title: sklearn.model_selection GridSearchCV is throwing KeyError: 'mean_train_score'
body: <p>I am trying to fetch mean train score from <code>classifierobject.cv_result_</code> from <code>GridSearchCV</code> method using 5 fold cross-validation but it's giving me <code>*** KeyError: 'mean_train_score'</code> in Google Colab. However, the same code is running fine in local machine Ipython notebook for <code>sklearn</code> version 0.19.1. 
  Can anyone help me how can I get the output in google colab?</p>
  
  <p><code>clf.cv_results_.keys()</code> ouputs following - </p>
  
  <p>for my local notebook -</p>
  
  <pre><code>dict_keys(['mean_fit_time', 'std_fit_time', 'mean_score_time', 'std_score_time', 'param_n_neighbors', 'params', 'split0_test_score', 'split1_test_score', 'split2_test_score', 'split3_test_score', 'split4_test_score', 'mean_test_score', 'std_test_score', 'rank_test_score', 'split0_train_score', 'split1_train_score', 'split2_train_score', 'split3_train_score', 'split4_train_score', 'mean_train_score', 'std_train_score'])
  </code></pre>
  
  <p>on google colab notebook - </p>
  
  <pre><code>dict_keys(['mean_fit_time', 'std_fit_time', 'mean_score_time', 'std_score_time', 'param_n_neighbors', 'params', 'split0_test_score', 'split1_test_score', 'split2_test_score', 'split3_test_score', 'split4_test_score', 'mean_test_score', 'std_test_score', 'rank_test_score'])
  </code></pre>
  
  <p>where is the <code>mean_train_score</code> in google colab. Am I missing something?</p>
  
  <pre><code>from sklearn.model_selection import GridSearchCV
  
  neigh = KNeighborsClassifier(n_jobs=-1)
  parameters = {'n_neighbors':[1, 5, 10, 15, 19 , 21, 31, 41, 51]}
  clf = GridSearchCV(neigh, parameters, cv=5,\ 
                     scoring='roc_auc',n_jobs=-1) 
  clf.fit(x_train, y_train)
  train_auc= clf.cv_results_['mean_train_score']
  train_auc_std= clf.cv_results_['std_train_score']
  cv_auc = clf.cv_results_['mean_test_score'] 
  cv_auc_std= clf.cv_results_['std_test_score']
  
  </code></pre>