The code uses Python 3.7.16
The relevant dependency libraries can be found in requirements.txt
This code includes mahakil, xgboost, gridsearchcv, and K-Fold Cross Validation.
Mahakil is designed to solve the problem of sample imbalance.
Xgboost solves classification problems.
Gridsearchcv optimizes the xgboost parameters to make this algorithm applicable to datasets of different volumes.
In K-Fold Cross Validation, K=10.
If you want to use this algorithm, you only need to call the function(train_mak_ xgb) in Mahakil_XGBoost.py
The test case is in the main function in Mahakil_XGBoost.py