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.

AuthorZachary M. Jones <zmj@zmjones.com> and Fridolin Linder <fridolin.linder@gmail.com>
Date of publication2017-03-06 08:28:57
MaintainerZachary M. Jones <zmj@zmjones.com>
LicenseMIT + file LICENSE
Version1.1.1

View on CRAN

Files

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

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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All documentation is copyright its authors; we didn't write any of that.