DocumentCode
2947267
Title
Selection of tuning parameters for support vector machines
Author
Solo, Victor
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Volume
5
fYear
2005
fDate
18-23 March 2005
Abstract
Support vector machines have become important in classification, biometrics, machine learning and pattern recognition. However, successful application requires selection of various tuning parameters such as kernel parameters and penalty or margin parameters. We apply a new technique for this problem which provides very simple structure for the automatic selector.
Keywords
biometrics (access control); learning (artificial intelligence); pattern classification; support vector machines; tuning; automatic selector structure; biometrics; classification; kernel parameters; machine learning; margin parameters; pattern recognition; penalty parameters; support vector machines; tuning parameter selection; Application software; Biometrics; Inverse problems; Kernel; Machine learning; Pattern recognition; Supervised learning; Support vector machine classification; Support vector machines; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-8874-7
Type
conf
DOI
10.1109/ICASSP.2005.1416284
Filename
1416284
Link To Document