8000 AdaBoost: allow base_estimator=None (#26242) · scikit-learn/scikit-learn@72a6049 · GitHub
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AdaBoost: allow base_estimator=None (#26242)
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-3
lines changed

4 files changed

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-3
lines changed

‎doc/whats_new/v1.3.rst‎

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@@ -281,6 +281,10 @@ Changelog
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pandas' conventions.
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:pr:`25629` by `Thomas Fan`_.
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- |Fix| Fix deprecation of `base_estimator` in :class:`ensemble.AdaBoostClassifier`
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and :class:`ensemble.AdaBoostRegressor` that was introduced in :pr:`23819`.
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:pr:`26242` by :user:`Marko Toplak <markotoplak>`.
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:mod:`sklearn.exception`
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........................
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- |Feature| Added :class:`exception.InconsistentVersionWarning` which is raised

‎sklearn/ensemble/_base.py‎

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@@ -157,15 +157,18 @@ def _validate_estimator(self, default=None):
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if self.estimator is not None:
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self.estimator_ = self.estimator
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elif self.base_estimator not in [None, "deprecated"]:
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elif self.base_estimator != "deprecated":
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warnings.warn(
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(
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"`base_estimator` was renamed to `estimator` in version 1.2 and "
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"will be removed in 1.4."
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),
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FutureWarning,
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)
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self.estimator_ = self.base_estimator
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if self.base_estimator is not None:
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self.estimator_ = self.base_estimator
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else:
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self.estimator_ = default
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else:
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self.estimator_ = default
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‎sklearn/ensemble/_weight_boosting.py‎

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@@ -64,7 +64,11 @@ class BaseWeightBoosting(BaseEnsemble, metaclass=ABCMeta):
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"n_estimators": [Interval(Integral, 1, None, closed="left")],
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"learning_rate": [Interval(Real, 0, None, closed="neither")],
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"random_state": ["random_state"],
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"base_estimator": [HasMethods(["fit", "predict"]), StrOptions({"deprecated"})],
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"base_estimator": [
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HasMethods(["fit", "predict"]),
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StrOptions({"deprecated"}),
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None,
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],
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}
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@abstractmethod

‎sklearn/ensemble/tests/test_weight_boosting.py‎

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@@ -613,6 +613,27 @@ def test_base_estimator_argument_deprecated(AdaBoost, Estimator):
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model.fit(X, y)
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# TODO(1.4): remove in 1.4
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@pytest.mark.parametrize(
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"AdaBoost",
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[
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AdaBoostClassifier,
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AdaBoostRegressor,
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],
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)
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def test_base_estimator_argument_deprecated_none(AdaBoost):
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X = np.array([[1, 2], [3, 4]])
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y = np.array([1, 0])
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model = AdaBoost(base_estimator=None)
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warn_msg = (
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"`base_estimator` was renamed to `estimator` in version 1.2 and "
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"will be removed in 1.4."
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)
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with pytest.warns(FutureWarning, match=warn_msg):
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model.fit(X, y)
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# TODO(1.4): remove in 1.4
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@pytest.mark.parametrize(
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"AdaBoost",

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