class_docstr: An algorithm in this context is loosely defined as a data processing pipeline consisting of multiple components
  such as image preprocessing, followed by deep learning model training and evaluation.
class_docstr_tok: ["An","algorithm","in","this","context","is","loosely","defined","as","a","data","processing","pipeline","consisting","of","multiple","components","such","as","image","preprocessing",",","followed","by","deep","learning","model","training","and","evaluation","."]
docstr: Returns the model quality measurement based on training and validation datasets.
docstr_tok: ["Returns","the","model","quality","measurement","based","on","training","and","validation","datasets","."]
code: def get_score(self, *args, **kwargs):
      """Returns the model quality measurement based on training and validation datasets."""
      pass
  
file_path: MONAI/monai/auto3dseg/algo_gen.py
imports: from __future__ import annotations
  from monai.config import PathLike
  from monai.transforms import Randomizable
label_desc: Use image node_id 4 for calling the Algo obj's underlying member method code with example usage: obj.get_score() without return types