A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.
Version: 0.8.2 Depends: R (≥ 3.6.0) Imports: foreach, ggplot2 (≥ 3.0.0), grDevices, lattice, methods, rlang (≥ 0.3.0), stats, utils Suggests: adabag, AmesHousing, C50, caret, covr, Cubist, doParallel, dplyr, e1071, earth, gbm, gridExtra, ICEbox, ipred, keras, kernlab, magrittr, MASS, Matrix, mda, mlbench, nnet, party, partykit, randomForest, ranger, reticulate, rpart, tinytest, xgboost (≥ 0.6-0), knitr, rmarkdown, vip Published: 2024-10-28 DOI: 10.32614/CRAN.package.pdp Author: Brandon M. Greenwell [aut, cre] Maintainer: Brandon M. Greenwell <greenwell.brandon at gmail.com> BugReports: https://github.com/bgreenwell/pdp/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/bgreenwell/pdp, http://bgreenwell.github.io/pdp/ NeedsCompilation: yes Citation: pdp citation info Materials: README NEWS In views: MachineLearning CRAN checks: pdp results Documentation: Downloads: Reverse dependencies: Reverse imports: caretSDM, hpiR, moreparty, oncrawlR, radiant.model, rmweather Reverse suggests: creditmodel, ENMTools, gbm, mpae, tinyVAST, vip, xgrove Linking:Please use the canonical form https://CRAN.R-project.org/package=pdp to link to this page.
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