title: The R^2 score I get from GridSearchCV is very different from the one I get from cross_val_score, why? (sklearn, python)
body: <p>I'm using GridSearchCV to pick a regressor. Once it's fitted, I pull out the chosen regressor with</p>
  
  <pre><code>predictor = GridSearchCV(Pipeline(...), params={...},
                           cv=10, scoring='r2')
  predictor.fit(X, y)
  estimator = predictor.get_params()['estimator']
  </code></pre>
  
  <p>and then I run <code>cross_val_score</code> with</p>
  
  <pre><code>cross_val_score(estimator, X, y,
                  cv=10, scoring='r2')
  </code></pre>
  
  <p>but the R^2 I get is consistently about 5 percentage points lower than <code>predictor.best_score_</code>. Why? </p>