edarf: 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.

Author
Zachary M. Jones <zmj@zmjones.com> and Fridolin Linder <fridolin.linder@gmail.com>
Date of publication
2016-11-30 20:03:53
Maintainer
Zachary M. Jones <zmj@zmjones.com>
License
MIT + file LICENSE
Version
1.1.0

View on CRAN

Man pages

extract_proximity
Methods to extract proximity matrices from random forests
partial_dependence
Partial dependence using random forests
plot_imp
Plot variable importance from random forests
plot_pd
Plot partial dependence from random forests
plot_pred
Plot predicted versus observed values
plot_prox
Plot principle components of the proximity matrix
variable_importance
Variable importance using random forests

Files in this package

edarf
edarf/inst
edarf/inst/doc
edarf/inst/doc/edarf.R
edarf/inst/doc/edarf.Rmd
edarf/inst/doc/edarf.html
edarf/tests
edarf/tests/testthat.R
edarf/tests/testthat
edarf/tests/testthat/test_pd.R
edarf/tests/testthat/test_imp.R
edarf/tests/testthat/test_prox.R
edarf/NAMESPACE
edarf/NEWS.md
edarf/R
edarf/R/pd.R
edarf/R/utils.R
edarf/R/plot.R
edarf/R/prox.R
edarf/R/imp.R
edarf/vignettes
edarf/vignettes/edarf.Rmd
edarf/README.md
edarf/MD5
edarf/build
edarf/build/vignette.rds
edarf/DESCRIPTION
edarf/man
edarf/man/extract_proximity.Rd
edarf/man/plot_pd.Rd
edarf/man/plot_pred.Rd
edarf/man/plot_imp.Rd
edarf/man/partial_dependence.Rd
edarf/man/plot_prox.Rd
edarf/man/variable_importance.Rd
edarf/LICENSE