code: def classification_random(model, test_fraction=0.02):
      return (
          model,
          utils.get_classification_random_data_model_trainer(
              test_fraction
          ),
          CLASSIFICATION,
      )
  
imports: from sys import setrecursionlimit
  import lightgbm
  import lightning.classification
  import lightning.regression
  import numpy
  import pytest
  import statsmodels.api
  import xgboost
  from sklearn import ensemble, linear_model, svm, tree
  from statsmodels.regression.process_regression import ProcessMLE
  from tests import utils
  from tests.e2e import executors
label_desc: Use image node_id 5 for calling a global function with example usage: classification_random(model, test_fraction) and returns: model,  utils,  CLASSIFICATION