Title :
A new scatter-based multi-class support vector machine
Author :
Jenssen, Robert ; Kloft, Marius ; Sonnenburg, Sören ; Zien, Alexander ; Müller, Klaus-Robert
Author_Institution :
Dept. of Phys. & Technol., Univ. of Tromso, Tromso, Norway
Abstract :
We provide a novel interpretation of the dual of support vector machines (SVMs) in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. We identify the associated primal problem and develop a fast chunking-based optimizer. Promising results are reported, also compared to the state-of-the-art, at lower computational complexity.
Keywords :
optimisation; support vector machines; chunking based optimizer; class prototype; computational complexity; joint scatter SVM algorithm; optimization variable; scatter based multiclass support vector machine; Joints; Kernel; Machine learning; Optimization; Prototypes; Support vector machines; Training; µ-SVM; multi-class; scatter;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on
Conference_Location :
Santander
Print_ISBN :
978-1-4577-1621-8
Electronic_ISBN :
1551-2541
DOI :
10.1109/MLSP.2011.6064625