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cff-version: 1.2.0
message: 'To cite package "randomForestVIP" in publications use:'
type: software
license: GPL-3.0-only
title: 'randomForestVIP: Tune Random Forests Based on Variable Importance and Plot
  Results'
version: 0.1.3.9000
doi: 10.32614/CRAN.package.randomForestVIP
abstract: Functions for assessing variable relations and associations prior to modeling
  with a Random Forest algorithm (although these are relevant for any predictive model).
  Metrics such as partial correlations and variance inflation factors are tabulated
  as well as plotted for the user. A function is available for tuning the main Random
  Forest hyper-parameter based on model performance and variable importance metrics.
  This grid-search technique provides tables and plots showing the effect of the main
  hyper-parameter on each of the assessment metrics. It also returns each of the evaluated
  models to the user. The package also provides superior variable importance plots
  for individual models. All of the plots are developed so that the user has the ability
  to edit and improve further upon the plots. Derivations and methodology are described
  in Bladen (2022) <https://digitalcommons.usu.edu/etd/8587/>.
authors:
- family-names: Bladen
  given-names: Kelvyn
  email: kelvyn.bladen@usu.edu
- family-names: Cutler
  given-names: D. Richard
repository: https://kelvynbladen.r-universe.dev
repository-code: https://github.com/KelvynBladen/randomForestVIP
commit: b9c5f647bc455cf3eff2eb6225d5acae83f7caa6
url: https://github.com/KelvynBladen/randomForestVIP
contact:
- family-names: Bladen
  given-names: Kelvyn
  email: kelvyn.bladen@usu.edu