Open ablaom opened 1 year ago
Also, it seems that loss
is only available for classification trees - not regression trees.
Is it possible to repurpose the existing code for classification trees to run regression tasks? It would be convenient both for
regression tasks with one target and a custom loss, and
multi-target problems (the current implementation for regression trees does not allow for features
that are not Float64
- i.e., single targets).
multi-target problems (the current implementation for regression trees does not allow for
features
that are notFloat64
- i.e., single targets).
Do you mean features
here or, rather, labels
(aka target)?
labels
as in this example
As far as I can tell, the
loss
parameter is only exposed for single trees. I think this would be pretty easy to add to the ensemble models.Issue raised at #211.