Closed Rane90 closed 1 year ago
Thank you for your response.
I should have provided more details:
params
dict below)params = {'objective': 'binary',
'random_state': RANDOM_STATE_INTEGER_GLOBAL,
'metric': 'auc',
'is_unbalance': True
}
lgbm = lgb.LGBMClassifier(**params)
model = BoostBoruta(
lgbm, max_iter=200, perc=50,
importance_type='shap_importances', train_importance=False, alpha=0.01,
)
model.fit(X_train, y_train, eval_set=[
(X_val, y_val)], early_stopping_rounds=6, verbose=0)
you are using early_stopping_rounds
in fit
.
fit
simply call lgbm fit under the hood.
use callbacks=[lgb.early_stopping(6)]
instead of early_stopping_rounds
as stated on the links provided.
All the best
Thank you :)
The correct call is:
callbacks=[lgb.early_stopping(stopping_rounds=6)]
Hi,
While running
BoostBoruta
according to the notebook toturial I'm getting the following warnings which I would like to suppress:Any ideas on how to do that?
Thank you