pdp: Partial Dependence Plots

A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.

Version: 0.7.0
Depends: R (≥ 3.2.5)
Imports: ggplot2 (≥ 0.9.0), grDevices, gridExtra, lattice, magrittr, methods, mgcv, plyr, stats, viridis, utils
Suggests: adabag, AmesHousing, C50, caret, Cubist, doParallel, dplyr, e1071, earth, gbm, ipred, keras, kernlab, MASS, mda, nnet, party, partykit, progress, randomForest, ranger, rpart, testthat, xgboost (≥ 0.6-0), knitr, rmarkdown, vip
Published: 2018-08-27
Author: Brandon Greenwell ORCID iD [aut, cre]
Maintainer: Brandon Greenwell <greenwell.brandon at gmail.com>
BugReports: https://github.com/bgreenwell/pdp/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://bgreenwell.github.io/pdp/index.html, https://github.com/bgreenwell/pdp
NeedsCompilation: yes
Citation: pdp citation info
Materials: README NEWS
In views: MachineLearning
CRAN checks: pdp results


Reference manual: pdp.pdf
Package source: pdp_0.7.0.tar.gz
Windows binaries: r-devel: pdp_0.7.0.zip, r-release: pdp_0.7.0.zip, r-oldrel: pdp_0.7.0.zip
OS X binaries: r-release: pdp_0.7.0.tgz, r-oldrel: pdp_0.7.0.tgz
Old sources: pdp archive

Reverse dependencies:

Reverse imports: DALEX, rmweather, vip
Reverse suggests: gbm


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