Closed rdiaz02 closed 5 months ago
Hello, I have a wrapper here that does that: https://github.com/ck37/ck37r/blob/master/R/sl_xgboost_cv.RCheers,Chris-ck.mobileOn Dec 9, 2023, at 9:57 AM, Ramon Diaz-Uriarte @.***> wrote: Hi, thanks a lot for SuperLearner! I wonder if it is possible to leverage on xgb.cv to tune ntrees (nrounds in xgboost doc) without doing an explicit grid search over a set of ntrees. One very nice thing of xgb.cv is that, using early_stopping_rounds , we can stop the tunning of ntrees. Thus, when doing a grid search over parameters, we would not need to search over ntrees: just pass a large enough value of ntrees and use early_stopping_rounds (an example of doing a grid search for other parameters using this approach in https://bradleyboehmke.github.io/HOML/gbm.html#xgb-tuning-strategy). I have not found anything that does this with SuperLearner. I guess I would need to write my own, following the examples in https://github.com/ecpolley/SuperLearnerExtra/tree/master/SL (e.g., SL.gbmOOB). Am I missing something obvious?
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Thanks a lot!!!
Closing, since this was never a bug to begin with, and the wrapper by @ck37 worked perfectly (I've been happily using a modified version of it).
Hi, thanks a lot for SuperLearner!
I wonder if it is possible to leverage on
xgb.cv
to tunentrees
(nrounds
in xgboost doc) without doing an explicit grid search over a set ofntrees
. One very nice thing ofxgb.cv
is that, usingearly_stopping_rounds
, we can stop the tunning ofntrees
. Thus, when doing a grid search over parameters, we would not need to search overntrees
: just pass a large enough value ofntrees
and useearly_stopping_rounds
(an example of doing a grid search for other parameters using this approach in https://bradleyboehmke.github.io/HOML/gbm.html#xgb-tuning-strategy).I have not found anything that does this with SuperLearner. I guess I would need to write my own, following the examples in https://github.com/ecpolley/SuperLearnerExtra/tree/master/SL (e.g., SL.gbmOOB).
Am I missing something obvious?