Editore: Springer International Publishing, 2017
ISBN 10: 3319571133 ISBN 13: 9783319571133
Lingua: Inglese
Da: Buchpark, Trebbin, Germania
Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 248 | Sprache: Englisch | Produktart: Bücher.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 157,39
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Editore: Springer International Publishing, Springer International Publishing Jul 2018, 2018
ISBN 10: 3319860798 ISBN 13: 9783319860794
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 149,79
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,.The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions forfuture research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 248 pp. Englisch.
Editore: Springer Nature Switzerland, Springer International Publishing Mai 2017, 2017
ISBN 10: 3319571133 ISBN 13: 9783319571133
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 149,79
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware -This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,.The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions forfuture research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 248 pp. Englisch.
Editore: Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319860798 ISBN 13: 9783319860794
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 149,79
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses theformation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting inefficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,.The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application.It covers the latest findings as well as directions forfuture research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering,data science, system design, pattern recognition,image analysis,neural computing, social network analysis, big data analytics, computational biology and soft computing.
Editore: Springer International Publishing, 2017
ISBN 10: 3319571133 ISBN 13: 9783319571133
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 149,79
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses theformation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting inefficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,.The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application.It covers the latest findings as well as directions forfuture research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering,data science, system design, pattern recognition,image analysis,neural computing, social network analysis, big data analytics, computational biology and soft computing.
Da: California Books, Miami, FL, U.S.A.
EUR 186,59
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Da: Books Puddle, New York, NY, U.S.A.
EUR 210,69
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Aggiungi al carrelloCondizione: New. pp. 246.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 151,23
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 151,57
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Da: Books Puddle, New York, NY, U.S.A.
EUR 212,92
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Da: Revaluation Books, Exeter, Regno Unito
EUR 224,45
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Aggiungi al carrelloHardcover. Condizione: Brand New. 227 pages. 9.25x6.25x0.75 inches. In Stock.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 218,71
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Aggiungi al carrelloHardcover. Condizione: New. New. book.
Editore: Springer International Publishing, 2017
ISBN 10: 3319571133 ISBN 13: 9783319571133
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 127,40
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a unified framework describing how fuzzy rough granular neural network technologies can be judiciously formulated and used in building efficient pattern recognition modelsIs structured according to the major phases of a pattern recognitio.
Editore: Springer International Publishing, 2018
ISBN 10: 3319860798 ISBN 13: 9783319860794
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 127,40
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a unified framework describing how fuzzy rough granular neural network technologies can be judiciously formulated and used in building efficient pattern recognition modelsIs structured according to the major phases of a pattern recognitio.
Editore: Springer International Publishing Jul 2018, 2018
ISBN 10: 3319860798 ISBN 13: 9783319860794
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 149,79
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses theformation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting inefficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,.The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application.It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering,data science, system design, pattern recognition,image analysis,neural computing, social network analysis, big data analytics, computational biology and soft computing. 248 pp. Englisch.
Editore: Springer International Publishing Mai 2017, 2017
ISBN 10: 3319571133 ISBN 13: 9783319571133
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 149,79
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses theformation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting inefficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,.The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application.It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering,data science, system design, pattern recognition,image analysis,neural computing, social network analysis, big data analytics, computational biology and soft computing. 248 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 217,37
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 246.
Da: Majestic Books, Hounslow, Regno Unito
EUR 218,31
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 223,89
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 246.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 225,72
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.