DOI status

Functions useful for exploratory data analysis using random forests.

This package extends the functionality of random forests fit by party (multivariate, regression, and classification), randomForestSRC (regression and classification,), randomForest (regression and classification), and ranger (classification and regression).

The subdirectory pkg contains the actual package. The package can be installed with devtools.

devtools::install_github("zmjones/edarf", subdir = "pkg")

Functionality includes:

If you use the package for research, please cite it.

  doi = {10.21105/joss.00092},
  url = {},
  year  = {2016},
  month = {oct},
  publisher = {The Open Journal},
  volume = {1},
  number = {6},
  author = {Zachary M. Jones and Fridolin J. Linder},
  title = {edarf: Exploratory Data Analysis using Random Forests},
  journal = {The Journal of Open Source Software}

Pull requests, bug reports, feature requests, etc. are welcome!

Try the edarf package in your browser

Any scripts or data that you put into this service are public.

edarf documentation built on May 2, 2019, 2:39 a.m.