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(self):
      if self.model is None:
          return
  
      train_sf = self.sf.copy()
      create_fun = self.get_create_function_of_model(self.model)
  
      # Missing value in each column
      # -------------------------------
      for col in ["int", "float", "dict", "array", "str"]:
          model = create_fun(train_sf, self.target, validation_set=None)
  
      # Missing value at top of each column
      # -------------------------------
      for col in ["int", "float", "dict", "array", "str"]:
          model = create_fun(train_sf, 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 3 for calling the SupervisedLearningStringTargetBinary obj's underlying member method code with example usage: obj.test_create() without return types