code: def model(opt):
      rgf = RGFClassifier(
          max_leaf=opt["max_leaf"],
          reg_depth=opt["reg_depth"],
          min_samples_leaf=opt["min_samples_leaf"],
          algorithm="RGF_Sib",
          test_interval=100,
          verbose=False,
      )
      scores = cross_val_score(rgf, X, y, cv=3)
  
      return scores.mean()
  
imports: from sklearn.datasets import load_breast_cancer
  from sklearn.model_selection import cross_val_score
  from rgf.sklearn import RGFClassifier
  from hyperactive import Hyperactive
label_desc: Use image node_id 1 for calling a global function with example usage: model(opt) and returns: scores