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ENH Checks n_features_in_ after fitting in random_projection #19541

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Merged
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Feb 25, 2021
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ENH Checks n_features_in_ after fitting in random_projection #19541

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5 changes: 2 additions & 3 deletions sklearn/random_projection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@
from .utils import check_random_state
from .utils.extmath import safe_sparse_dot
from .utils.random import sample_without_replacement
from .utils.validation import check_array, check_is_fitted
from .utils.validation import check_is_fitted
from .utils.validation import _deprecate_positional_args
from .exceptions import DataDimensionalityWarning

Expand Down Expand Up @@ -402,9 +402,8 @@ def transform(self, X):
X_new : {ndarray, sparse matrix} of shape (n_samples, n_components)
Projected array.
"""
X = check_array(X, accept_sparse=['csr', 'csc'])

check_is_fitted(self)
X = self._validate_data(X, accept_sparse=['csr', 'csc'], reset=False)

if X.shape[1] != self.components_.shape[1]:
raise ValueError(
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1 change: 0 additions & 1 deletion sklearn/tests/test_common.py
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Expand Up @@ -274,7 +274,6 @@ def test_search_cv(estimator, check, request):
'multiclass',
'multioutput',
'pipeline',
'random_projection',
}

N_FEATURES_IN_AFTER_FIT_ESTIMATORS = [
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