MokyoZhou/lassoenet: An Interactive Implementation of Penalised Regressions
Version 0.0.0.9000

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.

Getting started

Package details

Maintainer
LicenseGPL-2
Version0.0.0.9000
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("MokyoZhou/lassoenet")
MokyoZhou/lassoenet documentation built on Aug. 10, 2018, 12:42 a.m.