code: def human_sum_11(X, y, model_generator, method_name):
      """SUM (true/true)
  
      This tests how well a feature attribution method agrees with human intuition
      for a SUM operation. This metric deals
      specifically with the question of credit allocation for the following function
      when all three inputs are true:
      if fever: +2 points
      if cough: +2 points
  
      transform = "identity"
      sort_order = 2
      """
      return _human_sum(X, model_generator, method_name, True, True)
  
imports: import hashlib
  import os
  import time
  import numpy
  import sklearn
  from ..None import __version__
  from .None import measures, methods
label_desc: Use image node_id 60 for calling a global function with example usage: human_sum_11(X, y, model_generator, method_name) and returns: _human_sum