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Support early stopping with training continuation, correct num boosted rounds. (#6506)

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* Implement early stopping with training continuation.

* Add new C API for obtaining boosted rounds.

* Fix off by 1 in `save_best`.

Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Jiaming Yuan
2020-12-17 19:59:19 +08:00
committed by GitHub
parent 125b3c0f2d
commit ca3da55de4
16 changed files with 210 additions and 118 deletions
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2
tests/python/test_with_sklearn.py
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@@ -62,6 +62,8 @@ def test_multiclass_classification():
kf = KFold(n_splits=2, shuffle=True, random_state=rng)
for train_index, test_index in kf.split(X, y):
xgb_model = xgb.XGBClassifier().fit(X[train_index], y[train_index])
assert (xgb_model.get_booster().num_boosted_rounds() ==
xgb_model.n_estimators)
preds = xgb_model.predict(X[test_index])
# test other params in XGBClassifier().fit
preds2 = xgb_model.predict(X[test_index], output_margin=True,