Train a 'glmnet' with cross validation (cv) model and return convenient results (model and results with non zero coefficients)
pretty_cv.glmnet(
x_glmnet,
y,
alpha = 1,
family = "binomial",
s = "lambda.1se",
weights = rep(1, nrow(x_glmnet)),
...
)A list with the model, the coefficient associated with variables and the selected variables.
Independent variable matrix (X)
Dependent variable vector (Y)
alpha parameter of glmnet (default = 1)
family parameter of glmnet (default = "binomial")
lambda chosen from cv.glmnet (default = "lambda.1se")
glmnet parameter
additional parameters passed to glmnet