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  E-mail Message: I thought you might be interested in this item at http://www.worldcat.org/oclc/65196441 Title: Support vector machines for pattern classification Author: Shigeo Abe Publisher: London : Springer, ©2005. ISBN/ISSN: 1852339292 9781852339296 1846282195 9781846282195 OCLC:65196441

  
  

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• Pattern recognition systems.
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Support vector machines for pattern classification

Author:	Shigeo Abe
Publisher:	London : Springer, ©2005.
Series:	Advances in pattern recognition.
Edition/Format:	eBook : Document : EnglishView all editions and formats
Summary:	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. 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 are included to help readers understand the new ideas and their usefulness. This book supplies a comprehensive resource for the use of SVMs in pattern classification and will be invaluable reading for researchers, developers & students in academia and industry.  Read more...
Rating:	based on 1 rating(s) 1 with a review