code: def learn_confident_parallel(self):
      pool = Pool()
  
      method = getattr(self, self.confidence_measure)
      result = pool.map(method, self.recommenders)
      pool.close()
      pool.join()
  
      for n, r in enumerate(self.recommenders):
          self.rec_conf.setdefault(r, result[n][0])
          self.recommenders_confident.setdefault(r, result[n][1])
  
imports: from multiprocessing.pool import Pool
  from random import shuffle
  import numpy
  import os
  from caserec.recommenders.rating_prediction.itemknn import ItemKNN
  from caserec.recommenders.rating_prediction.matrixfactorization import MatrixFactorization
  from caserec.recommenders.rating_prediction.svdplusplus import SVDPlusPlus
  from caserec.recommenders.rating_prediction.userknn import UserKNN
  from caserec.utils.process_data import ReadFile
  from caserec.utils.extra_functions import ComputeBui
label_desc: Use image node_id 9 for calling the ECoRec obj's underlying member method code with example usage: obj.learn_confident_parallel() without return types