docstr: Method to initialize recommender algorithm.
docstr_tok: ["Method","to","initialize","recommender","algorithm","."]
code: def read_files(self):
      """
      Method to initialize recommender algorithm.
  
      """
  
      # Getting train_set as a dict_file = {'feedback': dict_feedback, 'users': list_users, 'items': list_items,
      #               'sparsity': sparsity, 'number_interactions': number_interactions, 'users_viewed_item': users_viewed_item, 'items_unobserved': items_unobserved,
      #               'items_seen_by_user': items_seen_by_user, 'mean_value': mean_value, 'max_value': max(list_feedback), 'min_value': min(list_feedback)}
      self.train_set = ReadFile(self.train_file, sep=self.sep).read()
  
      if self.test_file is not None:
          self.test_set = ReadFile(self.test_file, sep=self.sep).read()
  
          # Combining users/items from train and test set
          self.users = sorted(
              set(
                  list(self.train_set["users"])
                  + list(self.test_set["users"])
              )
          )
          self.items = sorted(
              set(
                  list(self.train_set["items"])
                  + list(self.test_set["items"])
              )
          )
      else:
          self.users = self.train_set["users"]
          self.items = self.train_set["items"]
  
      for i, item in enumerate(self.items):
          self.item_to_item_id.update({item: i})
          self.item_id_to_item.update({i: item})
      for u, user in enumerate(self.users):
          self.user_to_user_id.update({user: u})
          self.user_id_to_user.update({u: user})
  
file_path: CaseRecommender/caserec/recommenders/rating_prediction/base_rating_prediction.py
imports: from scipy.spatial.distance import squareform, pdist
  import numpy
  from caserec.evaluation.rating_prediction import RatingPredictionEvaluation
  from caserec.utils.extra_functions import print_header
  from caserec.utils.process_data import ReadFile, WriteFile
label_desc: Use image node_id 2 for calling the BaseRatingPrediction obj's underlying member method code with example usage: obj.read_files() without return types