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Support Vector Machines for Pattern Classification : Advances in Computer Vision and Pattern Recognition - Shigeo Abe

Support Vector Machines for Pattern Classification

Advances in Computer Vision and Pattern Recognition

Hardcover Published: 29th March 2010
ISBN: 9781849960977
Number Of Pages: 473

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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.

From the reviews:

"This broad and deep ... book is organized around the highly significant concept of pattern recognition by support vector machines (SVMs). ... The book is praxis and application oriented but with strong theoretical backing and support. Many ... details are presented and discussed, thereby making the SVM both an easy-to-understand learning machine and a more likable data modeling (mining) tool. Shigeo Abe has produced the book that will become the standard ... . I like it and therefore highly recommend this book ... ." (Vojislav Kecman, SIAM Review, Vol. 48 (2), 2006)

Introduction Two-Class Support Vector Machines Multiclass Support Vector Machines Variants of Support Vector Machines Training Methods Kernel-Based Methods Feature Selection and Extraction Clustering Maximum-Margin Multilayer Neural Networks Maximum-Margin Fuzzy Classifiers Function Approximation.

ISBN: 9781849960977
ISBN-10: 1849960976
Series: Advances in Computer Vision and Pattern Recognition
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 473
Published: 29th March 2010
Publisher: Springer London Ltd
Country of Publication: GB
Dimensions (cm): 23.5 x 15.5  x 3.18
Weight (kg): 1.9
Edition Number: 2
Edition Type: Revised