Best model for unbalanced data

1. Which algorithm is used for imbalanced data?
2. Does XGBoost work well with imbalanced data?

Which algorithm is used for imbalanced data?

SMOTEBoost, proposed by Chawla et al., is a data-level method to deal with the imbalanced data problem. The main steps of the proposed approach are SMOTE sampling and boosting. This algorithm uses SMOTE technique as a data level solution.

Does XGBoost work well with imbalanced data?

The XGBoost model achieved excellent attack detection with F1 scores of 99.9% and 99.87% on the two datasets. This result demonstrated that the proposed approach improved the detection attack performance in imbalanced multiclass IIoT datasets and was superior to existing IDS frameworks.