edarf (1.1.1)

Exploratory Data Analysis using Random Forests.


Functions useful for exploratory data analysis using random forests which can be used to compute multivariate partial dependence, observation, class, and variable-wise marginal and joint permutation importance as well as observation-specific measures of distance (supervised or unsupervised). All of the aforementioned functions are accompanied by 'ggplot2' plotting functions.

Maintainer: Zachary M. Jones
Author(s): Zachary M. Jones <zmj@zmjones.com> and Fridolin Linder <fridolin.linder@gmail.com>

License: MIT + file LICENSE

Uses: data.table, ggplot2, mmpf, party, randomForest, testthat, knitr, randomForestSRC, rmarkdown, ranger
Reverse depends: metaforest

Released about 3 years ago.