code: def test_prediction_intervals_lets_the_user_specify_number_of_intervals():
      np.random.seed(0)
  
      (
          df_boston_train,
          df_boston_test,
      ) = utils.get_boston_regression_dataset()
  
      column_descriptions = {"MEDV": "output", "CHAS": "categorical"}
  
      ml_predictor = Predictor(
          type_of_estimator="regressor",
          column_descriptions=column_descriptions,
      )
  
      ml_predictor.train(
          df_boston_train,
          predict_intervals=True,
          prediction_intervals=[0.2],
      )
  
      intervals = ml_predictor.predict_intervals(
          df_boston_test, return_type="list"
      )
  
      assert len(intervals[0]) == 2
  
file_path: auto_ml/tests/core_tests/test_prediction_intervals.py
imports: import os
  import sys
  from auto_ml import Predictor
  import dill
  from nose.tools import assert_equal, assert_not_equal, with_setup
  import numpy
  import pandas
  from sklearn.model_selection import train_test_split
  import utils_testing
label_desc: Use image node_id 3 for calling a global function with example usage: test_prediction_intervals_lets_the_user_specify_number_of_intervals() without return types