V. Vapnik, and O. Chapelle. Advances in Large Margin Classifiers, page 261-280. Cambridge, MA, MIT Press, (2000)
Abstract
Bounds on the Error Expectation for SVM in terms of the leave-one-out
estimate and the expected value of certain properties of the SVM
are given. It is shown that previous bounds involving the minimum
margin and the diameter $D$ of the set of support vectors can be
improved by the replacement of $D^2$ by $SD$. Here, $S$ is a new
geometric property of the support vectors called the span. Experimental
results show that this improvement gives significantly better predictions
of test error than the previous bounds, and seems likely to be useful
for model selection.
%0 Conference Paper
%1 VapCha00
%A Vapnik, V.
%A Chapelle, O.
%B Advances in Large Margin Classifiers
%C Cambridge, MA
%D 2000
%E Smola, A.J.
%E Bartlett, P.L.
%E Schölkopf, B.
%E Schuurmans, D.
%I MIT Press
%K imported
%P 261-280
%T Bounds on error expectation for SVM
%X Bounds on the Error Expectation for SVM in terms of the leave-one-out
estimate and the expected value of certain properties of the SVM
are given. It is shown that previous bounds involving the minimum
margin and the diameter $D$ of the set of support vectors can be
improved by the replacement of $D^2$ by $SD$. Here, $S$ is a new
geometric property of the support vectors called the span. Experimental
results show that this improvement gives significantly better predictions
of test error than the previous bounds, and seems likely to be useful
for model selection.
@inproceedings{VapCha00,
abstract = {Bounds on the Error Expectation for SVM in terms of the leave-one-out
estimate and the expected value of certain properties of the SVM
are given. It is shown that previous bounds involving the minimum
margin and the diameter $D$ of the set of support vectors can be
improved by the replacement of $D^2$ by $SD$. Here, $S$ is a new
geometric property of the support vectors called the span. Experimental
results show that this improvement gives significantly better predictions
of test error than the previous bounds, and seems likely to be useful
for model selection.},
added-at = {2008-04-30T12:59:47.000+0200},
address = {Cambridge, MA},
author = {Vapnik, V. and Chapelle, O.},
biburl = {https://www.bibsonomy.org/bibtex/2873d55324d9ad4d595e617e8a2603647/kdubiq},
booktitle = {Advances in Large Margin Classifiers},
description = {KDubiq Blueprint},
editor = {Smola, A.J. and Bartlett, P.L. and Sch{\"o}lkopf, B. and Schuurmans, D.},
groupsearch = {0},
interhash = {eb4f71d7942aecfa35b5c79f31dabd0b},
intrahash = {873d55324d9ad4d595e617e8a2603647},
keywords = {imported},
pages = {261-280},
publisher = {{MIT} Press},
timestamp = {2008-04-30T13:00:30.000+0200},
title = {Bounds on error expectation for {SVM}},
year = 2000
}