Téléchargez le livre : Support Vector Machines for Pattern Classification

Support Vector Machines for Pattern Classification



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Éditeur :

Springer


Collection :

Advances in Computer Vision and Pattern Recognition

Paru le : 2010-07-23



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Description
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.
Pages
473 pages
Collection
Advances in Computer Vision and Pattern Recognition
Parution
2010-07-23
Marque
Springer
EAN papier
9781849960977
EAN EPUB
9781849960984
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
47
Taille du fichier
4751 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
147,69 €

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