docstr: Selects the best model.
  
  Parameters
  ----------
  select_by : str or list of str
      Name of the strategy that chooses the model. The choices are specific to the
      implementation.
  
  Returns
  -------
  model_selection_result : ModelSelectionResult or None
      A model selection result object which contains the data of the selected model
      or None if no model could be selected.
docstr_tok: ["Selects","the","best","model",".","Parameters","--","--","--","--","--","select_by",":","str","or","list","of","str","Name","of","the","strategy","that","chooses","the","model",".","The","choices","are","specific","to","the","implementation",".","Returns","--","--","--","-","model_selection_result",":","ModelSelectionResult","or","None","A","model","selection","result","object","which","contains","the","data","of","the","selected","model","or","None","if","no","model","could","be","selected","."]
code: def select(self, select_by=None):
      """Selects the best model.
  
      Parameters
      ----------
      select_by : str or list of str
          Name of the strategy that chooses the model. The choices are specific to the
          implementation.
  
      Returns
      -------
      model_selection_result : ModelSelectionResult or None
          A model selection result object which contains the data of the selected model
          or None if no model could be selected.
      """
      pass
  
imports: import numpy
  from abc import ABC
  from small_text.training.metrics import Metric
label_desc: Use image node_id 2 for calling the ModelSelectionManager obj's underlying member method code with example usage: obj.select(select_by) without return types