Boruta (version 7.0.0)

getImpLegacyRf: randomForest importance adapters

Description

Those function is intended to be given to a getImp argument of Boruta function to be called by the Boruta algorithm as an importance source. getImpLegacyRfZ generates default, normalized permutation importance, getImpLegacyRfRaw raw permutation importance, finally getImpLegacyRfGini generates Gini index importance, all using randomForest as a Random Forest algorithm implementation.

Usage

getImpLegacyRfZ(x, y, ...)
getImpLegacyRfRaw(x, y, ...)
getImpLegacyRfGini(x, y, ...)

Arguments

x

data frame of predictors including shadows.

y

response vector.

...

parameters passed to the underlying randomForest call; they are relayed from ... of Boruta.

Examples

set.seed(777)
#Add some nonsense attributes to iris dataset by shuffling original attributes
iris.extended<-data.frame(iris,apply(iris[,-5],2,sample))
names(iris.extended)[6:9]<-paste("Nonsense",1:4,sep="")
#Run Boruta on this data
Boruta(Species~.,getImp=getImpLegacyRfZ,
 data=iris.extended,doTrace=2)->Boruta.iris.extended
#Nonsense attributes should be rejected
print(Boruta.iris.extended)

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