Tuning parameter calibration for $\ell_1$-regularized logistic regression

1 Oct 2016Wei LiJohannes Lederer

Feature selection is a standard approach to understanding and modeling high-dimensional classification data, but the corresponding statistical methods hinge on tuning parameters that are difficult to calibrate. In particular, existing calibration schemes in the logistic regression framework lack any finite sample guarantees... (read more)

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