Integrating the Evidence Framework and the Support Vector Machine

James Tin-Yau Kwok

Integrating the Evidence Framework and the Support Vector Machine

James Tin-Yau Kwok

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-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 language	English
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
Country/Territory	Belgium
City	Bruges
Period	21/04/99 → 23/04/99

Access to Document

https://www.esann.org/sites/default/files/proceedings/legacy/es1999-451.pdf

Cite this

@inproceedings{ef94ff3eb0fa4b2289e89e31f302d0cc,

title = "Integrating the Evidence Framework and the Support Vector Machine",

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.",

author = "Kwok, {James Tin-Yau}",

year = "1999",

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note = "European Symposium on Artificial Neural Networks, ESANN 1999 ; Conference date: 21-04-1999 Through 23-04-1999",

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AU - Kwok, James Tin-Yau

PY - 1999/4/21

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AB - 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.

UR - https://www.esann.org/proceedings/1999

M3 - Conference proceeding

SN - 26000499X

SP - 177

EP - 182

BT - Proceedings of European Symposium on Artificial Neural Networks, ESANN 1999

PB - ESANN

T2 - European Symposium on Artificial Neural Networks, ESANN 1999

Y2 - 21 April 1999 through 23 April 1999

ER -

Integrating the Evidence Framework and the Support Vector Machine

Abstract

Conference

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