code: def test_disallow_comparison_to_missing_value(self, missing, dtype_):
      if dtype_ == categorical_dtype:
          missing = str(missing)
  
      class C(Classifier):
          dtype = dtype_
          missing_value = missing
          inputs = ()
          window_length = 0
  
      with self.assertRaises(ValueError) as e:
          C().eq(missing)
      errmsg = str(e.exception)
      self.assertEqual(
          errmsg,
          "Comparison against self.missing_value ({v!r}) in C.eq().\n"
          "Missing values have NaN semantics, so the requested comparison"
          " would always produce False.\n"
          "Use the isnull() method to check for missing values.".format(
              v=missing,
          ),
      )
  
imports: from functools import reduce
  import operator
  import numpy
  import pandas
  from zipline.lib.labelarray import LabelArray
  from zipline.pipeline import Classifier
  from zipline.pipeline.data.testing import TestingDataSet
  from zipline.pipeline.expression import methods_to_ops
  from zipline.testing import parameter_space
  from zipline.testing.fixtures import ZiplineTestCase
  from zipline.testing.predicates import assert_equal
  from zipline.utils.numpy_utils import categorical_dtype, int64_dtype
  from .base import BaseUSEquityPipelineTestCase
label_desc: Use image node_id 5 for calling the ClassifierTestCase obj's underlying member method code with example usage: obj.test_disallow_comparison_to_missing_value(missing, dtype_) without return types