code: def test_adaboost():
      config = {
          "algorithm": "Regression",
          "enableAdaboost": True,
          "num_of_weak_classifier": 10,
          "enableParallelism": False,
      }
      df = pd.read_csv("dataset/adaboost.txt")
      validation_df = df.copy()
  
      model = cb.fit(
          df, config, validation_df=validation_df, silent=True
      )
  
      instance = [4, 3.5]
  
      prediction = cb.predict(model, instance)
  
      assert prediction == -1
      assert len(model["trees"]) > 1
  
      logger.info("✅ adaboost model restoration test done")
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_adaboost() without return types