code: def __caclulate_optimal_neighbor_cluster_score(self, index_cluster, difference):
          
  
          optimal_score = float('inf')
          for index_neighbor_cluster in range(len(self.__clusters)):
              if index_cluster != index_neighbor_cluster:
                  candidate_score = self.__calculate_cluster_score(index_neighbor_cluster, difference)
                  if candidate_score < optimal_score:
                      optimal_score = candidate_score
  
          if optimal_score == float('inf'):
              optimal_score = -1.0
  
          return optimal_score
docs: !
          @brief Calculates 'B' score for the specific object for the nearest cluster.
  
          @param[in] index_point (uint): Index point from input data for which 'B' score should be calculated.
          @param[in] index_cluster (uint): Index cluster to which the point is belong to.
  
          @return (float) 'B' score for the object.