Make error message uniform when calling `get_feature_names_out` before `fit`

While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.

From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors when `get_feature_names_out` is called before `fit`. Currently, these estimators have been whitelisted. Before we submit any PR for a particular estimator, we can remove the estimator from the list and run the test in #25223 to check if the code we submitted has raised the correct `NotFittedError`.

> Remember to add your estimator and PR in the same change log entry in `v1.3.rst` introduced in #25294.
Please link the PRs you'll make with this issue so that I can update this list for all of us to know which estimators have been worked on:

- [x] AdditiveChi2Sampler() #25291 
- [x] Binarizer()  #25294
- [x] MaxAbsScaler() #25294
- [x] MinMaxScaler() #25294
- [x] Normalizer()  #25294
- [x] OrdinalEncoder()  #25294
- [x] PowerTransformer() #25294
- [x] QuantileTransformer()  #25294
- [x] RobustScaler() #25294
- [x] StackingClassifier() #25324
- [x] StackingRegressor() #25324
- [x] StandardScaler() #25294
- [x] TfidfTransformer()  #25294
- [x] VotingClassifier() #25324 
- [x] VotingRegressor() #25324
- [x] GaussianRandomProjection() #25308
- [x] GenericUnivariateSelect() #25308
- [x] IterativeImputer() #25367 
- [x] RFE() #25308
- [x] RFECV() #25308 
- [x] SelectFdr() #25308 
- [x] SelectFpr() #25308
- [x] SelectFromModel() #25308
- [x] SelectFwe() #25308
- [x] SelectKBest() #25308
- [x] SelectPercentile() #25308 
- [x] SequentialFeatureSelector() #25308  
- [x] SparseRandomProjection()  #25308
- [x] VarianceThreshold() #25308
- [x] KNNImputer() #25367
- [x] SimpleImputer() #25367 
- [x] SplineTransformer() #25402
- [x] DictVectorizer() #25402
- [x] KBinsDiscretizer() #25402
- [x] MissingIndicator() #25402
- [x] IsotonicRegression()

<details>

```pytb
> pytest -vsl sklearn/tests/test_common.py -k error_get_feature_names_out
==================================================================================== test session starts ====================================================================================
platform darwin -- Python 3.10.6, pytest-7.2.0, pluggy-1.0.0 -- /Users/glemaitre/mambaforge/envs/dev/bin/python3.10
cachedir: .pytest_cache
rootdir: /Users/glemaitre/Documents/packages/scikit-learn, configfile: setup.cfg
plugins: xdist-3.0.2, anyio-3.6.2
collected 9473 items / 9275 deselected / 198 selected                                                                                                                                       

sklearn/tests/test_common.py::test_estimators[ARDRegression()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[AdaBoostClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[AdaBoostRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[AdditiveChi2Sampler()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[AffinityPropagation()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[AgglomerativeClustering()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[BaggingClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[BaggingRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[BayesianGaussianMixture()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[BayesianRidge()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[BernoulliNB()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[BernoulliRBM()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This BernoulliRBM instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[Binarizer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[Birch()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This Birch instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[BisectingKMeans()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This BisectingKMeans instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[CCA()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This CCA instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[CalibratedClassifierCV(estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[CategoricalNB()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[ComplementNB()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[DBSCAN()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[DecisionTreeClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[DecisionTreeRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[DictionaryLearning()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This DictionaryLearning instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[DummyClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[DummyRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[ElasticNet()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[ElasticNetCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[EllipticEnvelope()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[EmpiricalCovariance()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[ExtraTreeClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[ExtraTreeRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[FactorAnalysis()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This FactorAnalysis instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[FastICA()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This FastICA instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[FeatureAgglomeration()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This FeatureAgglomeration instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[FunctionTransformer()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GammaRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GaussianMixture()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GaussianNB()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GaussianProcessClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GaussianProcessRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GaussianRandomProjection()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GenericUnivariateSelect()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[GradientBoostingClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GradientBoostingRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GraphicalLasso()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[GraphicalLassoCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[HistGradientBoostingClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[HistGradientBoostingRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[HuberRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[IncrementalPCA()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This IncrementalPCA instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[IsolationForest()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[Isomap()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This Isomap instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[KBinsDiscretizer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[KMeans()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This KMeans instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[KNNImputer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[KNeighborsClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[KNeighborsRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[KNeighborsTransformer()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This KNeighborsTransformer instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[KernelCenterer()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This KernelCenterer instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[KernelDensity()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[KernelPCA()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This KernelPCA instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[KernelRidge()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LabelPropagation()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LabelSpreading()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[Lars()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LarsCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[Lasso()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LassoCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LassoLars()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LassoLarsCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LassoLarsIC()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LatentDirichletAllocation()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This LatentDirichletAllocation instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[LedoitWolf()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LinearDiscriminantAnalysis()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This LinearDiscriminantAnalysis instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[LinearRegression()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LinearSVC()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LinearSVR()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LocalOutlierFactor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LocallyLinearEmbedding()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This LocallyLinearEmbedding instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[LogisticRegression()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[LogisticRegressionCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MDS()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MLPClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MLPRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MaxAbsScaler()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[MeanShift()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MinCovDet()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MinMaxScaler()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[MiniBatchDictionaryLearning()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This MiniBatchDictionaryLearning instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[MiniBatchKMeans()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This MiniBatchKMeans instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[MiniBatchNMF()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This MiniBatchNMF instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[MiniBatchSparsePCA()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This MiniBatchSparsePCA instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[MissingIndicator()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[MultiOutputRegressor(estimator=Ridge())-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MultiTaskElasticNet()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MultiTaskElasticNetCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MultiTaskLasso()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MultiTaskLassoCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[MultinomialNB()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[NMF()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This NMF instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[NearestCentroid()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[NearestNeighbors()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[NeighborhoodComponentsAnalysis()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This NeighborhoodComponentsAnalysis instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[Normalizer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[NuSVC()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[NuSVR()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[Nystroem()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This Nystroem instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[OAS()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[OPTICS()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[OneClassSVM()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[OneVsOneClassifier(estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[OneVsRestClassifier(estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[OrthogonalMatchingPursuit()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[OrthogonalMatchingPursuitCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[OutputCodeClassifier(estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[PCA()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This PCA instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[PLSCanonical()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This PLSCanonical instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[PLSRegression()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This PLSRegression instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[PLSSVD()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This PLSSVD instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[PassiveAggressiveClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[PassiveAggressiveRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[Perceptron()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[PoissonRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[PolynomialCountSketch()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This PolynomialCountSketch instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[PolynomialFeatures()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This PolynomialFeatures instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[PowerTransformer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[QuadraticDiscriminantAnalysis()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[QuantileRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[QuantileTransformer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[RANSACRegressor(estimator=LinearRegression())-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RBFSampler()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This RBFSampler instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[RFE(estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[RFECV(estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[RadiusNeighborsClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RadiusNeighborsRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RadiusNeighborsTransformer()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This RadiusNeighborsTransformer instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[RandomForestClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RandomForestRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RandomTreesEmbedding()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This RandomTreesEmbedding instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[RegressorChain(base_estimator=Ridge())-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[Ridge()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RidgeCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RidgeClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RidgeClassifierCV()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[RobustScaler()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SGDClassifier()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SGDOneClassSVM()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SGDRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SVC()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SVR()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SelectFdr()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SelectFpr()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SelectFromModel(estimator=SGDRegressor(random_state=0))-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SelectFwe()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SelectKBest()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SelectPercentile()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SelfTrainingClassifier(base_estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SequentialFeatureSelector(estimator=LogisticRegression(C=1))-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[ShrunkCovariance()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SimpleImputer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[SkewedChi2Sampler()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This SkewedChi2Sampler instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[SparsePCA()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This SparsePCA instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[SparseRandomProjection()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SpectralBiclustering()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SpectralClustering()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SpectralCoclustering()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SpectralEmbedding()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[SplineTransformer()-check_error_get_feature_names_out_not_fitted] 

<class 'AttributeError'>
'SplineTransformer' object has no attribute 'bsplines_'

PASSED
sklearn/tests/test_common.py::test_estimators[StackingClassifier(estimators=[('est1',LogisticRegression(C=0.1)),('est2',LogisticRegression(C=1))])-check_error_get_feature_names_out_not_fitted] 

<class 'AttributeError'>
'StackingClassifier' object has no attribute '_n_feature_outs'

PASSED
sklearn/tests/test_common.py::test_estimators[StackingRegressor(estimators=[('est1',Ridge(alpha=0.1)),('est2',Ridge(alpha=1))])-check_error_get_feature_names_out_not_fitted] 

<class 'AttributeError'>
'StackingRegressor' object has no attribute '_n_feature_outs'

PASSED
sklearn/tests/test_common.py::test_estimators[StandardScaler()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[TSNE()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[TfidfTransformer()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[TheilSenRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[TransformedTargetRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[TruncatedSVD()-check_error_get_feature_names_out_not_fitted] 

<class 'sklearn.exceptions.NotFittedError'>
This TruncatedSVD instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

PASSED
sklearn/tests/test_common.py::test_estimators[TweedieRegressor()-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[VarianceThreshold()-check_error_get_feature_names_out_not_fitted] 

<class 'ValueError'>
Unable to generate feature names without n_features_in_

PASSED
sklearn/tests/test_common.py::test_estimators[VotingClassifier(estimators=[('est1',LogisticRegression(C=0.1)),('est2',LogisticRegression(C=1))])-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_estimators[VotingRegressor(estimators=[('est1',Ridge(alpha=0.1)),('est2',Ridge(alpha=1))])-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[GridSearchCV(cv=2,estimator=Ridge(),param_grid={'alpha':[0.1,1.0]})-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[GridSearchCV(cv=2,estimator=LogisticRegression(),param_grid={'C':[0.1,1.0]})-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingGridSearchCV(cv=2,estimator=Ridge(),min_resources='smallest',param_grid={'alpha':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted0] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingGridSearchCV(cv=2,estimator=LogisticRegression(),min_resources='smallest',param_grid={'C':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted0] PASSED
sklearn/tests/test_common.py::test_search_cv[RandomizedSearchCV(cv=2,estimator=Ridge(),param_distributions={'alpha':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[RandomizedSearchCV(cv=2,estimator=LogisticRegression(),param_distributions={'C':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingGridSearchCV(cv=2,estimator=Ridge(),min_resources='smallest',param_grid={'alpha':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted1] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingGridSearchCV(cv=2,estimator=LogisticRegression(),min_resources='smallest',param_grid={'C':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted1] PASSED
sklearn/tests/test_common.py::test_search_cv[GridSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('ridge',Ridge())]),param_grid={'ridge__alpha':[0.1,1.0]})-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[GridSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('logisticregression',LogisticRegression())]),param_grid={'logisticregression__C':[0.1,1.0]})-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingGridSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('ridge',Ridge())]),min_resources='smallest',param_grid={'ridge__alpha':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingGridSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('logisticregression',LogisticRegression())]),min_resources='smallest',param_grid={'logisticregression__C':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[RandomizedSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('ridge',Ridge())]),param_distributions={'ridge__alpha':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[RandomizedSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('logisticregression',LogisticRegression())]),param_distributions={'logisticregression__C':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingRandomSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('ridge',Ridge())]),param_distributions={'ridge__alpha':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
sklearn/tests/test_common.py::test_search_cv[HalvingRandomSearchCV(cv=2,error_score='raise',estimator=Pipeline(steps=[('pca',PCA()),('logisticregression',LogisticRegression())]),param_distributions={'logisticregression__C':[0.1,1.0]},random_state=0)-check_error_get_feature_names_out_not_fitted] PASSED
```

</details>

I assume that the most adequate error should be a `NotFittedError` asking to fit the estimator.

@scikit-learn/core-devs WDYT?

COMMENT:
@AlexBuzenet, I created a common test and ran it on all estimators with ```get feature names out```. Please take a look at the details below.  You can see the estimators which raise a ```NotFittedError``` and those that raise other types of Errors. 
<details>
<pre>(sklearn-dev) <font color="#26A269"><b>john@SwiftyXSwaggy</b></font>:<font color="#12488B"><b>~/Documents/Local_Code/scikit-learn</b></font>$ pytest -vsl sklearn/tests/test_common.py -k error_check_get_feature_names_out
<b>============================================================================ test session starts ============================================================================</b>
platform linux -- Python 3.9.15, pytest-7.2.0, pluggy-1.0.0 -- /home/john/miniconda3/envs/sklearn-dev/bin/python3.9
cachedir: .pytest_cache
rootdir: /home/john/Documents/Local_Code/scikit-learn, configfile: setup.cfg
plugins: cov-4.0.0, xdist-3.1.0
<b>collected 9597 items / 9400 deselected / 197 selected                                                                                                                       </b>

sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ARDRegression()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[AdaBoostClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[AdaBoostRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[AdditiveChi2Sampler()] (&apos;AdditiveChi2Sampler&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[AffinityPropagation()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[AgglomerativeClustering()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[BaggingClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[BaggingRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[BayesianGaussianMixture()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[BayesianRidge()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[BernoulliNB()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[BernoulliRBM()] (&apos;BernoulliRBM&apos;, NotFittedError(&quot;This BernoulliRBM instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Binarizer()] (&apos;Binarizer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Birch()] (&apos;Birch&apos;, NotFittedError(&quot;This Birch instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[BisectingKMeans()] (&apos;BisectingKMeans&apos;, NotFittedError(&quot;This BisectingKMeans instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[CCA()] (&apos;CCA&apos;, NotFittedError(&quot;This CCA instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[CalibratedClassifierCV(estimator=LogisticRegression(C=1))] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[CategoricalNB()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ClassifierChain(base_estimator=LogisticRegression(C=1))] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ComplementNB()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[CountVectorizer()] (&apos;CountVectorizer&apos;, NotFittedError(&apos;Vocabulary not fitted or provided&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[DBSCAN()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[DecisionTreeClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[DecisionTreeRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[DictVectorizer()] (&apos;DictVectorizer&apos;, AttributeError(&quot;&apos;DictVectorizer&apos; object has no attribute &apos;feature_names_&apos;&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[DictionaryLearning()] (&apos;DictionaryLearning&apos;, NotFittedError(&quot;This DictionaryLearning instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[DummyClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[DummyRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ElasticNet()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ElasticNetCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[EllipticEnvelope()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[EmpiricalCovariance()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ExtraTreeClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ExtraTreeRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ExtraTreesClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ExtraTreesRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[FactorAnalysis()] (&apos;FactorAnalysis&apos;, NotFittedError(&quot;This FactorAnalysis instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[FastICA()] (&apos;FastICA&apos;, NotFittedError(&quot;This FastICA instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[FeatureAgglomeration()] (&apos;FeatureAgglomeration&apos;, NotFittedError(&quot;This FeatureAgglomeration instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[FeatureHasher()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[FunctionTransformer()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GammaRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GaussianMixture()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GaussianNB()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GaussianProcessClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GaussianProcessRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GaussianRandomProjection()] (&apos;GaussianRandomProjection&apos;, TypeError(&quot;&apos;str&apos; object cannot be interpreted as an integer&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GenericUnivariateSelect()] (&apos;GenericUnivariateSelect&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GradientBoostingClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GradientBoostingRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GraphicalLasso()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[GraphicalLassoCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[HashingVectorizer()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[HistGradientBoostingClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[HistGradientBoostingRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[HuberRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[IncrementalPCA()] (&apos;IncrementalPCA&apos;, NotFittedError(&quot;This IncrementalPCA instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[IsolationForest()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Isomap()] (&apos;Isomap&apos;, NotFittedError(&quot;This Isomap instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[IsotonicRegression()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[IterativeImputer()] (&apos;IterativeImputer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KBinsDiscretizer()] (&apos;KBinsDiscretizer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KMeans()] (&apos;KMeans&apos;, NotFittedError(&quot;This KMeans instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KNNImputer()] (&apos;KNNImputer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KNeighborsClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KNeighborsRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KNeighborsTransformer()] (&apos;KNeighborsTransformer&apos;, NotFittedError(&quot;This KNeighborsTransformer instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KernelCenterer()] (&apos;KernelCenterer&apos;, NotFittedError(&quot;This KernelCenterer instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KernelDensity()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KernelPCA()] (&apos;KernelPCA&apos;, NotFittedError(&quot;This KernelPCA instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[KernelRidge()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LabelBinarizer()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LabelEncoder()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LabelPropagation()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LabelSpreading()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Lars()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LarsCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Lasso()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LassoCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LassoLars()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LassoLarsCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LassoLarsIC()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LatentDirichletAllocation()] (&apos;LatentDirichletAllocation&apos;, NotFittedError(&quot;This LatentDirichletAllocation instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LedoitWolf()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LinearDiscriminantAnalysis()] (&apos;LinearDiscriminantAnalysis&apos;, NotFittedError(&quot;This LinearDiscriminantAnalysis instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LinearRegression()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LinearSVC()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LinearSVR()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LocalOutlierFactor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LocallyLinearEmbedding()] (&apos;LocallyLinearEmbedding&apos;, NotFittedError(&quot;This LocallyLinearEmbedding instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LogisticRegression()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[LogisticRegressionCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MDS()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MLPClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MLPRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MaxAbsScaler()] (&apos;MaxAbsScaler&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MeanShift()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MinCovDet()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MinMaxScaler()] (&apos;MinMaxScaler&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MiniBatchDictionaryLearning()] (&apos;MiniBatchDictionaryLearning&apos;, NotFittedError(&quot;This MiniBatchDictionaryLearning instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MiniBatchKMeans()] (&apos;MiniBatchKMeans&apos;, NotFittedError(&quot;This MiniBatchKMeans instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MiniBatchNMF()] (&apos;MiniBatchNMF&apos;, NotFittedError(&quot;This MiniBatchNMF instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MiniBatchSparsePCA()] (&apos;MiniBatchSparsePCA&apos;, NotFittedError(&quot;This MiniBatchSparsePCA instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MissingIndicator()] (&apos;MissingIndicator&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultiLabelBinarizer()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultiOutputClassifier(estimator=LogisticRegression(C=1))] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultiOutputRegressor(estimator=Ridge())] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultiTaskElasticNet()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultiTaskElasticNetCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultiTaskLasso()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultiTaskLassoCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[MultinomialNB()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[NMF()] (&apos;NMF&apos;, NotFittedError(&quot;This NMF instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[NearestCentroid()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[NearestNeighbors()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[NeighborhoodComponentsAnalysis()] (&apos;NeighborhoodComponentsAnalysis&apos;, NotFittedError(&quot;This NeighborhoodComponentsAnalysis instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Normalizer()] (&apos;Normalizer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[NuSVC()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[NuSVR()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Nystroem()] (&apos;Nystroem&apos;, NotFittedError(&quot;This Nystroem instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OAS()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OPTICS()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OneClassSVM()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OneHotEncoder()] (&apos;OneHotEncoder&apos;, NotFittedError(&quot;This OneHotEncoder instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OneVsOneClassifier(estimator=LogisticRegression(C=1))] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OneVsRestClassifier(estimator=LogisticRegression(C=1))] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OrdinalEncoder()] (&apos;OrdinalEncoder&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OrthogonalMatchingPursuit()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OrthogonalMatchingPursuitCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[OutputCodeClassifier(estimator=LogisticRegression(C=1))] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PCA()] (&apos;PCA&apos;, NotFittedError(&quot;This PCA instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PLSCanonical()] (&apos;PLSCanonical&apos;, NotFittedError(&quot;This PLSCanonical instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PLSRegression()] (&apos;PLSRegression&apos;, NotFittedError(&quot;This PLSRegression instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PLSSVD()] (&apos;PLSSVD&apos;, NotFittedError(&quot;This PLSSVD instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PassiveAggressiveClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PassiveAggressiveRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PatchExtractor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Perceptron()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PoissonRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PolynomialCountSketch()] (&apos;PolynomialCountSketch&apos;, NotFittedError(&quot;This PolynomialCountSketch instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PolynomialFeatures()] (&apos;PolynomialFeatures&apos;, NotFittedError(&quot;This PolynomialFeatures instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[PowerTransformer()] (&apos;PowerTransformer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[QuadraticDiscriminantAnalysis()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[QuantileRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[QuantileTransformer()] (&apos;QuantileTransformer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RANSACRegressor(estimator=LinearRegression())] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RBFSampler()] (&apos;RBFSampler&apos;, NotFittedError(&quot;This RBFSampler instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RFE(estimator=LogisticRegression(C=1))] (&apos;RFE&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RFECV(estimator=LogisticRegression(C=1))] (&apos;RFECV&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RadiusNeighborsClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RadiusNeighborsRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RadiusNeighborsTransformer()] (&apos;RadiusNeighborsTransformer&apos;, NotFittedError(&quot;This RadiusNeighborsTransformer instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RandomForestClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RandomForestRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RandomTreesEmbedding()] (&apos;RandomTreesEmbedding&apos;, NotFittedError(&quot;This RandomTreesEmbedding instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RegressorChain(base_estimator=Ridge())] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[Ridge()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RidgeCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RidgeClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RidgeClassifierCV()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[RobustScaler()] (&apos;RobustScaler&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SGDClassifier()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SGDOneClassSVM()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SGDRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SVC()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SVR()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SelectFdr()] (&apos;SelectFdr&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SelectFpr()] (&apos;SelectFpr&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SelectFromModel(estimator=SGDRegressor(random_state=0))] (&apos;SelectFromModel&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SelectFwe()] (&apos;SelectFwe&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SelectKBest()] (&apos;SelectKBest&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SelectPercentile()] (&apos;SelectPercentile&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SelfTrainingClassifier(base_estimator=LogisticRegression(C=1))] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SequentialFeatureSelector(estimator=LogisticRegression(C=1))] (&apos;SequentialFeatureSelector&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[ShrunkCovariance()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SimpleImputer()] (&apos;SimpleImputer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SkewedChi2Sampler()] (&apos;SkewedChi2Sampler&apos;, NotFittedError(&quot;This SkewedChi2Sampler instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SparsePCA()] (&apos;SparsePCA&apos;, NotFittedError(&quot;This SparsePCA instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SparseRandomProjection()] (&apos;SparseRandomProjection&apos;, TypeError(&quot;&apos;str&apos; object cannot be interpreted as an integer&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SpectralBiclustering()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SpectralClustering()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SpectralCoclustering()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SpectralEmbedding()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[SplineTransformer()] (&apos;SplineTransformer&apos;, AttributeError(&quot;&apos;SplineTransformer&apos; object has no attribute &apos;bsplines_&apos;&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[StackingClassifier(estimators=[(&apos;est1&apos;,LogisticRegression(C=0.1)),(&apos;est2&apos;,LogisticRegression(C=1))])] (&apos;StackingClassifier&apos;, AttributeError(&quot;&apos;StackingClassifier&apos; object has no attribute &apos;_n_feature_outs&apos;&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[StackingRegressor(estimators=[(&apos;est1&apos;,Ridge(alpha=0.1)),(&apos;est2&apos;,Ridge(alpha=1))])] (&apos;StackingRegressor&apos;, AttributeError(&quot;&apos;StackingRegressor&apos; object has no attribute &apos;_n_feature_outs&apos;&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[StandardScaler()] (&apos;StandardScaler&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[TSNE()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[TfidfTransformer()] (&apos;TfidfTransformer&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[TfidfVectorizer()] (&apos;TfidfVectorizer&apos;, NotFittedError(&apos;Vocabulary not fitted or provided&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[TheilSenRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[TransformedTargetRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[TruncatedSVD()] (&apos;TruncatedSVD&apos;, NotFittedError(&quot;This TruncatedSVD instance is not fitted yet. Call &apos;fit&apos; with appropriate arguments before using this estimator.&quot;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[TweedieRegressor()] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[VarianceThreshold()] (&apos;VarianceThreshold&apos;, ValueError(&apos;Unable to generate feature names without n_features_in_&apos;))
<font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[VotingClassifier(estimators=[(&apos;est1&apos;,LogisticRegression(C=0.1)),(&apos;est2&apos;,LogisticRegression(C=1))])] <font color="#26A269">PASSED</font>
sklearn/tests/test_common.py::test_error_check_get_feature_names_out[VotingRegressor(estimators=[(&apos;est1&apos;,Ridge(alpha=0.1)),(&apos;est2&apos;,Ridge(alpha=1))])] <font color="#26A269">PASSED</font>

<font color="#A2734C">============================================================= </font><font color="#26A269">197 passed</font>, <font color="#A2734C"><b>9400 deselected</b></font>, <font color="#A2734C"><b>76 warnings</b></font><font color="#A2734C"> in 3.57s =============================================================</font>
</pre>
</details>

Labels: New Feature, Enhancement, help wanted, Meta-issue