code: def get_boston_regression_dataset():
      boston = load_boston()
      df_boston = pd.DataFrame(boston.data)
      df_boston.columns = boston.feature_names
      df_boston["MEDV"] = boston["target"]
      df_boston_train, df_boston_test = train_test_split(
          df_boston, test_size=0.33, random_state=42
      )
      return df_boston_train, df_boston_test
  
file_path: auto_ml/tests/advanced_tests/utils_testing.py
imports: import sys, os
  import pandas
  from sklearn.datasets import load_boston
  from sklearn.metrics import brier_score_loss, mean_squared_error
  from sklearn.model_selection import train_test_split
  from auto_ml import Predictor
label_desc: Use image node_id 1 for calling a global function with example usage: get_boston_regression_dataset() and returns: df_boston_train,  df_boston_test