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

Documentation

Manual: pdp.pdf
Vignette: None available.

Maintainer: Brandon Greenwell <greenwell.brandon at gmail.com>

Author(s): Brandon Greenwell*

Install package and any missing dependencies by running this line in your R console:

install.packages("pdp")

Depends R (>= 3.2.5)
Imports boot, dplyr, ggplot2(>=0.9.0), grDevices, gridExtra, lattice, magrittr, methods, mgcv, plyr, Rcpp(>=0.11.5), stats, viridis, utils
Suggests adabag, C50, caret, Cubist, e1071, earth, gbm, ipred, kernlab, MASS, mda, nnet, party, partykit, randomForest, ranger, rpart, testthat, xgboost(>=0.6-0)
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Package pdp
Materials
URL https://github.com/bgreenwell/pdp
Task Views
Version 0.5.2
Published 2017-03-13
License GPL (>= 2)
BugReports https://github.com/bgreenwell/pdp/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks pdp check results
Package source pdp_0.5.2.tar.gz