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.


The development version

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)


Reference manual

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0.4 by Philipp Probst, 2 years 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

Imported by moreparty.

Suggested by party, vip.

See at CRAN