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In situations when one wants to use R to do a quantile regression, the options available are fairly limited - the quantreg package and quantregForests are two.
On the other hand, since version 2.0.0, XGBoost also provides a quantile regression option, available in the R package as well.
It would be useful in and off itself to provide an interface to this capability from boost_tree so that quantile regression with xgboost is available out of the box
The function probably::int_conformal_quantile it might also be useful to give an option to use the xgboost quantile regression or the quantreg rq function instead of regression forests.
The text was updated successfully, but these errors were encountered:
I also am extremely interested in quantile regression being added to parsnip, but that feature is (AFAICT) not available yet in the xgboost R package, and probably will be some time coming still. They are rewriting the entire R interface to the underlying xgboost library and won't enable quantile regression until that's done. Skimming the linked issue, I think there is still a lot of work to do.
Feature
In situations when one wants to use R to do a quantile regression, the options available are fairly limited - the
quantreg
package andquantregForests
are two.On the other hand, since version 2.0.0, XGBoost also provides a quantile regression option, available in the R package as well.
boost_tree
so that quantile regression with xgboost is available out of the boxprobably::int_conformal_quantile
it might also be useful to give an option to use the xgboost quantile regression or the quantreg rq function instead of regression forests.The text was updated successfully, but these errors were encountered: