code: def regret(
      experiment,
      with_evc_tree=True,
      order_by="suggested",
      verbose_hover=True,
      **kwargs,
  ):
      """
      Make a plot to visualize the performance of the hyper-optimization process.
  
      The x-axis contain the trials and the y-axis their respective best performance.
  
      Parameters
      ----------
      experiment: ExperimentClient or Experiment
          The orion object containing the experiment data
  
      with_evc_tree: bool, optional
          Fetch all trials from the EVC tree.
          Default: True
  
      order_by: str
          Indicates how the trials should be ordered. Acceptable options are below.
          See attributes of ``Trial`` for more details.
  
          * 'suggested': Sort by trial suggested time (default).
          * 'reserved': Sort by trial reserved time.
          * 'completed': Sort by trial completed time.
  
      verbose_hover: bool
          Indicates whether to display the hyperparameter in hover tooltips. True by default.
  
      kwargs: dict
          All other plotting keyword arguments to be passed to
          :plotly:`express.line`.
  
      Returns
      -------
      plotly.graph_objects.Figure
  
      Raises
      ------
      ValueError
          If no experiment is provided.
  
      """
      return backend.regret(
          experiment,
          with_evc_tree=with_evc_tree,
          order_by=order_by,
          verbose_hover=verbose_hover,
          **kwargs,
      )
  
file_path: orion/src/orion/plotting/base.py
imports: import orion.plotting.backend_plotly
label_desc: Use image node_id 7 for calling a global function with example usage: regret(experiment, with_evc_tree, order_by, verbose_hover) and returns: backend