GA-XGBoost algorithm

Input: Iterations per Time Step T, parameter number N, population size P, Number of excellent individuals M

Output: optimal paramrters

1. Initialize( ${\theta }_{i1},{\theta }_{i2},\cdots ,{\theta }_{iN}$ )

2. while termination condition is not met do

3. AUC on the XGBoost model

4. Calculate fitness

5. Select the optimal parameters according to fitness value

6. GA(T, N, M, P)

7. Produce new parameters

8. end while