code: def create_embedded_meth(self):
          
          # Generate related trees:
          fns = []
          for idx, estimator in enumerate(self.estimators):
              tree = self.create_single_method(idx, estimator)
              fns.append(tree)
          fns = '\n'.join(fns)
  
          # Generate method or function names:
          fn_names = ''
          if self.target_language in ['c', 'java']:
              fn_names = []
              temp_method_calls = self.temp('embedded.method_calls', n_indents=2,
                                            skipping=True)
              for idx, estimator in enumerate(self.estimators):
                  cl_name = self.class_name
                  fn_name = self.method_name + '_' + str(idx)
                  fn_name = temp_method_calls.format(class_name=cl_name,
                                                     method_name=fn_name,
                                                     method_index=idx)
                  fn_names.append(fn_name)
              fn_names = '\n'.join(fn_names)
              fn_names = self.indent(fn_names, n_indents=1, skipping=True)
  
          # Merge generated content:
          n_indents = 1 if self.target_language in ['java', 'js'] else 0
          temp_method = self.temp('embedded.method')
          method = temp_method.format(method_name=self.method_name,
                                      class_name=self.class_name,
                                      method_calls=fn_names, methods=fns,
                                      n_estimators=self.n_estimators,
                                      n_classes=self.n_classes)
          return self.indent(method, n_indents=n_indents, skipping=True)
docs: Build the estimator methods or functions.
  
          Returns
          -------
          :return : string
              The built methods as merged string.