Integrating the Evidence Framework and the Support Vector Machine

James Tin-Yau Kwok

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

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 languageEnglish
Title of host publicationProceedings of European Symposium on Artificial Neural Networks, ESANN 1999
PublisherESANN
Pages177-182
Number of pages6
ISBN (Print)26000499X
Publication statusPublished - 21 Apr 1999
Externally publishedYes
EventEuropean Symposium on Artificial Neural Networks, ESANN 1999 - Bruges, Belgium
Duration: 21 Apr 199923 Apr 1999

Conference

ConferenceEuropean Symposium on Artificial Neural Networks, ESANN 1999
Country/TerritoryBelgium
CityBruges
Period21/04/9923/04/99

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