Librería: SpringBooks, Berlin, Alemania
Original o primera edición
EUR 35,00
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Añadir al carritoHardcover. Condición: Very Good. 1. Auflage. unread, with a mimimum of shelfwear.
Publicado por Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3030078620 ISBN 13: 9783030078621
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.Provides multiple examples to facilitate the understanding data streams in non-stationary environments;Presents several application cases to show how the methods solve different real world problems;Discusses the links between methods to help stimulate new research and application directions.
Publicado por Springer International Publishing, 2018
ISBN 10: 3319898027 ISBN 13: 9783319898025
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.Provides multiple examples to facilitate the understanding data streams in non-stationary environments;Presents several application cases to show how the methods solve different real world problems;Discusses the links between methods to help stimulate new research and application directions.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 119,33
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Añadir al carritoCondición: New. In.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 124,42
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Añadir al carritoCondición: New. In.
Publicado por Springer International Publishing, Springer International Publishing Dez 2018, 2018
ISBN 10: 3030078620 ISBN 13: 9783030078621
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.Provides multiple examples to facilitate the understanding data streams in non-stationary environments;Presents several application cases to show how the methods solve different real world problems;Discusses the links between methods to help stimulate new research and application directions.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 328 pp. Englisch.
Publicado por Springer International Publishing, Springer International Publishing Aug 2018, 2018
ISBN 10: 3319898027 ISBN 13: 9783319898025
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. Neuware -This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.Provides multiple examples to facilitate the understanding data streams in non-stationary environments;Presents several application cases to show how the methods solve different real world problems;Discusses the links between methods to help stimulate new research and application directions.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 328 pp. Englisch.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 154,86
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Añadir al carritoCondición: New.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 157,78
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Añadir al carritoHardcover. Condición: Brand New. 328 pages. 9.25x6.10x1.02 inches. In Stock.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 167,46
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Añadir al carritoPaperback. Condición: New. New. book.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 160,16
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Añadir al carritoCondición: New.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 217,24
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Añadir al carritoHardcover. Condición: Brand New. 212 pages. 9.75x6.75x0.75 inches. In Stock.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 240,81
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Añadir al carritoHardcover. Condición: Like New. Like New. book.
Publicado por Springer International Publishing, 2018
ISBN 10: 3030078620 ISBN 13: 9783030078621
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 92,27
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides multiple examples to facilitate the understanding data streams in non-stationary environmentsPresents several application cases to show how the methods solve different real world problemsDiscusses the links between methods t.
Publicado por Springer International Publishing, 2018
ISBN 10: 3319898027 ISBN 13: 9783319898025
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 92,27
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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. Provides multiple examples to facilitate the understanding data streams in non-stationary environmentsPresents several application cases to show how the methods solve different real world problemsDiscusses the links between methods t.
Publicado por Springer International Publishing Dez 2018, 2018
ISBN 10: 3030078620 ISBN 13: 9783030078621
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.Provides multiple examples to facilitate the understanding data streams in non-stationary environments;Presents several application cases to show how the methods solve different real world problems;Discusses the links between methods to help stimulate new research and application directions. 328 pp. Englisch.
Publicado por Springer International Publishing Aug 2018, 2018
ISBN 10: 3319898027 ISBN 13: 9783319898025
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.Provides multiple examples to facilitate the understanding data streams in non-stationary environments;Presents several application cases to show how the methods solve different real world problems;Discusses the links between methods to help stimulate new research and application directions. 328 pp. Englisch.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 125,51
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Añadir al carritoHRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 130,32
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 144,52
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Añadir al carritoHardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 574.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 157,69
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,92
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is a significant contribution to the subject of mining time-changing data streams and addresses the design of learning algorithms for this purpose. It introduces new contributions on several different aspects of the problem, identifying research opportunities and increasing the scope for applications. It also includes an in-depth study of stream mining and a theoretical analysis of proposed methods and algorithms. The first section is concerned with the use of an adaptive sliding window algorithm (ADWIN). Since this has rigorous performance guarantees, using it in place of counters or accumulators, it offers the possibility of extending such guarantees to learning and mining algorithms not initially designed for drifting data. Testing with several methods, including Naïve Bayes, clustering, decision trees and ensemble methods, is discussed as well. The second part of the book describes a formal study of connected acyclic graphs, or 'trees', from the point of view of closure-based mining, presenting efficient algorithms for subtree testing and for mining ordered and unordered frequent closed trees. Lastly, a general methodology to identify closed patterns in a data stream is outlined. This is applied to develop an incremental method, a sliding-window based method, and a method that mines closed trees adaptively from data streams. These are used to introduce classification methods for tree data streams.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 162,53
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Añadir al carritoCondición: New. PRINT ON DEMAND.