varImp v0.3

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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).

Readme

varImp

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)

Functions in varImp

Name Description
varImp varImp
varImpACC varImpACC
varImpAUC varImpAUC
varImpRanger varImpRanger
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Details

License GPL-3
Encoding UTF-8
LazyData true
Date 2019-04-16
RoxygenNote 6.1.1
NeedsCompilation no
Packaged 2019-05-03 14:00:57 UTC; lucia
Repository CRAN
Date/Publication 2019-05-03 14:20:03 UTC

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