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Introduction Learning Classifier Systems by Urbanowicz Ryan (16 results)
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Introduction to Learning Classifier Systems (SpringerBriefs in Intelligent Systems)
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Introduction to Learning Classifier Systems
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Introduction to Learning Classifier Systems
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Introduction to Learning Classifier Systems
Published by Springer-Verlag New York Inc, 2017
ISBN 10: 3662550067 ISBN 13: 9783662550069
Language: English
Paperback. Condition: Brand New. 123 pages. 9.00x6.00x0.25 inches. In Stock.
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Taschenbuch. Condition: Neu. Introduction to Learning Classifier Systems | Ryan J. Urbanowicz (u. a.) | Taschenbuch | xiii | Englisch | 2017 | Springer | EAN 9783662550069 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Introduction to Learning Classifier Systems
Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2017
ISBN 10: 3662550067 ISBN 13: 9783662550069
Language: English
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This accessible introduction shows the reader how to understand, implement, adapt, and apply Learning Classifier Systems (LCSs) to interesting and difficult problems. The text builds an understanding from basic ideas and concepts. The authors first explore learning through environment interaction, and then walk through the components of LCS that form this rule-based evolutionary algorithm. The applicability and adaptability of these methods is highlighted by providing descriptions of common methodological alternatives for different components that are suited to different types of problems from data mining to autonomous robotics. The authors have also paired exercises and a simple educational LCS (eLCS) algorithm (implemented in Python) with this book. It is suitable for courses or self-study by advanced undergraduate and postgraduate students in subjects such as Computer Science, Engineering, Bioinformatics, and Cybernetics, and by researchers, data analysts, andmachine learning practitioners.
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Paperback. Condition: New. New. book.
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Introduction to Learning Classifier Systems
Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2017
ISBN 10: 3662550067 ISBN 13: 9783662550069
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This accessible introduction shows the reader how to understand, implement, adapt, and apply Learning Classifier Systems (LCSs) to interesting and difficult problems. The text builds an understanding from basic ideas and concepts. The authors first explore learning through environment interaction, and then walk through the components of LCS that form this rule-based evolutionary algorithm. The applicability and adaptability of these methods is highlighted by providing descriptions of common methodological alternatives for different components that are suited to different types of problems from data mining to autonomous robotics. The authors have also paired exercises and a simple educational LCS (eLCS) algorithm (implemented in Python) with this book. It is suitable for courses or self-study by advanced undergraduate and postgraduate students in subjects such as Computer Science, Engineering, Bioinformatics, and Cybernetics, and by researchers, data analysts, andmachine learning practitioners. 123 pp. Englisch.
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Condition: New. Print on Demand.
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Condition: New. PRINT ON DEMAND.
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Introduction to Learning Classifier Systems
Published by Springer Berlin Heidelberg, 2017
ISBN 10: 3662550067 ISBN 13: 9783662550069
Language: English
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Ryan Urbanowicz is a postdoctoral research associate in the Dept. of Biostatistics, Epidemiology, and Informatics in the Perelman School of Medicine at the University of Pennsylvania. He received his PhD in Genetics from Dartmouth College, and a B.S. and.
