COSMIT

raghavrv · raghavrv · commit 812717270dfc · 2016-09-06T18:44:09.000+02:00
diff --git a/doc/tutorial/text_analytics/solutions/exercise_02_sentiment.py b/doc/tutorial/text_analytics/solutions/exercise_02_sentiment.py
@@ -55,12 +55,12 @@
 
     # TASK: print the mean and std for each candidate along with the parameter
     # settings for all the candidates explored by grid search.
-    n_candidates = len(grid_search.results_['params'])
+    n_candidates = len(grid_search.cv_results_['params'])
     for i in range(n_candidates):
         print(i, 'params - %s; mean - %0.2f; std - %0.2f'
-                 % (grid_search.results_['params'][i],
-                    grid_search.results_['test_mean_score'][i],
-                    grid_search.results_['test_std_score'][i]))
+                 % (grid_search.cv_results_['params'][i],
+                    grid_search.cv_results_['mean_test_score'][i],
+                    grid_search.cv_results_['std_test_score'][i]))
 
     # TASK: Predict the outcome on the testing set and store it in a variable
     # named y_predicted
diff --git a/doc/tutorial/text_analytics/working_with_text_data.rst b/doc/tutorial/text_analytics/working_with_text_data.rst
@@ -458,9 +458,9 @@ mean score and the parameters setting corresponding to that score::
   tfidf__use_idf: True
   vect__ngram_range: (1, 1)
 
-A more detailed summary of the search is available at ``gs_clf.results_``.
+A more detailed summary of the search is available at ``gs_clf.cv_results_``.
 
-The ``results_`` parameter can be easily imported into pandas as a
+The ``cv_results_`` parameter can be easily imported into pandas as a
 ``DataFrame`` for further inspection.
 
 .. note:
