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Aggiungi al carrelloHardcover. Condizione: Fine. Leichte Risse. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Da: Corner of a Foreign Field, Tokyo, TOKYO, Giappone
Prima edizione
EUR 71,02
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Aggiungi al carrelloHardcover. Condizione: Fine. No Jacket. 1st Edition. 2006.Hardcover.Fine.343 pages.Ships from Japan.Usually ships in 1-2 working days.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 85,14
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Aggiungi al carrelloBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Condizione: New. pp. xiv + 343 1st Edition.
EUR 105,72
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Aggiungi al carrelloCondizione: New. pp. xiv + 343.
Hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 158,89
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EUR 160,33
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 159,14
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Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 137,57
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Aggiungi al carrelloHardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 157,71
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 157,70
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 192,99
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Aggiungi al carrelloCondizione: New. In.
Condizione: New. pp. 492 2nd Edition.
Condizione: New. pp. 492 2nd Edition.
EUR 141,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Support Vector Machines for Pattern Classification | Shigeo Abe | Taschenbuch | xx | Englisch | 2012 | Springer | EAN 9781447125488 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 228,21
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Aggiungi al carrelloHardback. Condizione: New. 2nd ed. 2010. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
Editore: Springer London, Springer London, 2012
ISBN 10: 1447125487 ISBN 13: 9781447125488
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 166,62
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
EUR 166,62
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 233,98
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Editore: Springer-Verlag New York Inc, 2012
ISBN 10: 1447125487 ISBN 13: 9781447125488
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 236,44
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 2nd edition. 493 pages. 9.25x6.10x1.18 inches. In Stock.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 224,59
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 224,59
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Aggiungi al carrelloHardcover. Condizione: Like New. Like New. book.
EUR 256,67
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EUR 217,50
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Aggiungi al carrelloHardback. Condizione: New. 2nd ed. 2010. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
Da: Majestic Books, Hounslow, Regno Unito
EUR 104,80
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. xiv + 343 Illus. This item is printed on demand.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 160,49
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors. 492 pp. Englisch.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 160,49
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors. 473 pp. Englisch.
Da: moluna, Greven, Germania
EUR 136,16
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A comprehensive resource for the use of Support Vector Machines in Pattern ClassificationTakes the unique approach of focussing on classification rather than covering the theoretical aspects of Support Vector MachinesIncludes application of.