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).
Package details |
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Bioconductor views | KEGGREST |
Maintainer | |
License | GPL-3 |
Version | 0.0.0.9000 |
URL | http://github.com/bips-hb/rgp |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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