Abstract
In this pap er, we show that training of the support vector machine (SVM) can b e interpreted as performing the level 1 inference of MacKay's evidence framework. We further on show that levels 2 and 3 can also b e applied to SVM. This allows automatic adjustment of the regularization parameter and the kernel parameter. More importantly, it op ens up a wealth of Bayesian tools for use with SVM. Performance is evaluated on both synthetic and real-world data sets.
Original language | English |
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Title of host publication | Proceedings of European Symposium on Artificial Neural Networks, ESANN 1999 |
Publisher | ESANN |
Pages | 177-182 |
Number of pages | 6 |
ISBN (Print) | 26000499X |
Publication status | Published - 21 Apr 1999 |
Externally published | Yes |
Event | European Symposium on Artificial Neural Networks, ESANN 1999 - Bruges, Belgium Duration: 21 Apr 1999 → 23 Apr 1999 |
Conference
Conference | European Symposium on Artificial Neural Networks, ESANN 1999 |
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Country/Territory | Belgium |
City | Bruges |
Period | 21/04/99 → 23/04/99 |