code: def test_gbm_classification():
      config = {
          "algorithm": "ID3",
          "enableGBM": True,
          "epochs": 10,
          "learning_rate": 1,
      }
  
      df = pd.read_csv(
          "dataset/iris.data",
          names=[
              "Sepal length",
              "Sepal width",
              "Petal length",
              "Petal width",
              "Decision",
          ],
      )
      validation_df = df.copy()
  
      model = cb.fit(
          df, config, validation_df=validation_df, silent=True
      )
  
      instance = [7.0, 3.2, 4.7, 1.4]
      target = "Iris-versicolor"
      prediction = cb.predict(model, instance)
      assert prediction == target
  
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_gbm_classification() without return types