DOC Ensures that Ridge passes numpydoc validation (scikit-learn#20499)

Author: alinealfa

maint_tools/test_docstrings.py

@@ -128,7 +128,6 @@
     "RandomTreesEmbedding",
     "RandomizedSearchCV",
     "RegressorChain",
-    "Ridge",
     "RidgeCV",
     "RidgeClassifier",
     "RidgeClassifierCV",

sklearn/linear_model/_ridge.py

@@ -988,18 +988,19 @@ def fit(self, X, y, sample_weight=None):
         Parameters
         ----------
         X : {ndarray, sparse matrix} of shape (n_samples, n_features)
-            Training data
+            Training data.
 
         y : ndarray of shape (n_samples,) or (n_samples, n_targets)
-            Target values
+            Target values.
 
         sample_weight : float or ndarray of shape (n_samples,), default=None
             Individual weights for each sample. If given a float, every sample
             will have the same weight.
 
         Returns
         -------
-        self : returns an instance of self.
+        self : object
+            Fitted estimator.
         """
         return super().fit(X, y, sample_weight=sample_weight)