Umarkhon Mukhamedov

A Multimetric Evaluation of Ensemble and Neural Models for Imbalanced Credit Scoring on the German Credit Dataset

Credit scoring models must balance global discrimination, minority-class detection, probability quality, and computational efficiency, particularly when default cases are less frequent than non-default cases. This study benchmarks Logistic Regression, Random Forest, XGBoost, and a Multilayer Perceptron using the German...