title: Setting Cross Validation parameter in Grid Search
body: <p>I am trying to set a RandomForestClassification inside a GridSearch</p>
  
  <pre><code>rfc_model = RandomForestClassifier(n_estimators = 5, max_depth = 3 )
  
  gs = grid_search.GridSearchCV(estimator = rfc_model,
                               param_grid = {'n_estimators': [i for i in range(1,52,10)],
                                            "max_depth": [3, 5],
                                            "bootstrap": [True, False],
                                            "criterion": ["gini"]},
                               cv = cross_val_score(rfc_model,X, y, scoring='roc_auc'))
  
  gs.fit(X, y)
  gs.grid_scores_
  print gs.best_estimator
  print gs.best_score_
  </code></pre>
  
  <p>I get the error</p>
  
  <p><code>TypeError: 'numpy.float64' object is not iterable</code></p>
  
  <p>Obviously I am learning, so any comments are welcome.</p>