docstr: Evaluate holdout predictions for the run
docstr_tok: ["Evaluate","holdout","predictions","for","the","run"]
code: def on_run_end(self):
      """Evaluate holdout predictions for the run"""
      if G.Env.save_transformed_metrics:
          self.evaluate(
              "holdout",
              self.data_holdout.target.T.run,
              self.data_holdout.prediction.T.run,
          )
      else:  # See module "Notes"
          self.evaluate(
              "holdout",
              self.data_holdout.target.fold,
              self.data_holdout.prediction.run,
          )
      super().on_run_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 1 for calling the EvaluatorHoldout obj's underlying member method code with example usage: obj.on_run_end() without return types