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pdp  

Partial Dependence Plots
View on CRAN: Click here


Download and install pdp package within the R console
Install from CRAN:
install.packages("pdp")

Install from Github:
library("remotes")
install_github("cran/pdp")

Install by package version:
library("remotes")
install_version("pdp", "0.8.2")



Attach the package and use:
library("pdp")
Maintained by
Brandon M. Greenwell
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-09-02
Latest Update: 2022-06-07
Description:
A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.
How to cite:
Brandon M. Greenwell (2016). pdp: Partial Dependence Plots. R package version 0.8.2, https://cran.r-project.org/web/packages/pdp. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.0.1 (2016-09-02 12:19), 0.0.4 (2016-09-17 20:07), 0.1.0 (2016-10-06 21:42), 0.2.0 (2016-12-03 18:12), 0.3.0 (2016-12-19 00:01), 0.4.0 (2017-01-07 10:20), 0.5.2 (2017-03-13 06:52), 0.6.0 (2017-07-20 05:09), 0.7.0 (2018-08-27 19:50), 0.8.0 (2022-05-12 01:20), 0.8.1 (2022-06-07 22:40)
Other packages that cited pdp R package
View pdp citation profile
Other R packages that pdp depends, imports, suggests or enhances
Complete documentation for pdp
Functions, R codes and Examples using the pdp R package
Some associated functions: autoplot.partial . boston . exemplar . get_training_data . partial . pdp . pima . plotPartial . topPredictors . trellis.lastject . 
Some associated R codes: autoplot.R . data.R . exemplar.R . get_predictions.R . get_task.R . get_training_data.R . pardep.R . partial.R . pdp.R . plotPartial.R . pred_grid.R . topPredictors.R . utils.R .  Full pdp package functions and examples
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