original_docstring: 
          AUROC scoring method for estimators (classifiers) so we can use AUROC
          for model evaluation during hyperparam optimization using GridSearch.
          
docstring: AUROC scoring method for estimators (classifiers) so we can use AUROC
  for model evaluation during hyperparam optimization using GridSearch.
docstring_tokens: AUROC scoring method for estimators ( classifiers ) so we can use AUROC for model evaluation during hyperparam optimization using GridSearch .
code: def score_auroc(self, estimator, X, y):
          """
          AUROC scoring method for estimators (classifiers) so we can use AUROC
          for model evaluation during hyperparam optimization using GridSearch.
          """
          y_pred = estimator.predict_proba(X)
          return roc_auc_score(y, y_pred[:, 1])
code_tokens: def score_auroc ( self , estimator , X , y ) : y_pred = estimator . predict_proba ( X ) return roc_auc_score ( y , y_pred [ : , 1 ] )
short_docstring: AUROC scoring method for estimators (classifiers) so we can use AUROC
  for model evaluation during hyperparam optimization using GridSearch.
short_docstring_tokens: AUROC scoring method for estimators ( classifiers ) so we can use AUROC for model evaluation during hyperparam optimization using GridSearch .
comment: """
          AUROC scoring method for estimators (classifiers) so we can use AUROC
          for model evaluation during hyperparam optimization using GridSearch.
          """