code: def test_fit_Clf_feature_selector():
      """Test fit method of Clf_feature_selector class."""
      feature_selector = Clf_feature_selector()
      df_train = pd.read_csv("data_for_tests/clean_train.csv")
      y_train = pd.read_csv(
          "data_for_tests/clean_target.csv", squeeze=True
      )
      with pytest.raises(ValueError):
          feature_selector.fit(None, y_train)
      with pytest.raises(ValueError):
          feature_selector.fit(df_train, None)
      feature_selector.fit(df_train, y_train)
      assert feature_selector._Clf_feature_selector__fitOK
      feature_selector.set_params(strategy="variance")
      feature_selector.fit(df_train, y_train)
      assert feature_selector._Clf_feature_selector__fitOK
      feature_selector.set_params(strategy="rf_feature_importance")
      feature_selector.fit(df_train, y_train)
      assert feature_selector._Clf_feature_selector__fitOK
      feature_selector.set_params(strategy="wrond_strategy")
      with pytest.raises(ValueError):
          feature_selector.fit(df_train, y_train)
  
file_path: MLBox/tests/test_classification_feature_selector.py
imports: import pytest
  import pandas
  from mlbox.model.classification.feature_selector import Clf_feature_selector
label_desc: Use image node_id 4 for calling a global function with example usage: test_fit_Clf_feature_selector() without return types