code: def __get_incorrects(label, sf, evaluation):
      sf = sf.filter_by([False], "correct")
  
      if sf["target_label"].dtype == int:
          label = int(label)
  
      filtered_sframe = sf.filter_by([label], "target_label")
      unique_predictions = list(
          filtered_sframe["predicted_label"].unique()
      )
  
      data = []
      for u in unique_predictions:
          u_filt = filtered_sframe.filter_by([u], "predicted_label")
          data.append(
              {
                  "label": str(u),
                  "images": list(u_filt[evaluation._data["feature"]]),
              }
          )
  
      return (
          _json.dumps(
              {
                  "data_spec": {
                      "incorrects": {"target": label, "data": data}
                  }
              }
          )
          + "\n"
      )
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from ...visualization import _get_client_app_path
  import turicreate
  import subprocess
  import six
  from six.moves import _thread
  import json
  import base64
  import math
label_desc: Use image node_id 4 for calling a global function with example usage: __get_incorrects(label, sf, evaluation) and returns: unknown