科研成果详情

Ridge estimators regularize the squared Euclidean lengths of parameters. Such estimators are mathematically and computationally attractive but involve tuning parameters that need to be calibrated. It is shown that ridge estimators can be modified such that tuning parameters can be avoided altogether, and the resulting estimator can improve on the prediction accuracies of standard ridge estimators combined with cross-validation.