docstr: Evaluate final (run/repetition-averaged) holdout predictions
docstr_tok: ["Evaluate","final","(","run\/repetition-averaged",")","holdout","predictions"]
code: def on_exp_end(self):
      """Evaluate final (run/repetition-averaged) holdout predictions"""
      if G.Env.save_transformed_metrics:
          self.evaluate(
              "holdout",
              self.data_holdout.target.T.final,
              self.data_holdout.prediction.T.final,
          )
      else:  # See module "Notes"
          self.evaluate(
              "holdout",
              self.data_holdout.target.d,
              self.data_holdout.prediction.final,
          )
      super().on_exp_end()
  
file_path: hyperparameter_hunter/hyperparameter_hunter/callbacks/evaluators.py
imports: from hyperparameter_hunter.callbacks.bases import BaseEvaluatorCallback
  from hyperparameter_hunter.data.data_core import BaseDataset
  from hyperparameter_hunter.settings import G
label_desc: Use image node_id 4 for calling the EvaluatorHoldout obj's underlying member method code with example usage: obj.on_exp_end() without return types