Journal Articles

Stripling, E, Baesens, B, Chizi, B, & Vanden Broucke, S. (2018). Isolation-based conditional anomaly detection on mixed-attribute data to uncover workers’ compensation fraud. Decision Support Systems, 111, 13-26.

Stripling, Eugen, Vanden Broucke, Seppe, Antonio, Katrien, Baesens, Bart, & Snoeck, Monique. (2018). Profit maximizing logistic model for customer churn prediction using genetic algorithms. Swarm and Evolutionary Computation, 40, 116-130.

Conference Proceedings

Stripling, Eugen, Baesens, B, & Vanden Broucke, S. (n.d.). Regularized Empirical EMP Maximization Framework for Profit-Driven Model Building. Not Known Yet, Not known yet.

Höppner, S, Stripling, E, Baesens, Bart, Vanden Broucke, S, & Verdonck, T. (2018). Profit Driven Decision Trees for Churn Prediction. Proceedings of the Conference on Data Science, Statistics and Visualisation (DSSV 2018), Proceedings of the conference on Data Science, Statistics and Visualisation (DSSV 2018); 2018.

Devos, A, Dhondt, J, Stripling, Eugen, Baesens, Bart, Vanden Broucke, Seppe, & Sukhatme, G. (2018). Profit Maximizing Logistic Regression Modeling for Credit Scoring. Proceedings of the IEEE Data Science Workshop (DSW), 125-129.

Gaussier, E, Cao, LB, Gallinari, P, Kwok, J, Pasi, G, & Zaiane, O. (2015). Profit Maximizing Logistic Regression Modeling for Customer Churn Prediction. PROCEEDINGS OF THE 2015 IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (IEEE DSAA 2015), 851-860.

Abstracts, Presentations, Posters

Stripling, Eugen, Baesens, Bart, & Vanden Broucke, Seppe. (2018). Building profit-sensitive classifiers for maximum profit.

Haupt, J, Stripling, Eugen, Baesens, Bart, Vanden Broucke, Seppe, & Lessmann, S. (2017). Profit-maximizing scorecard development.

PhD Dissertation

Stripling, E. (2018). Business-Oriented Data Analytics: Advances in Profit-Driven Model Building and Fraud Detection.