The entire regularization path for the support vector machine

Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we argue that the choice of the SVM cost parameter can be critical. We then derive an algorithm that can fit the entire path of SVM solutions for every value of the cost parameter, with essentially the same computational cost as fitting one SVM model.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004
PublisherNeural information processing systems foundation
ISBN (Print)0262195348, 9780262195348
StatePublished - 2005
Externally publishedYes
Event18th Annual Conference on Neural Information Processing Systems, NIPS 2004 - Vancouver, BC, Canada
Duration: 13 Dec 200416 Dec 2004

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Conference

Conference18th Annual Conference on Neural Information Processing Systems, NIPS 2004
Country/TerritoryCanada
CityVancouver, BC
Period13/12/0416/12/04

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