code: def test_randomforest_for_regression():
      config = {
          "algorithm": "ID3",
          "enableRandomForest": True,
          "num_of_trees": 5,
      }
      df = pd.read_csv("dataset/car_reg.data")
      model = cb.fit(df, config, silent=True)
  
      assert model["evaluation"]["train"]["MAE"] < 30
      assert model["config"]["algorithm"] == "Regression"
  
      instance = ["high", "high", 4, "more", "big", "high"]
      target = 100
      prediction = cb.predict(model, instance)
      assert abs(prediction - target) < 30
  
imports: import pandas
  from chefboost import Chefboost
  from chefboost.commons.logger import Logger
label_desc: Use image node_id 2 for calling a global function with example usage: test_randomforest_for_regression() without return types