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/core_tests/quick_test.py
imports: import datetime
  import os
  import random
  import sys
  from auto_ml import Predictor
  from auto_ml.utils_models import load_ml_model
  from nose.tools import assert_equal, assert_not_equal, with_setup
  from sklearn.metrics import accuracy_score
  import dill
  import numpy
  import pandas
  from sklearn.datasets import load_boston
  from sklearn.model_selection import train_test_split
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