Imbalanced enterprise credit evaluation with DTE-SBD: Decision tree ensemble based on SMOTE and bagging with differentiated sampling rates

Enterprise credit evaluation model is an important tool for bank and enterprise risk management, but how to construct an effective decision tree (DT) ensemble model for imbalanced enterprise credit evaluation is seldom studied. This paper proposes a new DT ensemble model for imbalanced enterprise credit evaluation based on the synthetic minority over-sampling technique (SMOTE) and the Bagging ensemble learning algorithm with differentiated...