code: def test_mse_tree():
      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)
      avg_expected_loss, avg_bias, avg_var = bias_variance_decomp(
          tree,
          X_train,
          y_train,
          X_test,
          y_test,
          loss="mse",
          random_seed=123,
      )
  
      assert round(avg_expected_loss, 3) == 31.536
      assert round(avg_bias, 3) == 14.096
      assert round(avg_var, 3) == 17.440
  
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 4 for calling a global function with example usage: test_mse_tree() without return types