Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions

Enabling a sound understanding of SVMs, this book gives readers the tools to solve real-world problems using SVMs. It presents an accessible treatment of the two main components of SVMs-classification problems and regression problems. The authors emphasize the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built. They construct SVMs for semi-supervised, knowledge-based, and robust classification problems. They also cover SVMs for Universum, privileged, multi-class, multi-instance, and multi-label classification problems.

Author: Naiyang Deng,Yingjie Tian,Chunhua Zhang
Publisher: CRC Press
Published: 12/17/2012
Pages: 364
Binding Type: Hardcover
Weight: 1.40lbs
Size: 9.40h x 6.10w x 0.90d
ISBN: 9781439857922

About the Author
Naiyang Deng, Yingjie Tian, Chunhua Zhang