code: def test_lending_club_false_negative_rate_scorer_binary(
      lending_club_split_dataset_and_model,
  ):
      # Arrange
      _, test_ds, clf = lending_club_split_dataset_and_model
      binary = make_scorer(
          false_negative_rate_metric, averaging_method="binary"
      )
      scorer = deepchecks_scorer(binary, clf, test_ds)
  
      # Act
      score = scorer(clf, test_ds)
  
      # Assert
      assert_that(score, close_to(0.4906, 0.01))
  
imports: import pandas
  from hamcrest import assert_that, calling, close_to, has_entries, is_, raises
  from sklearn.metrics import log_loss, make_scorer, mean_squared_error
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.metric_utils import DeepcheckScorer
  from deepchecks.tabular.metric_utils.additional_classification_metrics import false_negative_rate_metric, false_positive_rate_metric, true_negative_rate_metric
  from deepchecks.tabular.utils.task_inference import get_all_labels, infer_classes_from_model
  from deepchecks.utils.single_sample_metrics import calculate_neg_cross_entropy_per_sample, calculate_neg_mse_per_sample
  from tests.common import is_nan
label_desc: Use image node_id 4 for calling a global function with example usage: test_lending_club_false_negative_rate_scorer_binary(lending_club_split_dataset_and_model) without return types