glm_net: fit a GLM with Lasso or Ridge or elasticnet regularization

In berthetclement/spam: Model analisys on data spam

Description

Fit a generalized linear model via penalized maximum likelihood ...

Usage

glm_net(data_df, y_name, x_name, alpha_, lambda_cv, ...)

Arguments

data_df	Model data, class "data.frame".
y_name	The variable cible (Y) in characters.
x_name	List of explanatory variables (list of characters).
alpha_	0 for Ridge and 1 for Lasso.
lambda_cv	Lambda min from cv_glm_net()
...	Add arguments from glmnet().

See Also

glmnet() for initial function

Other modeling functions: cv_glm_net(), def_model_keras(), fit_keras(), glm_logit(), tree_rpart()

berthetclement/spam documentation built on Oct. 4, 2020, 9:03 p.m.