getImpFerns {Boruta}

Random Ferns importance

Description

This function is intended to be given to a getImp argument of Boruta function to be called by the Boruta algorithm as an importance source.

Usage

getImpFerns(x, y, ...)

Arguments

x

data frame of predictors including shadows.

y

response vector.

...

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

Note

Random Ferns importance calculation should be much faster than using Random Forest; however, one must first optimize the value of the depth parameter and it is quite likely that the number of ferns in the ensemble required for the importance to converge will be higher than the number of trees in case of Random Forest.