code: def human_or_01(X, y, model_generator, method_name):
      """OR (false/true)
  
      This tests how well a feature attribution method agrees with human intuition
      for an OR operation combined with linear effects. 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
      if fever or cough: +6 points
  
      transform = "identity"
      sort_order = 1
      """
      return _human_or(X, model_generator, method_name, False, 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 51 for calling a global function with example usage: human_or_01(X, y, model_generator, method_name) and returns: _human_or