MulvariateRandomForestVarImp: Variable Importance Measures for Multivariate Random Forests

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.

Version:	0.0.2
Depends:	R (≥ 2.10)
Imports:	MultivariateRandomForest (≥ 1.1.5), MASS (≥ 7.3.0)
Suggests:	testthat (≥ 3.0.0)
Published:	2021-12-15
Author:	Sikdar Sharmistha [aut], Hooker Giles [aut], Kadiyali Vrinda [ctb], Dogonadze Nika [cre]
Maintainer:	Dogonadze Nika <nika.dogonadze at toptal.com>
BugReports:	https://github.com/Megatvini/VIM/issues
License:	GPL (≥ 3)
URL:	https://github.com/Megatvini/VIM/
NeedsCompilation:	no
Materials:	README
CRAN checks:	MulvariateRandomForestVarImp results

Documentation:

Reference manual:

MulvariateRandomForestVarImp.pdf

Downloads:

Package source:	MulvariateRandomForestVarImp_0.0.2.tar.gz
Windows binaries:	r-devel: MulvariateRandomForestVarImp_0.0.2.zip, r-release: MulvariateRandomForestVarImp_0.0.2.zip, r-oldrel: MulvariateRandomForestVarImp_0.0.2.zip
macOS binaries:	r-release (arm64): MulvariateRandomForestVarImp_0.0.2.tgz, r-oldrel (arm64): MulvariateRandomForestVarImp_0.0.2.tgz, r-release (x86_64): not available, r-oldrel (x86_64): MulvariateRandomForestVarImp_0.0.2.tgz
Old sources:	MulvariateRandomForestVarImp archive

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