code: def gini_xgb(prediction, target):
      target = target.get_label()
      gini_score = gini_normalized_c(target, prediction)
      return [("gini", gini_score)]
  
file_path: hyperparameter_hunter/examples/feature_engineering_examples/olivier_porto_seguro_kaggle.py
imports: from hyperparameter_hunter import Environment, CVExperiment, FeatureEngineer, EngineerStep
  import numpy
  import pandas
  from sklearn.model_selection import StratifiedKFold
  from sklearn.preprocessing import LabelEncoder
  from xgboost import XGBClassifier
label_desc: Use image node_id 3 for calling a global function with example usage: gini_xgb(prediction, target) and returns: list