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.


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install.packages("MulvariateRandomForestVarImp")

0.0.2 by Dogonadze Nika, a month ago


https://github.com/Megatvini/VIM/


Report a bug at https://github.com/Megatvini/VIM/issues


Browse source code at https://github.com/cran/MulvariateRandomForestVarImp


Authors: Sikdar Sharmistha [aut] , Hooker Giles [aut] , Kadiyali Vrinda [ctb] , Dogonadze Nika [cre]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports MultivariateRandomForest, MASS

Suggests testthat


See at CRAN