Support Vector Machines: Theory and Applications
Support Vector Machines: Theory and Applications
by Lipo Wang, (Studies in Fuzziness and Soft Computing)
Springer | ISBN: 3540243887 | 2005 Year | 431 Pages | PDF | 16 Mb
The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in their respective fields.