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=0,
      )
      cls.X = pd.DataFrame(
          cls.X, columns=[f"f_{i}" for i in range(cls.X.shape[1])]
      )
      cls.params = {
          "learning_rate": 0.1,
          "depth": 4,
          "rsm": 0.5,
          "l2_leaf_reg": 1,
          "seed": 1,
          "ml_task": "binary_classification",
          "loss_function": "Logloss",
          "eval_metric": "Logloss",
      }
  
imports: import unittest
  import tempfile
  import json
  import copy
  import numpy
  import pandas
  import os
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from supervised.algorithms.catboost import CatBoostAlgorithm, additional
  from supervised.utils.metric import Metric
  import tempfile
label_desc: Use image node_id 1 for calling the CatBoostAlgorithmTest obj's underlying member method code with example usage: obj.setUpClass(cls) without return types