docstr: ...
  
  Parameters
  ----------
  prediction: Array-like
  feature_engineer: FeatureEngineer
  target_column: List[str]
  *args: Tuple
  **kwargs: Dict
docstr_tok: ["...","Parameters","--","--","--","--","--","prediction",":","Array-like","feature_engineer",":","FeatureEngineer","target_column",":","List","[","str","]","*","args",":","Tuple","*","*","kwargs",":","Dict"]
code: def on_run_end(
      self, prediction, feature_engineer, target_column, *args, **kwargs
  ):
      """...
  
      Parameters
      ----------
      prediction: Array-like
      feature_engineer: FeatureEngineer
      target_column: List[str]
      *args: Tuple
      **kwargs: Dict"""
      self.T.run = deepcopy(prediction)
      self.run = deepcopy(prediction)
  
      self.run = _format_prediction(self.run, target_column)
      # `self.run` must be same shape as data transformed by `feature_engineer` prior to inversion
      # TODO: Make sure this doesn't screw up when no `inverse_transform` call
      #  Because then it'll just be two consecutive calls to `_format_predictions` with `self.run`
  
      with suppress(
          AttributeError
      ):  # TODO: Drop `suppress` - Was for `feature_engineer={}`
          # NOTE: How does `FeatureEngineer` know these are predictions to invert, not inputs?
          #   Probably need to make an assumption for now, albeit a fairly safe one
          self.run = feature_engineer.inverse_transform(self.run)
  
      self.run = _format_prediction(self.run, target_column)
      self.T.run = _format_prediction(self.T.run, target_column)
  
      self.fold += self.run
      self.T.fold += self.T.run
  
imports: from hyperparameter_hunter.data.data_core import BaseDataChunk
  from hyperparameter_hunter.feature_engineering import FeatureEngineer
  from contextlib import suppress
  from copy import deepcopy
  import numpy
  import pandas
label_desc: Use image node_id 4 for calling the BasePredictionChunk obj's underlying member method code with example usage: obj.on_run_end(prediction, feature_engineer, target_column) without return types