Order Total (1 Item Items):
Shipping Destination:
Support Vector Machines Pattern by Abe Shigeo (36 results)
Skip to main search results
Search filters
Product Type
- All Product Types
- Books (36)
- Magazines & Periodicals (No further results match this refinement)
- Comics (No further results match this refinement)
- Sheet Music (No further results match this refinement)
- Art, Prints & Posters (No further results match this refinement)
- Photographs (No further results match this refinement)
- Maps (No further results match this refinement)
- Manuscripts & Paper Collectibles (No further results match this refinement)
Condition Learn more
- New (28)
- As New, Fine or Near Fine (8)
- Very Good or Good (No further results match this refinement)
- Fair or Poor (No further results match this refinement)
- As Described (No further results match this refinement)
Binding
Collectible Attributes
- First Edition (1)
- Signed (No further results match this refinement)
- Dust Jacket (No further results match this refinement)
- Seller-Supplied Images (14)
- Not Print on Demand (28)
Language (1)
Free Shipping
Seller Location
Seller Rating
-
£ 66.81
Convert currencyFree shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketCondition: 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.
-
Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)
Seller: Corner of a Foreign Field, Tokyo, TOKYO, Japan
Seller rating 5 out of 5 stars
First Edition
£ 61.29
Convert currency£ 8.93 shipping from Japan to United KingdomQuantity: 1 available
Add to basketHardcover. Condition: Fine. No Jacket. 1st Edition. 2006.Hardcover.Fine.343 pages.Ships from Japan.Usually ships in 1-2 working days.
-
£ 66.32
Convert currency£ 9.13 shipping from Czech Republic to United KingdomQuantity: 1 available
Add to basketHardcover. Condition: 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.
-
£ 83.94
Convert currency£ 6.69 shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketCondition: New. pp. xiv + 343 1st Edition.
-
£ 90.86
Convert currency£ 6.92 shipping from Germany to United KingdomQuantity: 1 available
Add to basketCondition: New. pp. xiv + 343.
-
Hardcover. Condition: Like New. Like New. book.
-
Support Vector Machines for Pattern Classification
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 139.21
Convert currencyFree shipping within United KingdomQuantity: Over 20 available
Add to basketCondition: New.
-
Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 139.22
Convert currencyFree shipping within United KingdomQuantity: Over 20 available
Add to basketCondition: New. In.
-
£ 111.63
Convert currency£ 32.73 shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketHardcover. Condition: New. In shrink wrap. Looks like an interesting title!
-
£ 134.15
Convert currency£ 14.87 shipping from U.S.A. to United KingdomQuantity: 15 available
Add to basketCondition: New.
-
£ 138.31
Convert currency£ 14.87 shipping from U.S.A. to United KingdomQuantity: Over 20 available
Add to basketCondition: New.
-
£ 149.34
Convert currency£ 12.17 shipping from Germany to United KingdomQuantity: 2 available
Add to basketBuch. Condition: 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.
-
Support Vector Machines for Pattern Classification
Published by Springer London, Springer London, 2012
ISBN 10: 1447125487 ISBN 13: 9781447125488
Language: English
£ 149.34
Convert currency£ 12.17 shipping from Germany to United KingdomQuantity: 1 available
Add to basketTaschenbuch. Condition: 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.
-
Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 164.13
Convert currencyFree shipping within United KingdomQuantity: Over 20 available
Add to basketCondition: New. In.
-
Support Vector Machines for Pattern Classification (Paperback)
Published by Springer London Ltd, England, 2012
ISBN 10: 1447125487 ISBN 13: 9781447125488
Language: English
£ 136.18
Convert currency£ 37.19 shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketPaperback. Condition: new. Paperback. 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. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
-
£ 168.54
Convert currency£ 7.44 shipping from U.S.A. to United KingdomQuantity: Over 20 available
Add to basketCondition: New.
-
Support Vector Machines for Pattern Classification (Hardcover)
Published by Springer London Ltd, England, 2010
ISBN 10: 1849960976 ISBN 13: 9781849960977
Language: English
£ 140.34
Convert currency£ 37.19 shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. 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. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
-
£ 181.25
Convert currency£ 6.69 shipping from U.S.A. to United KingdomQuantity: 4 available
Add to basketCondition: New. pp. 492 2nd Edition.
-
£ 137.11
Convert currency£ 55.78 shipping from U.S.A. to United KingdomQuantity: Over 20 available
Add to basketCondition: New.
-
£ 137.32
Convert currency£ 55.78 shipping from U.S.A. to United KingdomQuantity: Over 20 available
Add to basketCondition: New.
-
Support Vector Machines for Pattern Classification
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 198.99
Convert currencyFree shipping within United KingdomQuantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
-
Paperback. Condition: Like New. Like New. book.
-
Hardcover. Condition: Like New. Like New. book.
-
Support Vector Machines for Pattern Classification
Published by Springer-Verlag New York Inc, 2012
ISBN 10: 1447125487 ISBN 13: 9781447125488
Language: English
Paperback. Condition: Brand New. 2nd edition. 493 pages. 9.25x6.10x1.18 inches. In Stock.
-
£ 225.66
Convert currency£ 14.87 shipping from U.S.A. to United KingdomQuantity: 15 available
Add to basketCondition: As New. Unread book in perfect condition.
-
£ 226.35
Convert currency£ 14.87 shipping from U.S.A. to United KingdomQuantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
-
Support Vector Machines for Pattern Classification (Paperback)
Published by Springer London Ltd, England, 2012
ISBN 10: 1447125487 ISBN 13: 9781447125488
Language: English
£ 244.83
Convert currency£ 27.52 shipping from Australia to United KingdomQuantity: 1 available
Add to basketPaperback. Condition: new. Paperback. 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. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
-
Support Vector Machines for Pattern Classification (Hardcover)
Published by Springer London Ltd, England, 2010
ISBN 10: 1849960976 ISBN 13: 9781849960977
Language: English
£ 269.18
Convert currency£ 27.52 shipping from Australia to United KingdomQuantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. 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. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
-
Condition: New. pp. xiv + 343 Illus. This item is printed on demand.
-
£ 122.04
Convert currency£ 21.75 shipping from Germany to United KingdomQuantity: Over 20 available
Add to basketCondition: 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.
