code: def test_error_if_select_model_performance_and_y_is_none(df_single):
      X, y = df_single
  
      transformer = SmartCorrelatedSelection(
          selection_method="model_performance",
          estimator=RandomForestClassifier(
              n_estimators=10, random_state=1
          ),
          scoring="roc_auc",
      )
  
      with pytest.raises(ValueError):
          transformer.fit(X)
  
file_path: feature_engine/tests/test_selection/test_smart_correlation_selection.py
imports: import pandas
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.ensemble import RandomForestClassifier
  from feature_engine.selection import SmartCorrelatedSelection
label_desc: Use image node_id 4 for calling a global function with example usage: test_error_if_select_model_performance_and_y_is_none(df_single) without return types