scikit-learn
diff --git a/‎sklearn/utils/estimator_checks.py
Lines changed: 14 additions & 0 deletions b/‎sklearn/utils/estimator_checks.py
Lines changed: 14 additions & 0 deletions
diff --git a/‎sklearn/utils/tests/test_estimator_checks.py
Lines changed: 23 additions & 0 deletions b/‎sklearn/utils/tests/test_estimator_checks.py
Lines changed: 23 additions & 0 deletions
@@ -251,6 +251,7 @@ def check_estimator(Estimator):
     """
     name = Estimator.__name__
     check_parameters_default_constructible(name, Estimator)
+    check_set_params(name, Estimator)
     for check in _yield_all_checks(name, Estimator):
         check(name, Estimator)
 
@@ -1630,6 +1631,19 @@ def transform(self, X):
                     shallow_params.items()))
 
 
+def check_set_params(name, Estimator):
+    # Trivial check to make sure set_params is working
+    classifier = LinearDiscriminantAnalysis()
+    with ignore_warnings(category=DeprecationWarning):
+        if name in META_ESTIMATORS:
+            estimator = Estimator(classifier)
+        else:
+            estimator = Estimator()
+
+    params = estimator.get_params()
+    estimator.set_params(**params)
+  
+
 def check_classifiers_regression_target(name, Estimator):
     # Check if classifier throws an exception when fed regression targets
 
 
@@ -42,6 +42,26 @@ def predict(self, X):
         return np.ones(X.shape[0])
 
 
+class NoSetter(BaseBadClassifier):
+    def __init__(self, p=0):
+        self._p = p
+
+    @property
+    def p(self):
+        return self._p
+
+    def fit(self, X, y):
+        X, y = check_X_y(X, y)
+        self.coef_ = np.ones(X.shape[1])
+        return self
+
+    def predict(self, X):
+        if not hasattr(self, 'coef_'):
+            raise CorrectNotFittedError("estimator is not fitted yet")
+        X = check_array(X)
+        return np.ones(X.shape[0])
+
+
 class NoCheckinPredict(BaseBadClassifier):
     def fit(self, X, y):
         X, y = check_X_y(X, y)
@@ -80,6 +100,9 @@ def test_check_estimator():
     # check that we have a set_params and can clone
     msg = "it does not implement a 'get_params' methods"
     assert_raises_regex(TypeError, msg, check_estimator, object)
+    # check that properties can be set
+    msg = "can't set attribute"
+    assert_raises_regex(AttributeError, msg, check_estimator, NoSetter)
     # check that we have a fit method
     msg = "object has no attribute 'fit'"
     assert_raises_regex(AttributeError, msg, check_estimator, BaseEstimator)