docs: def roc_auc(y_true, y_score):
      """
      Returns are under the ROC curve
      """
      notnull = ~np.isnan(y_true)
      fpr, tpr, thresholds = sklearn.metrics.roc_curve(y_true[notnull], y_score[notnull])
      return sklearn.metrics.auc(fpr, tpr)