MokyoZhou/lassoenet: An Interactive Implementation of Penalised Regressions

The package "lassoenet" is aiming to help and guide interested users to build penalised linear models to their own datasets. More specifically, the package is focusing on steering the users into a more appropriate modelling set up by providing a user-friendly interactive mode that contains a series of performance related questions and suggestions throughout the fitting process. Furthermore, core functions from the package glmnet are called and further developed on to form a collection of very flexible functions that offer extra fitting settings for both the Lasso and the Elastic Net. A direct and convenient fitting of the Adpative Lasso is also allowed.

install.packages("remotes")
remotes::install_github("MokyoZhou/lassoenet")