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What is the equivalent to missForest missing value imputation in rapidminer?
Learner IIII 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%.
the continuous values were imputed with an error of 13% and the categorical of 15%.
Do I have this possibility in RapidMiner too?
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