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randomForestVIP
View on CRAN: Click
here
Download and install randomForestVIP package within the R console
Install from CRAN:
install.packages("randomForestVIP")
Install from Github:
library("remotes")
install_github("cran/randomForestVIP") Install by package version:
library("remotes")
install_version("randomForestVIP", "0.1.3") Attach the package and use:
library("randomForestVIP")
Maintained by
Kelvyn Bladen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-07-19
Latest Update: 2023-07-19
Description:
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)
.
How to cite:
Kelvyn Bladen (2023). randomForestVIP: Tune Random Forests Based on Variable Importance & Plot Results. R package version 0.1.3, https://cran.r-project.org/web/packages/randomForestVIP. Accessed 22 Sep. 2026.
Previous versions and publish date:
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Other R packages that randomForestVIP depends,
imports, suggests or enhances
Complete documentation for randomForestVIP
Functions, R codes and Examples using
the randomForestVIP R package
Some associated functions: boston . ggvip . lichen . mtry_compare . partial_cor . robust_vifs .
Some associated R codes: data.R . ggvip.R . globals.R . mtry_compare.R . partial_cor.R . robust_vifs.R . Full randomForestVIP package functions and examples
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