Support Vector Machines for Pattern Classification 2010 Edition Contributor(s): Abe, Shigeo (Author) |
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ISBN: 1849960976 ISBN-13: 9781849960977 Publisher: Springer OUR PRICE: $161.49 Product Type: Hardcover - Other Formats Published: March 2010 |
Additional Information |
BISAC Categories: - Computers | Computer Vision & Pattern Recognition - Computers | Document Management - Technology & Engineering | Robotics |
Dewey: 005.52 |
LCCN: 2010920369 |
Series: Advances in Pattern Recognition |
Physical Information: 1.06" H x 6.14" W x 9.21" (1.90 lbs) 473 pages |
Descriptions, Reviews, Etc. |
Publisher 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. |