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cerlymarco / shap-hypetune

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
MIT License
567 stars 71 forks source link

Callbacks for progress tracking #8

Closed tautrimas closed 2 years ago

tautrimas commented 2 years ago

If parameter tuning is not being used, evaluation metric is not printed.

Would you consider adding events/callbacks so that custom functions can be called for progress logging / inspecting / interrupting on condition?

Thanks for sharing your work @cerlymarco!

cerlymarco commented 2 years ago

Hi,

thanks for the feedback. You should use verbose >1 to print feature selection logs.

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