diff --git a/sklearn/datasets/_samples_generator.py b/sklearn/datasets/_samples_generator.py
index 4c66489f3ca54..22205e6732833 100644
--- a/sklearn/datasets/_samples_generator.py
+++ b/sklearn/datasets/_samples_generator.py
@@ -1411,7 +1411,7 @@ def make_sparse_spd_matrix(
 
     norm_diag : bool, default=False
         Whether to normalize the output matrix to make the leading diagonal
-        elements all 1
+        elements all 1.
 
     smallest_coef : float, default=0.1
         The value of the smallest coefficient between 0 and 1.
@@ -1429,15 +1429,15 @@ def make_sparse_spd_matrix(
     prec : sparse matrix of shape (dim, dim)
         The generated matrix.
 
+    See Also
+    --------
+    make_spd_matrix : Generate a random symmetric, positive-definite matrix.
+
     Notes
     -----
     The sparsity is actually imposed on the cholesky factor of the matrix.
     Thus alpha does not translate directly into the filling fraction of
     the matrix itself.
-
-    See Also
-    --------
-    make_spd_matrix
     """
     random_state = check_random_state(random_state)
 
diff --git a/sklearn/tests/test_docstrings.py b/sklearn/tests/test_docstrings.py
index 7c1409b4b3f02..0d53251adc9a5 100644
--- a/sklearn/tests/test_docstrings.py
+++ b/sklearn/tests/test_docstrings.py
@@ -36,7 +36,6 @@
     "sklearn.datasets._samples_generator.make_multilabel_classification",
     "sklearn.datasets._samples_generator.make_regression",
     "sklearn.datasets._samples_generator.make_sparse_coded_signal",
-    "sklearn.datasets._samples_generator.make_sparse_spd_matrix",
     "sklearn.datasets._samples_generator.make_spd_matrix",
     "sklearn.datasets._species_distributions.fetch_species_distributions",
     "sklearn.datasets._svmlight_format_io.dump_svmlight_file",