For the unbalanced data set, using machine learning methods, three kinds of anti-balance are proposed. Fraud model. Firstly, data preprocessing is performed by using undersampling method. Secondly, Lasso-Logistic, XGBoost, and the above two models are used to model and predict. Finally, the ...
It is well-suited for multi-class classification tasks in the context of missing data [34]. The Extreme Gradient Boosting (XGBoost) classifier is a widely recognized ensemble learning technique with advantages in predictive accuracy and speed, robustly able to handle missing data effectively, further...