8000 Revert "Make FrozenEstimator explicitly accept and ignore sample_weight" by OmarManzoor · Pull Request #30898 · scikit-learn/scikit-learn · GitHub
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Revert "Make FrozenEstimator explicitly accept and ignore sample_weight" #30898

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Merged
merged 1 commit into from
Feb 26, 2025
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Revert "Make FrozenEstimator explicitly accept and ignore sample_weight" #30898

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3 changes: 0 additions & 3 deletions doc/whats_new/upcoming_changes/sklearn.frozen/30874.enhancement.rst
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5 changes: 1 addition & 4 deletions sklearn/frozen/_frozen.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,7 @@ def __sklearn_is_fitted__(self):
except NotFittedError:
return False

def fit(self, X, y, sample_weight=None, *args, **kwargs):
def fit(self, X, y, *args, **kwargs):
"""No-op.

As a frozen estimator, calling `fit` has no effect.
Expand All @@ -99,9 +99,6 @@ def fit(self, X, y, sample_weight=None, *args, **kwargs):
y : object
Ignored.

sample_weight : object
Ignored.

*args : tuple
Additional positional arguments. Ignored, but present for API compatibility
with `self.estimator`.
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15 changes: 1 addition & 14 deletions sklearn/frozen/tests/test_frozen.py
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Expand Up @@ -26,7 +26,7 @@
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import RobustScaler, StandardScaler
from sklearn.utils._testing import set_random_state
from sklearn.utils.validation import check_is_fitted, has_fit_parameter
from sklearn.utils.validation import check_is_fitted


@pytest.fixture
Expand Down Expand Up @@ -221,16 +221,3 @@ def test_frozen_params():
other_est = LocalOutlierFactor()
frozen.set_params(estimator=other_est)
assert frozen.get_params() == {"estimator": other_est}


def test_frozen_ignores_sample_weight(regression_dataset):
X, y = regression_dataset
estimator = LinearRegression().fit(X, y)
frozen = FrozenEstimator(estimator)

# Should not raise: sample_weight is just ignored as it is not used.
frozen.fit(X, y, sample_weight=np.ones(len(y)))

# FrozenEstimator should have sample_weight in its signature to make it
# explicit that sample_weight is accepted and ignored intentionally.
assert has_fit_parameter(frozen, "sample_weight")
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