docs: def f1(y_true, y_pred, round=True):
      """F1 score: `2 * (p * r) / (p + r)`, where p=precision and r=recall.
      """
      y_true, y_pred = _mask_value_nan(y_true, y_pred)
      if round:
          y_true = np.round(y_true)
          y_pred = np.round(y_pred)
      return skm.f1_score(y_true, y_pred)