1 code implementation • 5 May 2020 • Sebastiaan Höppner, Bart Baesens, Wouter Verbeke, Tim Verdonck
Fraud detection is to be acknowledged as an instance-dependent cost-sensitive classification problem, where the costs due to misclassification vary between instances, and requiring adapted approaches for learning a classification model.
Applications
1 code implementation • 22 Mar 2020 • Bart Baesens, Sebastiaan Höppner, Irene Ortner, Tim Verdonck
Detecting fraud in such a highly imbalanced data set typically leads to predictions that favor the majority group, causing fraud to remain undetected.
no code implementations • 21 Dec 2017 • Sebastiaan Höppner, Eugen Stripling, Bart Baesens, Seppe vanden Broucke, Tim Verdonck
Customer retention campaigns increasingly rely on predictive models to detect potential churners in a vast customer base.