The R Journal: article published in 2020, volume 12:1

Variable Importance Plots—An Introduction to the vip Package
Brandon M. Greenwell and Bradley C. Boehmke , The R Journal (2020) 12:1, pages 343-366.

Abstract In the era of “big data”, it is becoming more of a challenge to not only build state-of-the-art by Brandon M. Greenwell, Bradley C. Boehmke Introduction to the vip Package Variable Importance Plots—An

Received: 2019-09-25; online 2020-09-10
CRAN packages: iml, R6, foreach, ingredients, DALEX, mmpf, varImp, party, measures, vita, rfVarImpOOB, randomForestExplainer, tree.interpreter, pkgsearch, caret, mlr, ranger, vip, ggplot2, partykit, earth, nnet, vivo, pdp, microbenchmark, iBreakDown, fastshap, xgboost, ALEPlot, DT, mlr3, data.table, AmesHousing, SuperLearner, glmnet, kernlab, plyr, doParallel
CRAN Task Views implied by cited CRAN packages: MachineLearning, HighPerformanceComputing, Multivariate, Survival, Environmetrics, TeachingStatistics, Cluster, Econometrics, Finance, Graphics, ModelDeployment, NaturalLanguageProcessing, Optimization, Phylogenetics, ReproducibleResearch, SocialSciences, TimeSeries

This article is licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2020-013,
  author = {Brandon M. Greenwell and Bradley C. Boehmke},
  title = {{Variable Importance Plots—An Introduction to the vip Package}},
  year = {2020},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2020-013},
  url = {https://doi.org/10.32614/RJ-2020-013},
  pages = {343--366},
  volume = {12},
  number = {1}
}