docstr: Extends compute method from BaseRatingPrediction. Method to run recommender algorithm
  
  :param verbose: Print recommender and database information
  :type verbose: bool, default True
  
  :param metrics: List of evaluation measures
  :type metrics: list, default None
  
  :param verbose_evaluation: Print the evaluation results
  :type verbose_evaluation: bool, default True
  
  :param as_table: Print the evaluation results as table
  :type as_table: bool, default False
  
  :param table_sep: Delimiter for print results (only work with verbose=True and as_table=True)
  :type table_sep: str, default ' '
code: def compute(
      self,
      verbose=True,
      metrics=None,
      verbose_evaluation=True,
      as_table=False,
      table_sep="\t",
  ):
      """
      Extends compute method from BaseRatingPrediction. Method to run recommender algorithm
  
      :param verbose: Print recommender and database information
      :type verbose: bool, default True
  
      :param metrics: List of evaluation measures
      :type metrics: list, default None
  
      :param verbose_evaluation: Print the evaluation results
      :type verbose_evaluation: bool, default True
  
      :param as_table: Print the evaluation results as table
      :type as_table: bool, default False
  
      :param table_sep: Delimiter for print results (only work with verbose=True and as_table=True)
      :type table_sep: str, default '\t'
  
      """
  
      super(SVD, self).compute(verbose=verbose)
  
      if verbose:
          self.init_model()
          print("training_time:: %4f sec" % timed(self.fit))
          if self.extra_info_header is not None:
              print(self.extra_info_header)
  
          print("prediction_time:: %4f sec" % timed(self.predict))
  
          print("\n")
  
      else:
          # Execute all in silence without prints
          self.init_model()
          self.fit()
          self.predict()
  
      self.write_predictions()
  
      if self.test_file is not None:
          self.evaluate(
              metrics,
              verbose_evaluation,
              as_table=as_table,
              table_sep=table_sep,
          )
  
file_path: CaseRecommender/caserec/recommenders/rating_prediction/svd.py
imports: import numpy
  from scipy.sparse.linalg import svds
  from caserec.recommenders.rating_prediction.base_rating_prediction import BaseRatingPrediction
  from caserec.utils.extra_functions import timed
label_desc: Use image node_id 6 for calling the SVD obj's underlying member method code with example usage: obj.compute(verbose, metrics, verbose_evaluation, as_table, table_sep) without return types