code: def custom_public_data_interface():
      dataset = helpers.load_custom_testing_dataset_regression()
      d = dice_ml.Data(
          dataframe=dataset,
          continuous_features=["Numerical"],
          outcome_name="Outcome",
      )
      return d
  
imports: from collections import OrderedDict
  from itertools import product
  import pandas
  import pytest
  import torch
  from rai_test_utils.models.sklearn import create_complex_classification_pipeline, create_complex_regression_pipeline
  import dice_ml
  from dice_ml.utils import helpers
  from dice_ml.utils.neuralnetworks import FFNetwork
label_desc: Use image node_id 18 for calling a global function with example usage: custom_public_data_interface() and returns: d