DOC Ensures that mean_pinball_loss passes numpydoc validation (#24336)

ichko · web-flow · commit 01775ecb8565 · 2022-09-02T19:53:17.000+02:00
diff --git a/sklearn/metrics/_regression.py b/sklearn/metrics/_regression.py
@@ -226,8 +226,8 @@ def mean_pinball_loss(
     sample_weight : array-like of shape (n_samples,), default=None
         Sample weights.
 
-    alpha: float, slope of the pinball loss, default=0.5,
-        this loss is equivalent to :ref:`mean_absolute_error` when `alpha=0.5`,
+    alpha : float, slope of the pinball loss, default=0.5,
+        This loss is equivalent to :ref:`mean_absolute_error` when `alpha=0.5`,
         `alpha=0.95` is minimized by estimators of the 95th percentile.
 
     multioutput : {'raw_values', 'uniform_average'}  or array-like of shape \
diff --git a/sklearn/tests/test_docstrings.py b/sklearn/tests/test_docstrings.py
@@ -19,7 +19,6 @@
     "sklearn.metrics._plot.precision_recall_curve.plot_precision_recall_curve",
     "sklearn.metrics._ranking.dcg_score",
     "sklearn.metrics._ranking.roc_curve",
-    "sklearn.metrics._regression.mean_pinball_loss",
     "sklearn.metrics.cluster._bicluster.consensus_score",
     "sklearn.metrics.cluster._supervised.adjusted_mutual_info_score",
     "sklearn.metrics.cluster._supervised.adjusted_rand_score",
