High-Performance Open-Source Archive
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
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)
# Two classes:
iris2 = iris
iris2$Species = factor(iris$Species == "versicolor")
iris.cf = cforest(Species ~ ., data = iris2,control = cforest_unbiased(mtry = 2, ntree = 50))
varImpAUC(object = iris.cf)
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