code: def return_models_voting(classifier_list):
      estimators = []
  
      for classifier in classifier_list:
          clf = models[classifier](
              None, None, {"no_params": 0}, trained=False
          )
          estimators.append((str(clf), clf))
  
      return estimators
  
imports: from pandas.core.algorithms import mode
  from pandas.io import json
  from sklearn.metrics import accuracy_score
  from sklearn.linear_model import LinearRegression
  from sklearn.ensemble import RandomForestRegressor
  import os
  from sklearn.ensemble import BaggingClassifier
  import sys
  from importlib import import_module
  import shutil
  from sklearn.ensemble import VotingClassifier
  import ssl
  from nylon.preprocessing.preprocessing import initial_preprocessor
  import nltk
  import pandas
  import time
  from sklearn.model_selection import train_test_split
  from sklearn.decomposition import PCA
  from nylon.modeling.modeling import a_svm, nearest_neighbors, a_tree, sgd, gradient_boosting, adaboost, rf, mlp, default_modeling, svm_stroke, ensemble_stroke
  from nylon.preprocessing.preprocessing_methods import handle_scaling, handle_min_max, handle_label_encode, handle_ordinal, handle_filling, handle_importance, handle_one_hot, handle_text, handle_embedding, handle_dates
  from nylon.analysis.analysis import default_analysis, acc_score, cross_score, confusion, precision_calculation, recall_score_helper
  from nylon.data.reader import DataReader
label_desc: Use image node_id 4 for calling a global function with example usage: return_models_voting(classifier_list) and returns: estimators