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Check feature_names_in_ for sklearn.model_selection #20850

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Merged
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Aug 26, 2021
Merged

Check feature_names_in_ for sklearn.model_selection #20850

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ba18d23
Check feature_names_in_ for sklearn.model_selection
ogrisel Aug 26, 2021
1ea3dd9
Simpligy phrasing
ogrisel Aug 26, 2021
8e1bfa0
Merge branch 'main' into feature_names_in_-model_selection
ogrisel Aug 26, 2021
fdf189b
Apply suggestions from code review
ogrisel Aug 26, 2021
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Merge branch 'main' into feature_names_in_-model_selection
ogrisel Aug 26, 2021
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31 changes: 27 additions & 4 deletions sklearn/model_selection/_search.py
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Original file line number Diff line number Diff line change
Expand Up @@ -858,6 +858,9 @@ def evaluate_candidates(candidate_params, cv=None, more_results=None):
refit_end_time = time.time()
self.refit_time_ = refit_end_time - refit_start_time

if hasattr(self.best_estimator_, "feature_names_in_"):
self.feature_names_in_ = self.best_estimator_.feature_names_in_

# Store the only scorer not as a dict for single metric evaluation
self.scorer_ = scorers

Expand Down Expand Up @@ -1246,11 +1249,21 @@ class GridSearchCV(BaseSearchCV):
the underlying estimator is a classifier.

n_features_in_ : int
Number of features seen during :term:`fit`. Only defined if the
underlying estimator exposes such an attribute when fit.
Number of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`n_features_in_` when fit.

.. versionadded:: 0.24

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`feature_names_in_` when fit.

.. versionadded:: 1.0

Notes
-----
The parameters selected are those that maximize the score of the left out
Expand Down Expand Up @@ -1595,11 +1608,21 @@ class RandomizedSearchCV(BaseSearchCV):
the underlying estimator is a classifier.

n_features_in_ : int
Number of features seen during :term:`fit`. Only defined if the
underlying estimator exposes such an attribute when fit.
Number of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`n_features_in_` when fit.

.. versionadded:: 0.24

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`feature_names_in_` when fit.

.. versionadded:: 1.0

Notes
-----
The parameters selected are those that maximize the score of the held-out
Expand Down
28 changes: 24 additions & 4 deletions sklearn/model_selection/_search_successive_halving.py
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Expand Up @@ -626,11 +626,21 @@ class HalvingGridSearchCV(BaseSuccessiveHalving):
the underlying estimator is a classifier.

n_features_in_ : int
Number of features seen during :term:`fit`. Only defined if the
underlying estimator exposes such an attribute when fit.
Number of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`n_features_in_` when fit.

.. versionadded:: 0.24

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`feature_names_in_` when fit.

.. versionadded:: 1.0

See Also
--------
:class:`HalvingRandomSearchCV`:
Expand Down Expand Up @@ -954,11 +964,21 @@ class HalvingRandomSearchCV(BaseSuccessiveHalving):
the underlying estimator is a classifier.

n_features_in_ : int
Number of features seen during :term:`fit`. Only defined if the
underlying estimator exposes such an attribute when fit.
Number of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`n_features_in_` when fit.

.. versionadded:: 0.24

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during :term:`fit`. Only defined if
`best_estimator_` is defined (see the documentation for the `refit`
parameter for more details) and that `best_estimator_` exposes
`feature_names_in_` when fit.

.. versionadded:: 1.0

See Also
--------
:class:`HalvingGridSearchCV`:
Expand Down
7 changes: 5 additions & 2 deletions sklearn/tests/test_common.py
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Expand Up @@ -325,11 +325,14 @@ def test_check_n_features_in_after_fitting(estimator):

COLUMN_NAME_MODULES_TO_IGNORE = {
"compose",
"model_selection",
}

_estimators_to_test = list(
chain(_tested_estimators(), [make_pipeline(LogisticRegression(C=1))])
chain(
_tested_estimators(),
[make_pipeline(LogisticRegression(C=1))],
list(_generate_search_cv_instances()),
)
)


Expand Down