bips-hb/rgp: Identification of Risk Groups in Pharmacovigilance Using Penalized Regression and Machine Learning (RGP)

A package for analyzing healthcare claims data and simulated data using penalized regression and machine learning methods. This package contains function wrappers to create a simulated cohort, group predictors based on functional targets (from KEGG and TTD) and conventional groups (ATC/ICD systems) and analyze the data using various types of penalized regression (LASSO) and machine learning methods (random forests and block forests).

Getting started

Package details

Bioconductor views KEGGREST
Maintainer
LicenseGPL-3
Version0.0.0.9000
URL http://github.com/bips-hb/rgp
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("bips-hb/rgp")
bips-hb/rgp documentation built on Feb. 3, 2021, 11:31 a.m.