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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 106,25
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 96,89
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Añadir al carritoCondición: New. In.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 94,13
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 108,46
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 132,76
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 129,82
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 152,41
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Añadir al carritoHardcover. Condición: Brand New. 196 pages. 9.25x6.10x0.63 inches. In Stock.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 160,75
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Idioma: Inglés
Publicado por Springer International Publishing, 2019
ISBN 10: 3030224740 ISBN 13: 9783030224745
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018).Includes new advances in clustering and classification using semi-supervised and unsupervised learning;Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning;Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 184,21
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Añadir al carritoHardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing Sep 2019, 2019
ISBN 10: 3030224740 ISBN 13: 9783030224745
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018).Includes new advances in clustering and classification using semi-supervised and unsupervised learning;Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning;Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning. 196 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing, 2019
ISBN 10: 3030224740 ISBN 13: 9783030224745
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. Includes new advances in clustering and classification using semi-supervised and unsupervised learningAddress new challenges arising in feature extraction and selection using semi-supervised and unsupervised learningFeatures applications from health.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 145,74
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 147,48
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.
Idioma: Inglés
Publicado por Springer, Springer Sep 2019, 2019
ISBN 10: 3030224740 ISBN 13: 9783030224745
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Includes new advances in clustering and classification using semi-supervised and unsupervised learningAddress new challenges arising in feature extraction and selection using semi-supervised and unsupervised learningFeatures applications from business, engineering, and social science that exploit techniques from semi-supervised and unsupervised learningSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 196 pp. Englisch.