code: def grid_search_param_with_none():
      parameters = {
          "max_depth": [2, None],
          "criterion": ["gini", "entropy"],
      }
  
      est = RandomForestClassifier(random_state=42)
      clf = GridSearchCV(est, parameters, cv=5)
  
      X, y = datasets.make_classification(
          200, 10, n_informative=5, class_sep=0.7, random_state=42
      )
      clf.fit(X, y)
  
      return clf
  
imports: from copy import copy
  import sys
  import os
  from pathlib import Path
  import numpy
  from sklearn.linear_model import LogisticRegression
  import pytest
  from matplotlib.testing.conftest import mpl_test_settings, mpl_image_comparison_parameters
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import GridSearchCV
  from sklearn import datasets
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 9 for calling a global function with example usage: grid_search_param_with_none() and returns: clf