title: AttributeError: 'GridSearchCV' object has no attribute 'best_estimator_'
body: <p>I am using grid search to tune parameters of my models (Random Forest, Linear Regression, etc.). So I save <code>gs</code> objects in <code>grid_searches</code>:</p>
  
  <pre><code>gs = GridSearchCV(model, params, cv=cv, n_jobs=n_jobs,
                    verbose=verbose, scoring="mean_squared_error", refit=refit)
  gs.fit(trainX,trainy)
  grid_searches[key] = gs
  </code></pre>
  
  <p>Then I want to access the best estimator for each model in order to make predictions:</p>
  
  <pre><code>def predict(testX, testy, grid_searches):
      keys = models.keys()
      for k in keys:
          print("Predicting with %s." % k)
          yhat = grid_searches[k].best_estimator_.predict(testX)
  </code></pre>
  
  <p>The error is the following:</p>
  
  <pre><code>AttributeError: 'GridSearchCV' object has no attribute 'best_estimator_'
  </code></pre>
  
  <p>So how should I make predictions using best models found by Grid Search?</p>