Comparing penalization methods for linear models on large observational health data.
This study evaluates regularization variants in logistic regression (L1, L2, ElasticNet, Adaptive L1, Adaptive ElasticNet, Broken adaptive ridge [BAR], and Iterative hard thresholding [IHT]) for discrimination and calibration performance, focusing on both internal and external validation.
Author(s): Fridgeirsson, Egill A, Williams, Ross, Rijnbeek, Peter, Suchard, Marc A, Reps, Jenna M
DOI: 10.1093/jamia/ocae109