DOC Ensure rbf_kernel passes numpydoc validation (#23954)

Mathews-Tom · jeremiedbb · web-flow · commit 095e46670a1e · 2022-07-21T11:36:03.000+02:00
Co-authored-by: Jérémie du Boisberranger &lt;34657725+jeremiedbb@users.noreply.github.com&gt;
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
@@ -1260,8 +1260,7 @@ def sigmoid_kernel(X, Y=None, gamma=None, coef0=1):
 
 
 def rbf_kernel(X, Y=None, gamma=None):
-    """
-    Compute the rbf (gaussian) kernel between X and Y::
+    """Compute the rbf (gaussian) kernel between X and Y.
 
         K(x, y) = exp(-gamma ||x-y||^2)
 
@@ -1272,16 +1271,18 @@ def rbf_kernel(X, Y=None, gamma=None):
     Parameters
     ----------
     X : ndarray of shape (n_samples_X, n_features)
+        A feature array.
 
     Y : ndarray of shape (n_samples_Y, n_features), default=None
-        If `None`, uses `Y=X`.
+        An optional second feature array. If `None`, uses `Y=X`.
 
     gamma : float, default=None
         If None, defaults to 1.0 / n_features.
 
     Returns
     -------
     kernel_matrix : ndarray of shape (n_samples_X, n_samples_Y)
+        The RBF kernel.
     """
     X, Y = check_pairwise_arrays(X, Y)
     if gamma is None:
diff --git a/sklearn/tests/test_docstrings.py b/sklearn/tests/test_docstrings.py
@@ -49,7 +49,6 @@
     "sklearn.metrics.cluster._supervised.v_measure_score",
     "sklearn.metrics.pairwise.pairwise_distances_chunked",
     "sklearn.metrics.pairwise.polynomial_kernel",
-    "sklearn.metrics.pairwise.rbf_kernel",
     "sklearn.metrics.pairwise.sigmoid_kernel",
     "sklearn.preprocessing._data.maxabs_scale",
     "sklearn.preprocessing._data.scale",
