code: def check_disappearing_features(model, dataset):
      """The model should work fine when features disappear."""
  
      from river import utils
  
      for x, y in dataset:
          features = list(x.keys())
          random.shuffle(features)
          if utils.inspect.isanomalydetector(model):
              model.score_one(
                  {i: x[i] for i in features[:-3]}
              )  # drop 3 features at random
              model.learn_one(x)
          else:
              model.predict_one({i: x[i] for i in features[:-3]})
              model.learn_one(x, y)
  
imports: from __future__ import annotations
  import copy
  import inspect
  import pickle
  import random
  from .utils import assert_predictions_are_close, seed_params
label_desc: Use image node_id 4 for calling a global function with example usage: check_disappearing_features(model, dataset) without return types