code: def test_feature_importances_regressor():
      """Test feature_importances of Regressor class."""
      regressor = Regressor()
      with pytest.raises(ValueError):
          regressor.feature_importances()
      df_train = pd.read_csv("data_for_tests/clean_train.csv")
      y_train = pd.read_csv(
          "data_for_tests/clean_target.csv", squeeze=True
      )
      regressor.set_params(strategy="LightGBM")
      regressor.fit(df_train, y_train)
      importance = regressor.feature_importances()
      assert importance != {}
      regressor.set_params(strategy="Linear")
      regressor.fit(df_train, y_train)
      importance = regressor.feature_importances()
      assert importance != {}
      regressor.set_params(strategy="RandomForest")
      regressor.fit(df_train, y_train)
      importance = regressor.feature_importances()
      assert importance != {}
      regressor.set_params(strategy="AdaBoost")
      regressor.fit(df_train, y_train)
      importance = regressor.feature_importances()
      assert importance != {}
      regressor.set_params(strategy="Bagging")
      regressor.fit(df_train, y_train)
      importance = regressor.feature_importances()
      assert importance != {}
  
file_path: MLBox/tests/test_regressor.py
imports: import pytest
  import pandas
  import numpy
  from mlbox.model.regression.regressor import Regressor
  from lightgbm import LGBMRegressor
label_desc: Use image node_id 6 for calling a global function with example usage: test_feature_importances_regressor() without return types