Support Vector Machines for Pattern Classification

• Main Author: Abe, Shigeo (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2005.
• Series: Advances in Pattern Recognition
• Subjects: Computer science.; Artificial intelligence.; Text processing (Computer science).; Pattern recognition.; Control engineering.; Robotics.; Mechatronics.; Computer Science.; Pattern Recognition.; Document Preparation and Text Processing.; Artificial Intelligence (incl. Robotics).; Control, Robotics, Mechatronics.

I was shocked to see a student’s report on performance comparisons between support vector machines (SVMs) and fuzzy classi?ers that we had developed withourbestendeavors.Classi?cationperformanceofourfuzzyclassi?erswas comparable, but in most cases inferior, to that of support vector machines. This t...

Table of Contents:

• Two-Class Support Vector Machines
• Multiclass Support Vector Machines
• Variants of Support Vector Machines
• Training Methods
• Feature Selection and Extraction
• Clustering
• Kernel-Based Methods
• Maximum-Margin Multilayer Neural Networks
• Maximum-Margin Fuzzy Classifiers
• Function Approximation.