code: def normalize_r_value(self):
          '''
          Normalize r-value.
  
          Override.
  
          This method is called in each learning steps.
  
          For example:
              self.r_df = self.r_df.r_value / self.r_df.r_value.sum()
          '''
          if self.r_df is not None and self.r_df.shape[0]:
              # z-score normalization.
              self.r_df.r_value = (self.r_df.r_value - self.r_df.r_value.mean()) / self.r_df.r_value.std(f normalize_r_value(self):
          '''
          Normalize r-value.
  
          Override.
  
          This method is called in each learning steps.
  
          For example:
              self.r_df = self.r_df.r_value / self.r_df.r_value.sum()
          '''
          if self.r_df is not None and self.r_df.shape[0]:
              # z-score normalization.
              self.r_df.r_value = (self.r_df.r_value - self.r_df.r_value.mean()) / self.r_df.r_value.std()
docs: Normalize r-value.
  
          Override.
  
          This method is called in each learning steps.
  
          For example:
              self.r_df = self.r_df.r_value / self.r_df.r_value.sum()