Free Support Vector Machines for Pattern Classification

Author: Shigeo Abe
Edition: 1st Edition.
Binding: Hardcover
ISBN: 1852339292
Publisher: Springer
Features:

Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)

Support vector machines (SVMs), were originally formulated for two-class classification problems, and have been accepted as a powerful tool for developing pattern classification and function approximations systems. Search and download computer ebooks Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition) for free.
Support Vector Machines for Pattern Classification (Advances in Pattern Recognition), ISBN-13: 9781849960977, ISBN-10: 1849960976. Download Support Vector Machines for Pattern Classification computer ebooks
This book provides a unique perspective of the state of the art in SVMs by taking the only approach that focuses on classification rather than covering the theoretical aspects. The book clarifies the characteristics of two-class SVMs through their extensive analysis, presents various useful architectures for multiclass classification and function approximation problems, and discusses kernel methods for improving generalization ability of conventional neural networks and fuzzy systems. Ample illustrations, examples and computer experiments

Support Vector Machines for Pattern Classification

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, empir

author shigeo abe format hardback language english publication year 29 03 2010 series advances in computer vision and pattern recognition subject engineering technology subject 2 electronics engineering communications engineering support vector machines for pattern classification advances in computer vision author s shigeo abe content note 1 black white illustrations country of publication united kingdom date of publication 29 03 2010 edition statement 2 nd ed 2010 format hardback format details

Support Vector Machines for Pattern Classification provides a comprehensive resource for the use of SVM s in pattern classification The subject area is particularly timely with research on kernel methods increasing rapidly this book is unique in its focus on classification methods The characteristic SVM s are discussed L1 SVMs and L2 SVMs lease squares SVMs and linear programming SVMs from both a theoretical and an experimental viewpoint SVMs were originally formulated for two class problems and an extension to multiclass systems which are essential for practical use is not unique However in i

Store Search search Title, ISBN and Author Support Vector Machines for Pattern Classification by Shigeo Abe Estimated delivery 3-12 business days Format Paperback Condition Brand New 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 c

Support Vector Machines for Pattern Classification Free

This book provides a unique perspective of the state of the art in SVMs by taking the only approach that focuses on classification rather than covering the theoretical aspects
Ample illustrations, examples and computer experiments