Support Vector Machines for Pattern Classification
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ISBN-13:
9781849960977
Veröffentl:
2010
Erscheinungsdatum:
29.03.2010
Seiten:
473
Autor:
Shigeo Abe
Gewicht:
870 g
Format:
242x164x38 mm
Sprache:
Englisch
Beschreibung:
Originally formulated for two-class classification problems, support vector machines (SVMs) are now accepted as powerful tools for developing pattern classification and function approximation systems. Recent developments in kernel-based methods include kernel classifiers and regressors and their variants, advancements in generalization theory, and various feature selection and extraction methods.
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.
Two-Class Support Vector Machines.- Multiclass Support Vector Machines.- Variants of Support Vector Machines.- Training Methods.- Kernel-Based Methods Kernel@Kernel-based method .- Feature Selection and Extraction.- Clustering.- Maximum-Margin Multilayer Neural Networks.- Maximum-Margin Fuzzy Classifiers.- Function Approximation.
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