code: def setUpClass(cls):
      cls.X, cls.y = datasets.make_classification(
          n_samples=100,
          n_features=5,
          n_informative=4,
          n_redundant=1,
          n_classes=2,
          n_clusters_per_class=3,
          n_repeated=0,
          shuffle=False,
          random_state=1,
      )
  
      cls.params = {
          "dense_1_size": 8,
          "dense_2_size": 4,
          "learning_rate": 0.01,
          "ml_task": "binary_classification",
      }
  
imports: import unittest
  import tempfile
  import json
  import numpy
  import pandas
  import os
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from sklearn import preprocessing
  from supervised.algorithms.nn import MLPAlgorithm, MLPRegressorAlgorithm
  from supervised.utils.metric import Metric
label_desc: Use image node_id 1 for calling the MLPAlgorithmTest obj's underlying member method code with example usage: obj.setUpClass(cls) without return types