class_docstr: Unit test class for testing scikit-learn converter.
class_docstr_tok: ["Unit","test","class","for","testing","scikit-learn","converter","."]
code: def test_binary_class_string_label_with_probability_stress_test(self):
      # Scikit Learn uses technique to normalize pairwise probabilities even for binary classification.
      # This leads to difference in probabilities.
      self._evaluation_test_helper(
          ["foo", "bar"],
          True,
          allow_slow=True,
          allowed_prob_delta=0.005,
      )
  
imports: import unittest
  import tempfile
  import os
  import pandas
  import random
  import pytest
  from coremltools.models.utils import evaluate_classifier, evaluate_classifier_with_probabilities, _macos_version, _is_macos
  from coremltools._deps import _HAS_LIBSVM, MSG_LIBSVM_NOT_FOUND, _HAS_SKLEARN, MSG_SKLEARN_NOT_FOUND
label_desc: Use image node_id 4 for calling the NuSvcScikitTest obj's underlying member method code with example usage: obj.test_binary_class_string_label_with_probability_stress_test() without return types