Isbn: 9781849960977 - support vector machines for pattern classification (15 risultati)

Condizione: New. In English.

Condizione: New.

Condizione: New.

Hardback. Condizione: New. 2nd ed. 2010. Support Vector Machines are popular because of their high classification importance; this is the first book to focus the discussions on SVMs specifically to pattern classification.

Condizione: New. pp. 492 2nd Edition.

Condizione: As New. Unread book in perfect condition.

Hardcover. Condizione: Like New. Like New. book.

Buch. 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.…

Condizione: As New. Unread book in perfect condition.

Hardback. Condizione: New. 2nd ed. 2010. Support Vector Machines are popular because of their high classification importance; this is the first book to focus the discussions on SVMs specifically to pattern classification.

Condizione: new. Questo è un articolo print on demand.

Buch. 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.…

Condizione: 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.…

Condizione: New. Print on Demand pp. 492 144 Illus.

Condizione: New. PRINT ON DEMAND pp. 492.