code: def do_full_save(experiment_result):
      """This is a simple check to see if the final OOF ROC-AUC score is above 0.75. If it is, we return True; otherwise, we return
      False. As input, your do_full_save functions should expect an Experiment's result dictionary. This is actually the dictionary
      that gets saved as the Experiment's "description" file, so for more information on what's in there, look at any description
      file or see :attr:`hyperparameter_hunter.recorders.DescriptionRecorder.result` (the object passed to `do_full_save`)
      """
      return (
          experiment_result["final_evaluations"]["oof"]["roc_auc_score"]
          > 0.75
      )
  
imports: from hyperparameter_hunter import Environment, CVExperiment
  from hyperparameter_hunter.utils.learning_utils import get_toy_classification_data
  from sklearn.model_selection import RepeatedStratifiedKFold
  from xgboost import XGBClassifier
label_desc: Use image node_id 1 for calling a global function with example usage: do_full_save(experiment_result) and returns: unknown