code: def test_gbm_regression():
      config = {
          "algorithm": "Regression",
          "enableGBM": True,
          "epochs": 10,
          "learning_rate": 1,
      }
  
      df = pd.read_csv("dataset/golf4.txt")
      validation_df = pd.read_csv("dataset/golf4.txt")
  
      model = cb.fit(
          df, config, validation_df=validation_df, silent=True
      )
      assert model["config"]["algorithm"] == "Regression"
      assert len(model["trees"]) > 1
  
      features = ["Sunny", 85, 85, "Weak"]
      target = 25
      prediction = cb.predict(model, features)
      assert abs(prediction - target) < 1
  
imports: import pandas
  from chefboost import Chefboost
  from chefboost.commons.logger import Logger
label_desc: Use image node_id 1 for calling a global function with example usage: test_gbm_regression() without return types