DOC added examples to ridge classes (#11730)

adrinjalali · jnothman · commit 71ee6d2f12bc · 2018-08-02T17:46:53.000+10:00
diff --git a/sklearn/linear_model/ridge.py b/sklearn/linear_model/ridge.py
@@ -779,6 +779,15 @@ class RidgeClassifier(LinearClassifierMixin, _BaseRidge):
         Actual number of iterations for each target. Available only for
         sag and lsqr solvers. Other solvers will return None.
 
+    Examples
+    --------
+    >>> from sklearn.datasets import load_breast_cancer
+    >>> from sklearn.linear_model import RidgeClassifier
+    >>> X, y = load_breast_cancer(return_X_y=True)
+    >>> clf = RidgeClassifier().fit(X, y)
+    >>> clf.score(X, y) # doctest: +ELLIPSIS
+    0.9595...
+
     See also
     --------
     Ridge : Ridge regression
@@ -1249,6 +1258,15 @@ class RidgeCV(_BaseRidgeCV, RegressorMixin):
     alpha_ : float
         Estimated regularization parameter.
 
+    Examples
+    --------
+    >>> from sklearn.datasets import load_diabetes
+    >>> from sklearn.linear_model import RidgeCV
+    >>> X, y = load_diabetes(return_X_y=True)
+    >>> clf = RidgeCV(alphas=[1e-3, 1e-2, 1e-1, 1]).fit(X, y)
+    >>> clf.score(X, y) # doctest: +ELLIPSIS
+    0.5166...
+
     See also
     --------
     Ridge : Ridge regression
@@ -1339,6 +1357,15 @@ class RidgeClassifierCV(LinearClassifierMixin, _BaseRidgeCV):
     alpha_ : float
         Estimated regularization parameter
 
+    Examples
+    --------
+    >>> from sklearn.datasets import load_breast_cancer
+    >>> from sklearn.linear_model import RidgeClassifierCV
+    >>> X, y = load_breast_cancer(return_X_y=True)
+    >>> clf = RidgeClassifierCV(alphas=[1e-3, 1e-2, 1e-1, 1]).fit(X, y)
+    >>> clf.score(X, y) # doctest: +ELLIPSIS
+    0.9630...
+
     See also
     --------
     Ridge : Ridge regression
