Feature Screening for High-Dimensional Variable Selection in Generalized Linear Models
Feature Screening for High-Dimensional Variable Selection in Generalized Linear Models
The two-stage feature screening method for linear models applies dimension reduction at first stage to screen out nuisance features and dramatically reduce the dimension to a moderate size; at the second stage, penalized methods such as LASSO and SCAD could be applied for feature selection. A majority of subsequent works …