code: def _evaluation_test_helper_with_probability(
      self, labels, allow_slow
  ):
      import copy
  
      df = pd.DataFrame(self.x, columns=self.column_names)
      y = copy.copy(self.y)
      for i, val in enumerate(labels):
          y[i] = val
      probability_param = "-b 1"
  
      for param1 in self.non_kernel_parameters:
          for param2 in self.kernel_parameters:
              param_str = " ".join(
                  [self.base_param, param1, param2, probability_param]
              )
              # print("PARAMS: ", param_str)
              param = svm_parameter(param_str)
  
              model = svm_train(self.prob, param)
  
              # Get predictions with probabilities as dictionaries
              (df["prediction"], _, probability_lists) = svm_predict(
                  y, self.x, model, probability_param + " -q"
              )
              probability_dicts = [
                  dict(zip([1, 2], cur_vals))
                  for cur_vals in probability_lists
              ]
              df["probabilities"] = probability_dicts
  
              spec = libsvm.convert(
                  model, self.column_names, "target", "probabilities"
              )
  
              if _is_macos() and _macos_version() >= (10, 13):
                  metrics = evaluate_classifier_with_probabilities(
                      spec, df, verbose=False
                  )
                  self.assertEquals(metrics["num_key_mismatch"], 0)
                  self.assertLess(
                      metrics["max_probability_error"], 0.00001
                  )
  
              if not allow_slow:
                  break
  
          if not allow_slow:
              break
  
imports: import unittest
  import tempfile
  import os
  import pandas
  import random
  import pytest
  import numpy
  from coremltools.models.utils import evaluate_classifier, evaluate_classifier_with_probabilities, _macos_version, _is_macos
  from coremltools._deps import _HAS_LIBSVM, _HAS_SKLEARN
label_desc: Use image node_id 11 for calling the CSVCLibSVMTest obj's underlying member method code with example usage: obj._evaluation_test_helper_with_probability(labels, allow_slow) without return types