glmnet
package implementation.emil.fit.glmnet(x, y, family, nfolds, foldid, alpha = 1, lambda = NULL, ...)glmnet.y is numeric or survival. See family for details.cv.glmnet.cv.glmnet.glmnet.glmnet.cv.glmnet.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 variable to tune
on. The shrinkage, controlled by the lambda parameter, can be left
unspecified for internal tuning (works the same way as
emil.fit.glmnet).emil, emil.predict.glmnet,
modeling.procedure