:
Cambridge University Press, 2012
ISBN 10: 052112204X
ISBN 13: 9780521122047
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - What is knowledge and how is it represented This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches. Codice articolo 9780521122047
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Relational Knowledge Discovery (Paperback)
Editore:
Cambridge University Press, Cambridge, 2012
ISBN 10: 052112204X
ISBN 13: 9780521122047
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Paperback
Da: AussieBookSeller, Truganina, VIC, Australia
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Paperback. Condizione: new. Paperback. What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches. What is knowledge and how is it represented? This introductory textbook presents relational methods in machine learning. Its clear and precise presentation is ideal for undergraduate computer science students and it will also interest those who study artificial intelligence or machine learning at the graduate level. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9780521122047
Quantità: 1 disponibili