The training set adopts six commonly used machine learning algorithms, including DT, SVM, NB, KNN, XGBoost, and GBM. Model evaluation is mainly evaluated through accuracy, precision, recall, F1 score, and AUC value. The model with the highest AUC value is selected as the optimal model.
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