This study investigates the use of ensemble learning models bagging, boosting, and
stacking to enhance the accuracy and reliability of predicting customer subscriptions in bank …

Predicting credit default risk is important to financial institutions, as accurately predicting the
likelihood of a borrower defaulting on their loans will help to reduce financial losses, thereby …

One of the most important issues affecting machine learning performance is class imbalance
problems. In this case, which is frequently encountered in real-world problems, the effect of …