I would like to obtain missing value imputation.
In the missForest package in R I could implement the missing values and check the error imputate values (out of bag) as normalized mean
square error (NRMSE) and proportion of falsely classified (PFC).
Thereby for example a NRMS of 0.13 and PFC of 0.15 mean that the
the continuous values were imputed with an error of 13% and the
categorical of 15%.
Do I have this possibility in RapidMiner too?
