Fits a regularized generalized linear model using elastic net penalties via glmnet.
fit_glmnet(formula, data, family = gaussian, alpha = 0.5, ...)An object of class formula with a symbolic description
of the model to be fitted.
A data.frame containing the variables in the model.
A description of the error distribution and link function.
See stats::family for details.
The elasticnet mixing parameter, between 0 and 1:
alpha = 1: Lasso penalty
alpha = 0: Ridge penalty
0 < alpha < 1: Elastic net penalty
Additional parameters passed to glmnet::glmnet.
A list containing two data frames:
metrics - Goodness of fit measures including lambda and R-squared
coefficients - Regularized coefficient estimates