class_docstr: Base class for missing values in supervised learning.
class_docstr_tok: ["Base","class","for","missing","values","in","supervised","learning","."]
code: def test_create_with_missing_target(self):
      if self.model is None or not self.support_missing_value:
          return
  
      train_sf = self.sf.copy()
      create_fun = self.get_create_function_of_model(self.model)
  
      with self.assertRaises(ToolkitError):
          train_sf_with_na = self.fill_with_na(train_sf, "y")
          model = create_fun(
              train_sf_with_na, self.target, validation_set=None
          )
  
      with self.assertRaises(ToolkitError):
          train_sf_with_na = self.fill_some_na(train_sf, "y")
          model = create_fun(
              train_sf_with_na, self.target, validation_set=None
          )
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import turicreate
  import array
  from turicreate.toolkits._main import ToolkitError
label_desc: Use image node_id 6 for calling the SupervisedLearningMissingValueTest obj's underlying member method code with example usage: obj.test_create_with_missing_target() without return types