Support Vector Machines for Pattern Classification

€ 171,99
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Juli 2010



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.


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



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)

EAN: 9781849960984
Untertitel: 2nd ed. 2010. 114 schwarz-weiße Abbildungen, 89 schwarz-weiße Tabellen, Bibliographie. eBook. Sprache: Englisch. Dateigröße in MByte: 6.
Verlag: Springer London
Erscheinungsdatum: Juli 2010
Seitenanzahl: xx473
Format: pdf eBook
Kopierschutz: Adobe DRM
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