fit_glmnet(x, y, family, nfolds, foldid, alpha = 1, lambda = NULL, ...)fit_ridge_regression(...)
fit_lasso(...)
alpha parameter of glmnet controls the type of
penalty. Use 0 (default) for lasso only, 1 for ridge only, or
an intermediate for a combination. This is typically the parameter to tune
on. The shrinkage, controlled by the lambda parameter, can be left
unspecified for internal tuning (works the same way as
fit_glmnet).emil, predict_glmnet,
importance_glmnet, modeling_procedure