class_docstr: This is an abstract class.
  All algorithms inherit from BaseAlgorithm.
code: def set_params(self, json_desc, learner_path):
      self.library_version = json_desc.get(
          "library_version", self.library_version
      )
      self.algorithm_name = json_desc.get(
          "algorithm_name", self.algorithm_name
      )
      self.algorithm_short_name = json_desc.get(
          "algorithm_short_name", self.algorithm_short_name
      )
      self.uid = json_desc.get("uid", self.uid)
      self.params = json_desc.get("params", self.params)
      self.name = json_desc.get("name", self.name)
      self.model_file_path = learner_path
  
      if hasattr(self, "best_ntree_limit"):
          self.best_ntree_limit = json_desc.get(
              "best_ntree_limit", self.best_ntree_limit
          )
  
imports: import uuid
  import numpy
  from supervised.utils.common import construct_learner_name
  from supervised.utils.importance import PermutationImportance
  from supervised.utils.shap import PlotSHAP
label_desc: Use image node_id 16 for calling the BaseAlgorithm obj's underlying member method code with example usage: obj.set_params(json_desc, learner_path) without return types