Other packages > Find by keyword >

MulvariateRandomForestVarImp  

Variable Importance Measures for Multivariate Random Forests
View on CRAN: Click here


Download and install MulvariateRandomForestVarImp package within the R console
Install from CRAN:
install.packages("MulvariateRandomForestVarImp")

Install from Github:
library("remotes")
install_github("cran/MulvariateRandomForestVarImp")

Install by package version:
library("remotes")
install_version("MulvariateRandomForestVarImp", "0.0.2")



Attach the package and use:
library("MulvariateRandomForestVarImp")
Maintained by
Dogonadze Nika
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-12-03
Latest Update: 2021-12-15
Description:
Calculates two sets of post-hoc variable importance measures for multivariate random forests. The first set of variable importance measures are given by the sum of mean split improvements for splits defined by feature j measured on user-defined examples (i.e., training or testing samples). The second set of importance measures are calculated on a per-outcome variable basis as the sum of mean absolute difference of node values for each split defined by feature j measured on user-defined examples (i.e., training or testing samples). The user can optionally threshold both sets of importance measures to include only splits that are statistically significant as measured using an F-test.
How to cite:
Dogonadze Nika (2021). MulvariateRandomForestVarImp: Variable Importance Measures for Multivariate Random Forests. R package version 0.0.2, https://cran.r-project.org/web/packages/MulvariateRandomForestVarImp. Accessed 07 Oct. 2026.
Previous versions and publish date:
0.0.1 (2021-12-03 19:50), (2026-07-09 08:11)
Other packages that cited MulvariateRandomForestVarImp R package
View MulvariateRandomForestVarImp citation profile
Other R packages that MulvariateRandomForestVarImp depends, imports, suggests or enhances
Complete documentation for MulvariateRandomForestVarImp
Functions, R codes and Examples using the MulvariateRandomForestVarImp R package
Some associated functions: MeanOutcomeDifference . MeanSplitImprovement . 
Some associated R codes: common.R . mean_outcome_difference.R . mean_split_improvement.R .  Full MulvariateRandomForestVarImp package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

skewlmm  
Scale Mixture of Skew-Normal Linear Mixed Models
It fits scale mixture of skew-normal linear mixed models using an expectation–maximization (EM) ty ...
Download / Learn more Package Citations See dependency  
ggTimeSeries  
Time Series Visualisations Using the Grammar of Graphics
Provides additional display mediums for time series visualisations. ...
Download / Learn more Package Citations See dependency  
PairedData  
Paired Data Analysis
Many datasets and a set of graphics (based on ggplot2), statistics, effect sizes and hypothesis test ...
Download / Learn more Package Citations See dependency  
splm  
Econometric Models for Spatial Panel Data
ML and GM estimation and diagnostic testing of econometric models for spatial panel data. ...
Download / Learn more Package Citations See dependency  
blandr  
Bland-Altman Method Comparison
Carries out Bland Altman analyses (also known as a Tukey mean-difference plot) as described by JM B ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  

28,905

R Packages

247,686

Dependencies

76,495

Author Associations

28,906

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA