RF Variable Importance for Arbitrary Measures

Computes the random forest variable importance (VIMP) for the conditional inference random forest (cforest) of the 'party' package. Includes a function (varImp) that computes the VIMP for arbitrary measures from the 'measures' package. For calculating the VIMP regarding the measures accuracy and AUC two extra functions exist (varImpACC and varImpAUC).


Random forest variable importance for arbitrary measures of the measures package, which contains the biggest collection of measures for regression and classification in R.

Installation

The development version

devtools::install_github("mlr-org/measures")
devtools::install_github("PhilippPro/varImp")
iris.cf <- cforest(Species ~ ., data = iris, control = cforest_unbiased(mtry = 2, ntree = 50))
varImp(object = iris.cf, measure = "multiclass.Brier")
varImpACC(object = iris.cf)
varImpAUC(object = iris.cf)

News

Reference manual

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install.packages("varImp")

0.3 by Philipp Probst, 2 months ago


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


Authors: Philipp Probst [aut, cre] , Silke Janitza [ctb]


Documentation:   PDF Manual  


GPL-3 license


Depends on measures, party, stats

Suggests testthat, ranger


Suggested by party.


See at CRAN