CRAN/E | randomForestVIP

randomForestVIP

Tune Random Forests Based on Variable Importance & Plot Results

Installation

About

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) .

github.com/KelvynBladen/randomForestVIP

Key Metrics

Version 0.1.3
R ≥ 4.0.0
Published 2023-07-19 445 days ago
Needs compilation? no
License GPL-3
CRAN checks randomForestVIP results

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Maintainer

Maintainer

Kelvyn Bladen

Authors

Kelvyn Bladen

aut / cre

D. Richard Cutler

aut

Material

README
Reference manual
Package source

Vignettes

randomForestVIP Vignette

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 4.0.0

Imports

car
dplyr
ggplot2
gridExtra
minerva
randomForest
stats
tidyr

Suggests

EZtune
e1071
knitr
MASS
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testthat ≥3.0.0