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And I'm wanting to know how I could potentially implement this in Feature Selector. Instead of using eval_metric='auc', is there a way I can rig this to use my metric? I'm not super clear on how LightGBM implements custom scoring metrics, but looks confusing from first glance lol.
Thanks!
The text was updated successfully, but these errors were encountered:
Not really an issue, just a general question, but I have made a scoring metric using the fbeta score that looks like this:
my_custom_scorer = make_scorer(fbeta_score, average='binary', zero_division=0, pos_label=1, beta=fbeta_for_scorer, greater_is_better=True)
And I'm wanting to know how I could potentially implement this in Feature Selector. Instead of using
eval_metric='auc'
, is there a way I can rig this to use my metric? I'm not super clear on how LightGBM implements custom scoring metrics, but looks confusing from first glance lol.Thanks!
The text was updated successfully, but these errors were encountered: