ENH Document how to get valid parameters in set_params

Issue scikit-learn#4690

Author: joshloyal

sklearn/base.py

@@ -254,15 +254,19 @@ def set_params(self, **params):
                 # nested objects case
                 name, sub_name = split
                 if name not in valid_params:
-                    raise ValueError('Invalid parameter %s for estimator %s' %
+                    raise ValueError('Invalid parameter %s for estimator %s. ' 
+                                     'Check the list of available parameters '
+                                     'with `estimator.get_params().keys()`.' %
                                      (name, self))
                 sub_object = valid_params[name]
                 sub_object.set_params(**{sub_name: value})
             else:
                 # simple objects case
                 if key not in valid_params:
-                    raise ValueError('Invalid parameter %s ' 'for estimator %s'
-                                     % (key, self.__class__.__name__))
+                    raise ValueError('Invalid parameter %s for estimator %s. '
+                                     'Check the list of available parameters '
+                                     'with `estimator.get_params().keys()`.' %
+                                     (key, self.__class__.__name__))
                 setattr(self, key, value)
         return self
 

sklearn/tests/test_pipeline.py

@@ -5,7 +5,7 @@
 from scipy import sparse
 
 from sklearn.externals.six.moves import zip
-from sklearn.utils.testing import assert_raises, assert_raises_regex
+from sklearn.utils.testing import assert_raises, assert_raises_regex, assert_raise_message
 from sklearn.utils.testing import assert_equal
 from sklearn.utils.testing import assert_false
 from sklearn.utils.testing import assert_true
@@ -165,6 +165,27 @@ def test_pipeline_fit_params():
     assert_true(pipe.named_steps['transf'].b is None)
 
 
+def test_pipeline_raise_set_params_error():
+    # Test pipeline raises set params error message for nested models.
+    pipe  = Pipeline([('cls', LinearRegression())])
+ 
+    # expected error message
+    error_msg = ('Invalid parameter %s for estimator %s. ' 
+                 'Check the list of available parameters ' 
+                 'with `estimator.get_params().keys()`.' )
+
+    assert_raise_message(ValueError, 
+                         error_msg % ('fake', 'Pipeline'),
+                         pipe.set_params,
+                         fake='nope')
+    
+    # nested model check
+    assert_raise_message(ValueError,
+                         error_msg % ("fake", pipe),
+                         pipe.set_params,
+                         fake__estimator='nope') 
+
+
 def test_pipeline_methods_pca_svm():
     # Test the various methods of the pipeline (pca + svm).
     iris = load_iris()