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Can I read Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition) on EtoBox?
Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition) by Shigeo Abe; Sameer Singh is a nonfiction available to read on EtoBox.
What is Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition) about?
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.
Who reads Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Shigeo Abe; Sameer Singh
- Publisher
- Springer London, Limited
- Published
- 2005
- Language
- EN
- ISBN
- 9781852339296
- Category
- nonfiction
- Subjects
- Engineering, Science, Computer Science
Other editions & translations
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