upload the learner object with each run

[giuseppec]

There are sometimes bugs in mlr (e.g. mlr-org/mlr#2218) or OpenML (e.g. 171aee9 ) causing critical issues (e.g. some hyperparameters are not uploaded properly on the OpenML server).
Maybe we should always upload the learner object just to be sure that if something went wrong, one can still get the hyperparameters from the uploaded mlr learner object.
I thought of uploading just the result of getHyperPars(lrn) instead of the learner object itself, but this still does not solve the issue when there are also bugs in mlr (e.g. mlr-org/mlr#2218).

[joaquinvanschoren]

+1

On Mon, 12 Mar 2018 at 17:58 Giuseppe Casalicchio ***@***.***> wrote: There are sometimes bugs in mlr or OpenML causing an issue that hyperparameters are not stored properly on the OpenML server. Maybe we should always upload the learner object just to be sure that if something went wrong, one can still get the hyperparameters from the uploaded mlr learner object. I also thought of uploading just the result of getHyperPars(lrn) instead of the learner object itself, but this still does not solve the issue when there are also bugs in mlr (e.g. mlr-org/mlr#2218 <mlr-org/mlr#2218>). Uploading the learner also solves the issue for learners where user-defined functions are passed as hyperparameters. — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#411>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABpQV9sVt60-QF7WmykYoW8RTW4Vb-x0ks5tdqlBgaJpZM4SnA7r> .

-- Thank you, Joaquin

[giuseppec]

@joaquinvanschoren do you think this could be a file storage problem for the server? A mlr learner object can be up to 0.1 MegaByte and we currently have 9.000.000 runs now. Or are these peanuts?