2
$\begingroup$

How can it be that a xgboost.cv cross-validation operation where n-folds are evaluated is quicker than a single XGBoostClassifier.fit(X,y) of the xgboost.sklearn API?

$\endgroup$
1
$\begingroup$

I believe this is the answer: https://github.com/dmlc/xgboost/issues/651 the sklearn api uses n_estimators= 100 as default whereas xgb.train is using n_boost_rounds=10

As both refer to the same parameter this could explain the huge difference.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.