[MRG + 1] Removes estimator method check in cross_val_predict before …

…fitting (#9641)

* Removes check in cross_val_predict that checks estimator method before fitting

* Adds regression test for issue #9639

sklearn/model_selection/_validation.py

@@ -637,11 +637,6 @@ def cross_val_predict(estimator, X, y=None, groups=None, cv=None, n_jobs=1,
 
     cv = check_cv(cv, y, classifier=is_classifier(estimator))
 
-    # Ensure the estimator has implemented the passed decision function
-    if not callable(getattr(estimator, method)):
-        raise AttributeError('{} not implemented in estimator'
-                             .format(method))
-
     if method in ['decision_function', 'predict_proba', 'predict_log_proba']:
         le = LabelEncoder()
         y = le.fit_transform(y)

sklearn/model_selection/tests/test_validation.py

@@ -51,7 +51,7 @@
 from sklearn.metrics import r2_score
 from sklearn.metrics.scorer import check_scoring
 
-from sklearn.linear_model import Ridge, LogisticRegression
+from sklearn.linear_model import Ridge, LogisticRegression, SGDClassifier
 from sklearn.linear_model import PassiveAggressiveClassifier
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.svm import SVC
@@ -1194,6 +1194,13 @@ def test_cross_val_predict_with_method():
     check_cross_val_predict_with_method(LogisticRegression())
 
 
+def test_cross_val_predict_method_checking():
+    # Regression test for issue #9639. Tests that cross_val_predict does not
+    # check estimator methods (e.g. predict_proba) before fitting
+    est = SGDClassifier(loss='log', random_state=2)
+    check_cross_val_predict_with_method(est)
+
+
 def test_gridsearchcv_cross_val_predict_with_method():
     est = GridSearchCV(LogisticRegression(random_state=42),
                        {'C': [0.1, 1]},