code: def overall_CEN_calc(classes, TP, TOP, P, CEN_dict, modified=False):
      """
      Calculate Overall_CEN (Overall confusion entropy).
  
      :param classes: confusion matrix classes
      :type classes: list
      :param TP: true positive
      :type TP: dict
      :param TOP: number of positives in predict vector per class
      :type TOP: dict
      :param P: number of actual positives per class
      :type P: dict
      :param CEN_dict: CEN dictionary for each class
      :type CEN_dict: dict
      :param modified: modified mode flag
      :type modified: bool
      :return: Overall_CEN(MCEN) as float
      """
      try:
          result = 0
          for i in classes:
              result += (
                  convex_combination(classes, TP, TOP, P, i, modified)
                  * CEN_dict[i]
              )
          return result
      except Exception:
          return "None"
  
imports: from __future__ import division
  import math
  import operator
  from functools import reduce
  from .pycm_interpret import *
  from .pycm_ci import kappa_SE_calc, CI_calc, SE_calc
  from .pycm_util import complement
label_desc: Use image node_id 15 for calling a global function with example usage: overall_CEN_calc(classes, TP, TOP, P, CEN_dict, modified) and returns: result, str