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FIX Raise appropriate attribute error in ensemble #25668

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Merged
merged 2 commits into from
Feb 27, 2023
Merged

FIX Raise appropriate attribute error in ensemble #25668

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afda19e
raise appropriate attr error
jeremiedbb Feb 23, 2023
578f11a
directly set estimator_
jeremiedbb Feb 27, 2023
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14 changes: 4 additions & 10 deletions sklearn/ensemble/_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -161,16 +161,16 @@ def _validate_estimator(self, default=None):
)

if self.estimator is not None:
self._estimator = self.estimator
self.estimator_ = self.estimator
elif self.base_estimator not in [None, "deprecated"]:
warnings.warn(
"`base_estimator` was renamed to `estimator` in version 1.2 and "
"will be removed in 1.4.",
FutureWarning,
)
self._estimator = self.base_estimator
self.estimator_ = self.base_estimator
else:
self._estimator = default
self.estimator_ = default

# TODO(1.4): remove
# mypy error: Decorated property not supported
Expand All @@ -181,13 +181,7 @@ def _validate_estimator(self, default=None):
@property
def base_estimator_(self):
"""Estimator used to grow the ensemble."""
return self._estimator

# TODO(1.4): remove
@property
def estimator_(self):
"""Estimator used to grow the ensemble."""
return self._estimator
return self.estimator_

def _make_estimator(self, append=True, random_state=None):
"""Make and configure a copy of the `estimator_` attribute.
Expand Down
24 changes: 24 additions & 0 deletions sklearn/ensemble/tests/test_base.py
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Expand Up @@ -12,10 +12,12 @@
from sklearn.ensemble import BaggingClassifier
from sklearn.ensemble._base import _set_random_states
from sklearn.linear_model import Perceptron
from sklearn.linear_model import Ridge, LogisticRegression
from collections import OrderedDict
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.pipeline import Pipeline
from sklearn.feature_selection import SelectFromModel
from sklearn import ensemble


def test_base():
Expand Down Expand Up @@ -117,3 +119,25 @@ def test_validate_estimator_value_error():
err_msg = "Both `estimator` and `base_estimator` were set. Only set `estimator`."
with pytest.raises(ValueError, match=err_msg):
model.fit(X, y)


# TODO(1.4): remove
@pytest.mark.parametrize(
"model",
[
ensemble.GradientBoostingClassifier(),
ensemble.GradientBoostingRegressor(),
ensemble.HistGradientBoostingClassifier(),
ensemble.HistGradientBoostingRegressor(),
ensemble.VotingClassifier(
[("a", LogisticRegression()), ("b", LogisticRegression())]
),
ensemble.VotingRegressor([("a", Ridge()), ("b", Ridge())]),
],
)
def test_estimator_attribute_error(model):
X = [[1], [2]]
y = [0, 1]
model.fit(X, y)

assert not hasattr(model, "estimator_")