pdp: An R Package for Constructing Partial Dependence Plots

Abstract:

Complex nonparametric models—like neural networks, random forests, and support vector machines—are more common than ever in predictive analytics, especially when dealing with large observational databases that don’t adhere to the strict assumptions imposed by traditional statistical techniques (e.g., multiple linear regression which assumes linearity, homoscedasticity, and normality). Unfortunately, it can be challenging to understand the results of such models and explain them to management. Partial dependence plots offer a simple solution. Partial dependence plots are low dimensional graphical renderings of the prediction function so that the relationship between the outcome and predictors of interest can be more easily understood. These plots are especially useful in explaining the output from black box models. In this paper, we introduce pdp, a general R package for constructing partial dependence plots.

Cite PDF Tweet

Author

Affiliation

Brandon M. Greenwell

 

Published

May 9, 2017

Received

Sep 30, 2016

DOI

10.32614/RJ-2017-016

Volume

Pages

9/1

421 - 436

CRAN packages used

randomForest, gbm, party, partykit, pdp, plotmo, lattice, ICEbox, car, effects, ggplot2, grid, latticeExtra, gridExtra, nnet, C50, rpart, adabag, ipred, adabag, xgboost, Cubist, MASS, earth, mda, ranger, e1071, kernlab, caret, magrittr, foreach, viridis, plyr, doMC, doParallel, dplyr

CRAN Task Views implied by cited packages

MachineLearning, Multivariate, Environmetrics, Survival, Econometrics, SocialSciences, Graphics, HighPerformanceComputing, Cluster, Distributions, Psychometrics, Finance, NaturalLanguageProcessing, NumericalMathematics, Optimization, Phylogenetics, Robust, WebTechnologies

Footnotes

    Reuse

    Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

    Citation

    For attribution, please cite this work as

    Greenwell, "The R Journal: pdp: An R Package for Constructing Partial Dependence Plots", The R Journal, 2017

    BibTeX citation

    @article{RJ-2017-016,
      author = {Greenwell, Brandon M.},
      title = {The R Journal: pdp: An R Package for Constructing Partial Dependence Plots},
      journal = {The R Journal},
      year = {2017},
      note = {https://doi.org/10.32614/RJ-2017-016},
      doi = {10.32614/RJ-2017-016},
      volume = {9},
      issue = {1},
      issn = {2073-4859},
      pages = {421-436}
    }