code: def execute():
      env = Environment(
          train_dataset=get_breast_cancer_data(),
          results_path="HyperparameterHunterAssets",
          target_column="diagnosis",
          metrics=["roc_auc_score"],
          cv_type="StratifiedKFold",
          cv_params=dict(n_splits=5, shuffle=True, random_state=32),
      )
  
      experiment = CVExperiment(
          model_initializer=KerasClassifier,
          model_init_params=build_fn,
          model_extra_params=dict(
              callbacks=[
                  ModelCheckpoint(
                      filepath=os.path.abspath("foo_checkpoint"),
                      save_best_only=True,
                      verbose=1,
                  ),
                  ReduceLROnPlateau(patience=5),
              ],
              batch_size=32,
              epochs=10,
              verbose=0,
              shuffle=True,
          ),
      )
  
file_path: hyperparameter_hunter/examples/keras_examples/experiment_example.py
imports: from hyperparameter_hunter import Environment, CVExperiment
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data
  import os.path
  from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau
  from keras.layers import Dense, Activation, 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: execute() without return types