We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic models. This model class can be viewed as a reparametrization of the SVM in a similar vein to the v-SVM reparametrizing the classical (C-)SVM. It is not discriminative, but has a non-uniform marginal. We illustrate the benefits of this new view by rederiving and re-investigating two established SVM-related algorithms.
| Author(s): | Franc, V. and Zien, A. and Schölkopf, B. |
| Book Title: | Proceedings of the 28th International Conference on Machine Learning |
| Pages: | 665-672 |
| Year: | 2011 |
| Month: | July |
| Day: | 0 |
| Editors: | L Getoor and T Scheffer |
| Publisher: | International Machine Learning Society |
| Bibtex Type: | Conference Paper (inproceedings) |
| Address: | Madison, WI, USA |
| Event Name: | ICML 2011 |
| Event Place: | Bellevue, WA, USA |
| Electronic Archiving: | grant_archive |
| ISBN: | 978-1-450-30619-5 |
| Links: | |
BibTex
@inproceedings{FrancZS2011,
title = {Support Vector Machines as Probabilistic Models},
booktitle = {Proceedings of the 28th International Conference on Machine Learning},
abstract = {We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic models. This model class can be viewed as a reparametrization of the SVM in a similar vein to the v-SVM reparametrizing the classical (C-)SVM. It is not discriminative, but has a non-uniform marginal. We
illustrate the benefits of this new view by rederiving and re-investigating two established SVM-related algorithms.},
pages = {665-672},
editors = {L Getoor and T Scheffer},
publisher = {International Machine Learning Society},
address = {Madison, WI, USA},
month = jul,
year = {2011},
slug = {franczs2011},
author = {Franc, V. and Zien, A. and Sch{\"o}lkopf, B.},
month_numeric = {7}
}