Abstract #301253

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JSM 2003 Abstract #301253
Activity Number: 431
Type: Invited
Date/Time: Thursday, August 7, 2003 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #301253
Title: Boosting and Support Vector Machines
Author(s): Trevor J. Hastie*+
Companies: Stanford University
Address: Sequoia Hall, Rm. 104, Stanford, CA, 94305-4020,
Keywords: regularization ; stagewise ; boosting ; SVM ; lasso ; overfit
Abstract:

We argue that a useful form of boosting behaves like an L1 optimized path of models. In other words, the sequence of boosted models, for a particular loss function, follows the same path as the sequence of L1 penalized versions of this same loss function, as the penalty is relaxed. This offers us some insight into why boosting appears to work well in some high-dimensional situations - the same situations where L1 penalized regression works well. It also makes connections with the Support Vector Machine, which has a similar structure; we show that for particular loss functions both procedures have similar margin-maximizing limits.

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