docstr: Create labeled and unlabeled files for N recommenders
docstr_tok: ["Create","labeled","and","unlabeled","files","for","N","recommenders"]
code: def create_initial_files(self):
      """
      Create labeled and unlabeled files for N recommenders
      """
      for r in self.recommenders:
          labeled_file = (
              os.path.dirname(self.train_file)
              + "/labeled_set_"
              + str(r)
              + ".dat"
          )
          self.labeled_files.setdefault(r, labeled_file)
          unlabeled_file = (
              os.path.dirname(self.train_file)
              + "/unlabeled_set_"
              + str(r)
              + ".dat"
          )
          self.unlabeled_files.setdefault(r, unlabeled_file)
  
          self.write_with_dict(labeled_file, self.train_set["feedback"])
          self.write_file(
              self.unlabeled_set, unlabeled_file, score=False
          )
          self.unlabeled_data.setdefault(r, self.unlabeled_set)
  
      if self.ensemble_method:
          self.ensemble_file = (
              os.path.dirname(self.train_file) + "/ensemble_set.dat"
          )
          self.write_with_dict(
              self.ensemble_file, self.train_set["feedback"]
          )
  
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 3 for calling the ECoRec obj's underlying member method code with example usage: obj.create_initial_files() without return types