The Entire Regularization Path for the Support Vector Machine

Rosset, Saharon, Tibshirani, Robert, Zhu, Ji, Hastie, Trevor J.

–Neural Information Processing Systems 

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.

Neural Information Processing Systems

Dec-31-2005

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The Entire Regularization Path for the Support Vector Machine
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