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dmlc / XGBoost.jl

XGBoost Julia Package
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Hyperparameter Tuning #80

Closed Sinansi closed 4 years ago

Sinansi commented 4 years ago

Hello,

May someone confirm whether this package support hyperparameter tuning? Either grid or random search? If not, any plan to add it in the future?

Thank you!

ablaom commented 4 years ago

XGBoost is a model supported by the MLJ.jl machine learning platform which, among other things, allows you to tune models with a grid search (more options coming soon).

You can look at this XGBoost example but note that the tuning API has changed a little since that was written (specifically, how you specify the range). See here and here for the latest API

ablaom commented 4 years ago

Okay, there is an up-to-date XGBoost tuning example here.

ablaom commented 4 years ago

You may also want to check out EvoTrees.jl, a pure julia alternative to XGBoost for which an MLJ interface is a work-in-progress.

Sinansi commented 4 years ago

Dear Dr. Anthony, Thanks alot for your great help. This package seems promising. I was just going to ask you about hyper tuning it, but I saw your comment regarding integrating it with MLJ. I can't wait to fully utilize this package. Looking forward to MLJ future releases. Thanks again!