Mohammad Shamsu Uddin
Mohammad Shamsu Uddin is a Theory of Investment Doctor graduate student, Faculty of Economics and Management, Dalian University of Technology, Dalian 116024, China. His research interest includes financial risk management, credit scoring, asset liability management, data mining, and artificial intelligence.
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This paper examines which hybridization strategy is more suitable for credit risk assessment in the dynamic financial world.
This study compares the gradient-boosting model with four other well-known classifiers, namely, a classification and regression tree (CART), logistic regression (LR), multivariate adaptive regression splines (MARS) and a random forest (RF).