code: def test_importances_binary_classification(self, metric):
      (
          X_train,
          y_train,
          X_test,
          y_test,
          _,
      ) = create_binary_classification_dataset()
      feature_names = list(X_train.columns)
      models = create_models_classification(X_train, y_train)
  
      for model in models:
          categorical_features = []
          run_error_analyzer(
              model,
              X_test,
              y_test,
              feature_names,
              categorical_features,
              metric=metric,
          )
  
file_path: responsible-ai-toolbox/erroranalysis/tests/test_root_stats.py
imports: import pytest
  from erroranalysis._internal.constants import Metrics, RootKeys, metric_to_display_name
  from erroranalysis._internal.error_analyzer import ModelAnalyzer
  from erroranalysis._internal.metrics import metric_to_func
  from rai_test_utils.datasets.tabular import create_binary_classification_dataset, create_cancer_data, create_housing_data, create_iris_data, create_simple_titanic_data
  from rai_test_utils.models.model_utils import create_models_classification, create_models_regression
  from rai_test_utils.models.sklearn import create_titanic_pipeline
label_desc: Use image node_id 3 for calling the TestRootStats obj's underlying member method code with example usage: obj.test_importances_binary_classification(metric) without return types