1-norm Support Vector Machines

The standard 2-norm SVM is known for its good performance in twoclass classi£cation. 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 ef£cient 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.

• Type: Conference
• Year: 2003
• Where: NIPS
• Authors: Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani
• Keywords: 1-norm Svm, NIPS 2003, NIPS 2007, Redundant Noise Features, Standard 2-norm Svm