code: def make_sklearn_classifier(algo, args):
      name = algo.split(".", 1)[1]
      kwargs = {}
  
      for key in sklearn_kwargs.get(name, []):
          val = getattr(args, key, None)
          if val:
              kwargs[sklearn_keys.get(key, key)] = val
  
      if args.trace and kwargs:
          print("training %s with %s" % (algo, kwargs))
  
      if args.trace and name in verbose_classifiers:
          kwargs["verbose"] = True
  
      return sklearn_classifiers[name](**kwargs)
  
file_path: nltk-trainer/nltk_trainer/classification/args.py
imports: from nltk.classify import DecisionTreeClassifier, MaxentClassifier, NaiveBayesClassifier, megam
  from nltk_trainer import basestring
  from nltk_trainer.classification.multi import AvgProbClassifier
label_desc: Use image node_id 4 for calling a global function with example usage: make_sklearn_classifier(algo, args) and returns: sklearn_classifiers