code: def env_breast_cancer():
      env = Environment(
          train_dataset=get_breast_cancer_data(target="target"),
          results_path=assets_dir,
          metrics=["roc_auc_score"],
          cv_type="StratifiedKFold",
          cv_params=dict(n_splits=5, shuffle=True, random_state=32),
      )
      return env
  
file_path: hyperparameter_hunter/tests/integration_tests/test_optimization_space.py
imports: from hyperparameter_hunter import __version__, Environment, Real, Integer, Categorical
  from hyperparameter_hunter import BayesianOptPro, GBRT, RF, ET, DummyOptPro
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data
  from hyperparameter_hunter.utils.version_utils import HHVersion
  from os import makedirs
  import pytest
  from shutil import rmtree
  from keras.layers import Dense, Dropout
  from keras.models import Sequential
  from keras.wrappers.scikit_learn import KerasClassifier
label_desc: Use image node_id 2 for calling a global function with example usage: env_breast_cancer() and returns: env