Scikit-learn random forest does not handle the multi-output case, but only
maps to each output one at a time, thereby not accounting for the correlation
between multi-outputs, which is what the Mahalanobis distance does. I, as well
as other researchers have observed this issue for as much as tw
Hi Paul,
The way multioutput is handled in decision trees (and thus in the
forests) is described in
https://scikit-learn.org/stable/modules/tree.html#multi-output-problems.
As you can see, the correlation between the output values *is* taken
into account.
Can you explain what you would like
