1-norm support vector machines

Ji Zhu, Saharon Rosset, Trevor Hastie, Rob Tibshirani

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

Abstract

The standard 2-norm SVM is known for its good performance in two-class classification. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advantage over the standard 2-norm SVM, especially when there are redundant noise features. We also propose an efficient algorithm that computes the whole solution path of the 1-norm SVM, hence facilitates adaptive selection of the tuning parameter for the 1-norm SVM.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 16 - Proceedings of the 2003 Conference, NIPS 2003
PublisherNeural information processing systems foundation
ISBN (Print)0262201526, 9780262201520
StatePublished - 2004
Externally publishedYes
Event17th Annual Conference on Neural Information Processing Systems, NIPS 2003 - Vancouver, BC, Canada
Duration: 8 Dec 200313 Dec 2003

Publication series

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

Conference

Conference17th Annual Conference on Neural Information Processing Systems, NIPS 2003
Country/TerritoryCanada
CityVancouver, BC
Period8/12/0313/12/03

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