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The aim of healthcareai is to make machine learning easy on healthcare data. The package has two main goals:

For those starting out

Note: if you’re setting up R on an ETL server, don’t download RStudio–simply open up RGui

Install the latest release on Windows

Open RStudio and work in the console


If install.packages('healthcareai') or library(healthcareai) fails

If you don’t have admin rights on the machine you are working on, you may need to set a custom location for your R libraries. Here’s how to do that:

  1. Create a folder to hold your R packages. You’ll generally have write access to your Documents folder, so you might create a new directory: C:\Users\\Documents\R\R_library. Shift-right click on that folder and copy its path.
  2. Define a system variable with that folder location. Open the Control Panel and click through User Accounts -> User Accounts -> Change my environment variables, and add a variable called R_LIBS_USER, and paste the folder path (C:\Users\\Documents\R\R_library) into the value field. Make sure the path is not surrounded by "s.
  3. Tell R to use that location. Restart R Studio, run install.packages('healthcareai'), and if asked whether you want to use a custom library location choose yes, which may be sufficient. If not, click into the Console in R Studio, type .libPaths(), paste the path to your new library folder inside the (), and change the \s to /. You should end up with a line that looks like: .libPaths("C:/Users/"). Press enter to run that.
  4. Try again. Run install.packages('healthcareai') and library(healthcareai) again and all should be well!

How to install the latest version on macOS

Open RStudio and work in the console


How to install latest version on Ubuntu (Linux)

Install the bleeding edge version (for folks providing contributions)

Open RStudio and work in the console


Tips on getting started

Built-in examples

Load the package you just installed and read the built-in docs


Website examples

See our docs website

Join the community

Read the blog and join the slack channel at

What’s new?

The CRAN 1.0.0 release features: - Added: - Kmeans clustering - XGBoost multiclass support - findingVariation family of functions - Changed: - Develop step trains and saves models - Deploy no longer trains. Loads and predicts on all rows. - SQL uses a DBI back end - Removed: - testWindowCol is no longer a param. - SQL reading/writing is outside model deployment.

For issues


You want to help? Woohoo! We welcome that and are willing to help newbies get started.

First, see here for instructions on setting up your development environment and how to contribute.