code: def save_result(self):
      self.result = read_json(
          f"{self.result_paths['description']}/{self.experiment_id}.json"
      )
  
      make_dirs(self.result_path, exist_ok=True)
      with open(
          f"{self.result_path}/{self.experiment_id}.yml", "w+"
      ) as f:
          yaml.dump(self.result, f, default_flow_style=False, width=200)
  
file_path: hyperparameter_hunter/examples/advanced_examples/recorder_example.py
imports: from hyperparameter_hunter import Environment, BayesianOptPro, Real, Integer, Categorical
  from hyperparameter_hunter.i_o.recorders import UnsortedIDLeaderboardRecorder, BaseRecorder
  from hyperparameter_hunter.utils.file_utils import make_dirs, read_json
  import pandas
  from sklearn.datasets import load_breast_cancer
  from sklearn.model_selection import StratifiedKFold
  from xgboost import XGBClassifier
  import yaml
label_desc: Use image node_id 2 for calling the YAMLDescriptionRecorder obj's underlying member method code with example usage: obj.save_result() without return types