code: def cric__random_forest():
      """Random Forest"""
      model = sklearn.ensemble.RandomForestClassifier(
          100, random_state=0
      )
  
      # we want to explain the raw probability outputs of the trees
      model.predict = lambda X: model.predict_proba(X)[:, 1]
  
      return model
  
imports: import numpy
  import sklearn
  import sklearn.ensemble
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 16 for calling a global function with example usage: cric__random_forest() and returns: model