def __get_variance_increase_distance(self, entry):
linear_part_12 = list_math_addition(self.linear_sum, entry.linear_sum);<EOL>variance_part_first = (self.square_sum + entry.square_sum) -<NUM_LIT> * sum(list_math_multiplication(linear_part_12, linear_part_12)) / (self.number_points + entry.number_points) +(self.number_points + entry.number_points) * sum(list_math_multiplication(linear_part_12, linear_part_12)) / (self.number_points + entry.number_points)**<NUM_LIT>;<EOL>linear_part_11 = sum(list_math_multiplication(self.linear_sum, self.linear_sum));<EOL>variance_part_second = -( self.square_sum - (<NUM_LIT> * linear_part_11 / self.number_points) + (linear_part_11 / self.number_points) );<EOL>linear_part_22 = sum(list_math_multiplication(entry.linear_sum, entry.linear_sum));<EOL>variance_part_third = -( entry.square_sum - (<NUM_LIT> / entry.number_points) * linear_part_22 + entry.number_points * (<NUM_LIT:1.0> / entry.number_points ** <NUM_LIT>) * linear_part_22 );<EOL>return (variance_part_first + variance_part_second + variance_part_third)<EOL>
!
        @brief Calculates variance increase distance between current and specified clusters.

        @param[in] entry (cfentry): Clustering feature to which distance should be obtained.

        @return (double) Variance increase distance.