title: Scoring in Gridsearch CV
body: <p>I just started with GridSearchCV in Python, but I am confused what is scoring in this. Somewhere I have seen </p>
  
  <pre><code>scorers = {
      'precision_score': make_scorer(precision_score),
      'recall_score': make_scorer(recall_score),
      'accuracy_score': make_scorer(accuracy_score)
  }
  
  grid_search = GridSearchCV(clf, param_grid, scoring=scorers, refit=refit_score,
                         cv=skf, return_train_score=True, n_jobs=-1)
  </code></pre>
  
  <p>What is the intent of using these values, i.e. precision, recall, accuracy in scoring? </p>
  
  <p>Is this used by gridsearch in giving us the optimized parameters based on these scoring values.... like for the best precision score it finds the best parameters or something like that? </p>
  
  <p>It calculate precision, recall, accuracy for the possible parameters and gives the result, now the question is if this is true, then it select best parameters based on precision, recall or accuracy? Is the above statement true?</p>