Eugen Stripling
Katholieke Universiteit Leuven
6 Papers
3 Citations
Eugen Stripling is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Profit maximization & Computer science. The author has an hindex of 4, co-authored 6 publications.
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Papers
Profit maximizing logistic model for customer churn prediction using genetic algorithms
Eugen Stripling,Seppe vanden Broucke,Katrien Antonio,Katrien Antonio,Bart Baesens,Bart Baesens,Monique Snoeck +6 more
TL;DR: A classifier is presented that maximizes the EMPC in the training step using a genetic algorithm, where ProfLogit's interior model structure resembles a lasso-regularized logistic model, and it exhibits the overall highest, out-of-sample EMPC performance as well as the overall best, profit-based precision and recall values.
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Profit driven decision trees for churn prediction
Sebastiaan Höppner,Eugen Stripling,Bart Baesens,Bart Baesens,Seppe vanden Broucke,Tim Verdonck +5 more
TL;DR: In this article, a new classifier that integrates the EMPC metric directly into the model construction is presented, called ProfTree, which uses an evolutionary algorithm for learning profit driven decision trees.
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•Posted Content
Profit Driven Decision Trees for Churn Prediction
Sebastiaan Höppner,Eugen Stripling,Bart Baesens,Bart Baesens,Seppe vanden Broucke,Tim Verdonck +5 more
TL;DR: In this paper, a new classifier that integrates the EMPC metric directly into the model construction is presented, called ProfTree, which uses an evolutionary algorithm for learning profit driven decision trees.
Isolation-based conditional anomaly detection on mixed-attribute data to uncover workers' compensation fraud
Eugen Stripling,Bart Baesens,Bart Baesens,Barak Chizi,Seppe vanden Broucke +4 more
- 01 Jul 2018
TL;DR: This work proposes the i Forest CAD approach that computes conditional anomaly scores, useful for fraud detection, and presents a case study in which the usefulness of the proposed approach is demonstrated on real-world workers' compensation claims received from a large European insurance organization.
Profit maximizing logistic regression modeling for customer churn prediction
Eugen Stripling,Seppe vanden Broucke,Katrien Antonio,Bart Baesens,Monique Snoeck +4 more
- 01 Oct 2015
TL;DR: This work introduces a classifier that incorporates the expected maximum profit metric in the construction of a classification model, called ProfLogit, which explicitly takes profit maximization concerns into account during the training step, rather than the evaluation step.
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