Multiple Imputation by Chained Equations with Random Forests
Description
Multiple Imputation has been shown to
be a flexible method to impute missing values by
Van Buuren (2007) .
Expanding on this, random forests have been shown
to be an accurate model by Stekhoven and Buhlmann
to impute missing values in datasets.
They have the added benefits of returning out of bag
error and variable importance estimates, as well as
being simple to run in parallel.