DOC Ensures that RandomizedSearchCV passes numpydoc validation (#21131)

nikJ13 · web-flow · commit c588230dad7c · 2021-09-24T13:59:04.000+02:00
diff --git a/maint_tools/test_docstrings.py b/maint_tools/test_docstrings.py
@@ -32,7 +32,6 @@
     "PatchExtractor",
     "PolynomialFeatures",
     "QuadraticDiscriminantAnalysis",
-    "RandomizedSearchCV",
     "RobustScaler",
     "SelfTrainingClassifier",
     "SparseRandomProjection",
diff --git a/sklearn/model_selection/_search.py b/sklearn/model_selection/_search.py
@@ -1420,7 +1420,7 @@ class RandomizedSearchCV(BaseSearchCV):
 
     Parameters
     ----------
-    estimator : estimator object.
+    estimator : estimator object
         A object of that type is instantiated for each grid point.
         This is assumed to implement the scikit-learn estimator interface.
         Either estimator needs to provide a ``score`` function,
@@ -1692,6 +1692,12 @@ class RandomizedSearchCV(BaseSearchCV):
 
         .. versionadded:: 1.0
 
+    See Also
+    --------
+    GridSearchCV : Does exhaustive search over a grid of parameters.
+    ParameterSampler : A generator over parameter settings, constructed from
+        param_distributions.
+
     Notes
     -----
     The parameters selected are those that maximize the score of the held-out
@@ -1705,12 +1711,6 @@ class RandomizedSearchCV(BaseSearchCV):
     `pre_dispatch` many times. A reasonable value for `pre_dispatch` is `2 *
     n_jobs`.
 
-    See Also
-    --------
-    GridSearchCV : Does exhaustive search over a grid of parameters.
-    ParameterSampler : A generator over parameter settings, constructed from
-        param_distributions.
-
     Examples
     --------
     >>> from sklearn.datasets import load_iris
