To fit the model, we use the machine learning library XGBoost. … the maximum and total amount, and the number of transactions of each of almost 30 different transaction types.

The top-performing model was a LightGBM … The aggregation functions include sum, mean, minimum, maximum, and count. We also compare aggregations over two time windows using ratios and differences.

…leverages recursive feature elimination with cross-validation for optimal feature selection. Subsequently, Optuna is employed to fine-tune hyperparameters for the XGBoost model.

…innovative methods such as graph analysis and anomaly detection were suggested to overcome the limitations of rule-based systems.

DNB va Feedzai retseptlari bizda pastroq: ularda nisbiy tur farqlari yo'q. Anomaliya ≠ eskalatsiya.