Predictions, Lasso Regression, Model Averaging, Spline Regression, Crossvalidation.
smaller numbers of predictors, e.g. k< 30 (not set in stone). Selection methods all focus on the bias / variance trade-off. Most models, by default, want to decrease variance. They are wired to decrease the residuals error after each iterative step until the minimum residual error has been found.