docstr: initializer
  
  answers - a vector of answers to be returned by "predict"
  
  classes - a vector of class numbers to be used to populate classes_
code: def __init__(self, answers, classes):
      """initializer
  
      answers - a vector of answers to be returned by "predict"
  
      classes - a vector of class numbers to be used to populate classes_
      """
      self.answers_ = answers
      self.classes_ = classes
  
imports: import contextlib
  import io
  import os
  import pickle
  import tempfile
  import numpy
  import pytest
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.modules
  from cellprofiler_core.constants.measurement import FF_PARENT, FF_COUNT, FF_CHILDREN_COUNT, M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, M_LOCATION_CENTER_Z, M_NUMBER_OBJECT_NUMBER
  import cellprofiler.modules.filterobjects
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 1 to create a new FakeClassifier object from inherited base classes: object with example: obj = FakeClassifier(answers, classes)