title: Cross-validate precision, recall and f1 together with sklearn
body: <p>is there any simple way to cross-validate a classifier and calculate precision and recall at once? Currently I use the function </p>
  
  <pre><code>cross_validation.cross_val_score(classifier, designMatrix, classes, cv=5, scoring="precision")
  </code></pre>
  
  <p>however it calculates only one metric, so I have to call it 2 times to calculate precision and recall. With a large ML model, the calculation then unnecessarily takes 2 times longer. Is there any built-in better option, or do I have to implement the cross-validation on my own? thanks.</p>