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TST Relax test_gradient_boosting_early_stopping #24541

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merged 3 commits into from Oct 7, 2022
Merged

TST Relax test_gradient_boosting_early_stopping #24541

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ebbf4ec
TST Relax test_gradient_boosting_early_stopping
jjerphan Sep 29, 2022
c47bbbd
TST Simplify test and split into two
jjerphan Sep 30, 2022
321221f
Update sklearn/ensemble/tests/test_gradient_boosting.py
jeremiedbb Oct 7, 2022
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16 changes: 13 additions & 3 deletions sklearn/ensemble/tests/test_gradient_boosting.py
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Expand Up @@ -1122,16 +1122,26 @@ def test_gradient_boosting_early_stopping():
)

X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)
# Check if early_stopping works as expected
for est, tol, early_stop_n_estimators in (
# Check if early_stopping works as expected, that is empirically check that the
# number of estimators is increasing when the tolerance decreases.

# Depending on platforms, the number of fitted estimators might slightly vary.
# Hence, we check for its inclusion in an interval centered in the expected
# number of fitted estimators rather than a strict equality.
delta_early_stop_n_estimators = 2
for est, tol, expected_early_stop_n_estimators in (
(gbc, 1e-1, 28),
(gbr, 1e-1, 13),
(gbc, 1e-3, 70),
(gbr, 1e-3, 28),
):
est.set_params(tol=tol)
est.fit(X_train, y_train)
assert est.n_estimators_ == early_stop_n_estimators
assert (
expected_early_stop_n_estimators - delta_early_stop_n_estimators
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I think it would be enough to have an upper bound with a less-than-operator.

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What I don't get here is why Python 3.11 would trigger this issue while other Windows builds are working.

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can we just follow the description of the test and simply check the following ?
gbc(tol=1e-1).fit(X, y).n_estimators_ < gbc(tol=1e-3).fit(X, y).n_estimators_

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Done in c47bbbd.

<= est.n_estimators_
<= expected_early_stop_n_estimators + delta_early_stop_n_estimators
)
assert est.score(X_test, y_test) > 0.7

# Without early stopping
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