docstr: Train the model in a co-training process
docstr_tok: ["Train","the","model","in","a","co-training","process"]
code: def train_model(self):
      """
      Train the model in a co-training process
      """
  
      epoch = 0
      while not self.empty:
          print("Epoch:: ", epoch)
          self.recommenders_predictions = dict()
          self.recommenders_confident = dict()
  
          if not self.run_recommenders_parallel():
              break
  
          self.learn_confident_parallel()
          self.update_data()
  
          epoch += 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 4 for calling the ECoRec obj's underlying member method code with example usage: obj.train_model() without return types