code: def test_mse_bagging():
      X, y = boston_housing_data()
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, test_size=0.3, random_state=123, shuffle=True
      )
  
      tree = DecisionTreeRegressor(random_state=123)
      bag = BaggingRegressor(
          base_estimator=tree, n_estimators=10, random_state=123
      )
  
      avg_expected_loss, avg_bias, avg_var = bias_variance_decomp(
          bag,
          X_train,
          y_train,
          X_test,
          y_test,
          loss="mse",
          random_seed=123,
      )
  
      assert round(avg_expected_loss, 2) == 20.24, avg_expected_loss
      assert round(avg_bias, 2) == 15.63, avg_bias
      assert round(avg_var, 2) == 4.61, avg_var
  
file_path: mlxtend/mlxtend/evaluate/tests/test_bias_variance_decomp.py
imports: import os
  import pandas
  import pytest
  from sklearn.ensemble import BaggingClassifier, BaggingRegressor
  from sklearn.model_selection import train_test_split
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from mlxtend.data import boston_housing_data, iris_data
  from mlxtend.evaluate import bias_variance_decomp
label_desc: Use image node_id 5 for calling a global function with example usage: test_mse_bagging() without return types