title: how to work with the catboost overfitting detector
body: <p>I am trying to understand the catboost overfitting detector. It is described here: </p>
  
  <p><a href="https://tech.yandex.com/catboost/doc/dg/concepts/overfitting-detector-docpage/#overfitting-detector" rel="noreferrer">https://tech.yandex.com/catboost/doc/dg/concepts/overfitting-detector-docpage/#overfitting-detector</a></p>
  
  <p>Other gradient boosting packages like lightgbm and xgboost use a parameter called early_stopping_rounds, which is easy to understand (it stops the training once the validation error hasn't decreased in early_stopping_round steps).</p>
  
  <p>However I have a hard time understanding the p_value approach used by catboost. Can anyone explain how this overfitting detector works and when it stops the training? </p>