ENH Raise NotFittedError in get_feature_names_out for Imputers and Isotonic Regression (#25367)

rprkh · glemaitre · web-flow · commit 7c91462fdb65 · 2023-01-18T09:47:22.000-05:00
Co-authored-by: Guillaume Lemaitre &lt;g.lemaitre58@gmail.com&gt;
diff --git a/doc/whats_new/v1.3.rst b/doc/whats_new/v1.3.rst
@@ -41,12 +41,12 @@ Changes impacting all modules
   raises a `NotFittedError` if the instance is not fitted. This ensures the error is
   consistent in all estimators with the `get_feature_names_out` method.
 
-  - :class:`ensemble.StackingClassifier`
-  - :class:`ensemble.StackingRegressor`
-  - :class:`ensemble.VotingClassifier`
-  - :class:`ensemble.VotingRegressor`
   - :class:`feature_extraction.text.TfidfTransformer`
   - :class:`kernel_approximation.AdditiveChi2Sampler`
+  - :class:`impute.IterativeImputer`
+  - :class:`impute.KNNImputer`
+  - :class:`impute.SimpleImputer`
+  - :class:`isotonic.IsotonicRegression`
   - :class:`preprocessing.Binarizer`
   - :class:`preprocessing.MaxAbsScaler`
   - :class:`preprocessing.MinMaxScaler`
@@ -60,8 +60,8 @@ Changes impacting all modules
   The `NotFittedError` displays an informative message asking to fit the instance
   with the appropriate arguments.
 
-  :pr:`25294` by :user:`John Pangas <jpangas>` and :pr:`25291`, :pr:`25324`
-  by :user:`Rahil Parikh <rprkh>`.
+  :pr:`25294` by :user:`John Pangas <jpangas>` and :pr:`25291`, :pr:`25367` by
+  :user:`Rahil Parikh <rprkh>`.
 
 Changelog
 ---------
diff --git a/sklearn/impute/_base.py b/sklearn/impute/_base.py
@@ -709,6 +709,7 @@ def get_feature_names_out(self, input_features=None):
         feature_names_out : ndarray of str objects
             Transformed feature names.
         """
+        check_is_fitted(self, "n_features_in_")
         input_features = _check_feature_names_in(self, input_features)
         non_missing_mask = np.logical_not(_get_mask(self.statistics_, np.nan))
         names = input_features[non_missing_mask]
diff --git a/sklearn/impute/_iterative.py b/sklearn/impute/_iterative.py
@@ -897,6 +897,7 @@ def get_feature_names_out(self, input_features=None):
         feature_names_out : ndarray of str objects
             Transformed feature names.
         """
+        check_is_fitted(self, "n_features_in_")
         input_features = _check_feature_names_in(self, input_features)
         names = self.initial_imputer_.get_feature_names_out(input_features)
         return self._concatenate_indicator_feature_names_out(names, input_features)
diff --git a/sklearn/impute/_knn.py b/sklearn/impute/_knn.py
@@ -386,6 +386,7 @@ def get_feature_names_out(self, input_features=None):
         feature_names_out : ndarray of str objects
             Transformed feature names.
         """
+        check_is_fitted(self, "n_features_in_")
         input_features = _check_feature_names_in(self, input_features)
         names = input_features[self._valid_mask]
         return self._concatenate_indicator_feature_names_out(names, input_features)
diff --git a/sklearn/isotonic.py b/sklearn/isotonic.py
@@ -12,7 +12,7 @@
 
 from .base import BaseEstimator, TransformerMixin, RegressorMixin
 from .utils import check_array, check_consistent_length
-from .utils.validation import _check_sample_weight
+from .utils.validation import _check_sample_weight, check_is_fitted
 from .utils._param_validation import Interval, StrOptions
 from ._isotonic import _inplace_contiguous_isotonic_regression, _make_unique
 
@@ -429,6 +429,7 @@ def get_feature_names_out(self, input_features=None):
         feature_names_out : ndarray of str objects
             An ndarray with one string i.e. ["isotonicregression0"].
         """
+        check_is_fitted(self, "f_")
         class_name = self.__class__.__name__.lower()
         return np.asarray([f"{class_name}0"], dtype=object)
 
diff --git a/sklearn/tests/test_common.py b/sklearn/tests/test_common.py
@@ -466,10 +466,7 @@ def test_transformers_get_feature_names_out(transformer):
     "DictVectorizer",
     "GaussianRandomProjection",
     "GenericUnivariateSelect",
-    "IterativeImputer",
-    "IsotonicRegression",
     "KBinsDiscretizer",
-    "KNNImputer",
     "MissingIndicator",
     "RFE",
     "RFECV",
@@ -480,7 +477,6 @@ def test_transformers_get_feature_names_out(transformer):
     "SelectKBest",
     "SelectPercentile",
     "SequentialFeatureSelector",
-    "SimpleImputer",
     "SparseRandomProjection",
     "SplineTransformer",
     "VarianceThreshold",
