API Deprecate n_feature_ fitted attribute in PCA (#24421)

doc/whats_new/v1.2.rst

@@ -192,6 +192,11 @@ Changelog
   :pr:`11860` by :user:`Pierre Ablin <pierreablin>`,
   :pr:`22527` by :user:`Meekail Zain <micky774>` and `Thomas Fan`_.
 
+- |API| The `n_features_` attribute of
+  :class:`decomposition.PCA` is deprecated in favor of
+  `n_features_in_` and will be removed in 1.4. :pr:`24421` by
+  :user:`Kshitij Mathur <Kshitij68>`.
+
 :mod:`sklearn.discriminant_analysis`
 ....................................
 

sklearn/decomposition/_pca.py

@@ -22,6 +22,7 @@
 from ._base import _BasePCA
 from ..utils import check_random_state
 from ..utils._arpack import _init_arpack_v0
+from ..utils.deprecation import deprecated
 from ..utils.extmath import fast_logdet, randomized_svd, svd_flip
 from ..utils.extmath import stable_cumsum
 from ..utils.validation import check_is_fitted
@@ -402,6 +403,16 @@ def __init__(
         self.power_iteration_normalizer = power_iteration_normalizer
         self.random_state = random_state
 
+    # TODO(1.4): remove in 1.4
+    # mypy error: Decorated property not supported
+    @deprecated(  # type: ignore
+        "Attribute `n_features_` was deprecated in version 1.2 and will be "
+        "removed in 1.4. Use `n_features_in_` instead."
+    )
+    @property
+    def n_features_(self):
+        return self.n_features_in_
+
     def fit(self, X, y=None):
         """Fit the model with X.
 
@@ -552,7 +563,7 @@ def _fit_full(self, X, n_components):
         else:
             self.noise_variance_ = 0.0
 
-        self.n_samples_, self.n_features_ = n_samples, n_features
+        self.n_samples_ = n_samples
         self.components_ = components_[:n_components]
         self.n_components_ = n_components
         self.explained_variance_ = explained_variance_[:n_components]
@@ -614,7 +625,7 @@ def _fit_truncated(self, X, n_components, svd_solver):
                 random_state=random_state,
             )
 
-        self.n_samples_, self.n_features_ = n_samples, n_features
+        self.n_samples_ = n_samples
         self.components_ = Vt
         self.n_components_ = n_components
 

sklearn/decomposition/tests/test_sparse_pca.py

@@ -289,6 +289,13 @@ def test_spca_n_iter_deprecation():
     assert model.n_iter_ <= max_iter
 
 
+def test_pca_n_features_deprecation():
+    X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
+    pca = PCA(n_components=2).fit(X)
+    with pytest.warns(FutureWarning, match="`n_features_` was deprecated"):
+        pca.n_features_
+
+
 def test_spca_early_stopping(global_random_seed):
     """Check that `tol` and `max_no_improvement` act as early stopping."""
     rng = np.random.RandomState(global_random_seed)