Lasso type classifiers with a reject option

Abstract

We consider the problem of binary classification where one can, for a particular cost, choose not to classify an observation. We present a simple proof for the oracle inequality for the excess risk of structural risk minimizers using a lasso type penalty.

Published at http://dx.doi.org/10.1214/07-EJS058 in the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (1)

• High-dimensional generalized linear models and the lasso

Cited by in corpus (1)

• Honest variable selection in linear and logistic regression models via ${\ell }_1$ and ${\ell }_1+{\ell }_2$ penalization