title: How to choose the nrounds using `catboost`?
body: <p>If I understand correctly <code>catboost</code>, we need to tune the <code>nrounds</code> just like in <code>xgboost</code>, using CV. I see the following code in the <a href="https://github.com/catboost/catboost/blob/master/catboost/tutorials/catboost_r_tutorial.ipynb" rel="nofollow noreferrer">official tutorial</a> <strong>In [8]</strong></p>
  
  <pre><code>params_with_od &lt;- list(iterations = 500,
                         loss_function = 'Logloss',
                         train_dir = 'train_dir',
                         od_type = 'Iter',
                         od_wait = 30)
  model_with_od &lt;- catboost.train(train_pool, test_pool, params_with_od)
  </code></pre>
  
  <p>Which result in the best <code>iterations</code> = 211. </p>
  
  <p>My question are:</p>
  
  <ul>
  <li>Is it correct that: this command use the <code>test_pool</code> to choose the best <code>iterations</code> instead of using cross-validation?</li>
  <li>If yes, does catboost provide a command to choose the best <code>iterations</code> from CV, or I need to do it manually?</li>
  </ul>