code: def test_learn_one_methods(model):
      """Assert that the methods of the Naives Bayes class behave correctly."""
      assert model.predict_proba_one("not fitted yet") == {}
      assert model.predict_one("not fitted yet") is None
  
      for x, y in yield_dataset():
          model.learn_one(x, y)
  
      # Check class methods.
      if isinstance(
          model["model"], naive_bayes.ComplementNB
      ) or isinstance(model["model"], naive_bayes.MultinomialNB):
          assert model["model"]._more_tags() == {"positive input"}
      assert model["model"]._multiclass
  
file_path: river/river/naive_bayes/test_naive_bayes.py
imports: from __future__ import annotations
  import pandas
  import pytest
  from sklearn import naive_bayes
  from river import compose, feature_extraction, naive_bayes
label_desc: Use image node_id 7 for calling a global function with example usage: test_learn_one_methods(model) without return types