code: def test_feature_importances_classifier():
      """Test feature_importances method of Classifier class."""
      classifier = Classifier()
      with pytest.raises(ValueError):
          classifier.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
      )
      classifier.set_params(strategy="LightGBM")
      classifier.fit(df_train, y_train)
      importance = classifier.feature_importances()
      assert importance != {}
      classifier.set_params(strategy="Linear")
      classifier.fit(df_train, y_train)
      importance = classifier.feature_importances()
      assert importance != {}
      classifier.set_params(strategy="RandomForest")
      classifier.fit(df_train, y_train)
      importance = classifier.feature_importances()
      assert importance != {}
      classifier.set_params(strategy="AdaBoost")
      classifier.fit(df_train, y_train)
      importance = classifier.feature_importances()
      assert importance != {}
      classifier.set_params(strategy="Bagging")
      classifier.fit(df_train, y_train)
      importance = classifier.feature_importances()
      assert importance != {}
  
file_path: MLBox/tests/test_classifier.py
imports: import pytest
  import pandas
  import numpy
  from mlbox.model.classification.classifier import Classifier
  from lightgbm import LGBMClassifier
label_desc: Use image node_id 6 for calling a global function with example usage: test_feature_importances_classifier() without return types