Closed prockenschaub closed 3 years ago
Thanks a lot.
I would prefer the faster method (ranger
) as default, and switch to randomForest
only if needed for backward compatibility. In that way, future users will get the faster method without further ado.
Would you be able to make ranger
the default?
Changed the default to ranger and updated the help pages accordingly.
Changes
As described in #264 , add a
ranger
backend for imputation via random forest. New implementation has been checked using the same tasks used in:Doove, L. L., S. Van Buuren, and E. Dusseldorp. 2014. “Recursive Partitioning for Missing Data Imputation in the Presence of Interaction Effects.” Computational Statistics & Data Analysis 72: 92–104.
Comment
Since both the
randomForest
package (current default) and theranger
package fit the same model class and draw from it in the same way, I have opted to make the choice of backend a new parameterrfPackage
inmice.impute.rf
, which keepsrandomForest
as the default choice for backwards compatibility. If this is not wanted, the same implementation can easily be pulled out into its ownmice.impute.ranger
.