This paper develops an early warning system for predicting distress for large European banks. Using a novel definition of distress derived from banks' headroom above regulatory requirements, we investigate the performance of three machine learning techniques against the traditional logistic...

This research article presents a comparative analysis between logistic regression as a traditional method, artificial neural networks (ANNs), and decision tree as machine learning techniques for predicting credit risk. It meticulously examines and evaluates these three methods, elucidating their...

Feature selection identifies the relevant features and removes the irrelevant and redundant ones, intending to obtain the best-performing feature subset. This paper proposes a new feedback feature selection system with a reinforcement learning-based method to identify the best feature subset....