docstr: Method to create a feedback matrix having users as rows and items as columns
docstr_tok: ["Method","to","create","a","feedback","matrix","having","users","as","rows","and","items","as","columns"]
code: def create_matrix(self):
      """
      Method to create a feedback matrix having users as rows and items as columns
  
      """
  
      self.matrix = np.zeros((len(self.users), len(self.items)))
  
      for user in self.train_set["users"]:
          for item in self.train_set["feedback"][user]:
              self.matrix[self.user_to_user_id[user]][
                  self.item_to_item_id[item]
              ] = self.train_set["feedback"][user][item]
  
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 3 for calling the BaseRatingPrediction obj's underlying member method code with example usage: obj.create_matrix() without return types