93 citations · 195 across the 11 of their papers we have counts for
5 papers · 1 filter
Response Transformation and Profit Decomposition for Revenue Uplift Modeling
Robin M. Gubela, Stefan Lessmann, Szymon Jaroszewicz
Uplift models support decision-making in marketing campaign planning. Estimating the causal effect of a marketing treatment, an uplift model facilitates targeting communication to…
Affordable Uplift: Supervised Randomization in Controlled Experiments
Johannes Haupt, Daniel Jacob, Robin M. Gubela +1
Customer scoring models are the core of scalable direct marketing. Uplift models provide an estimate of the incremental benefit from a treatment that is used for operational decisi…
Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis
C. Gary Mena, Arno De Caigny, Kristof Coussement +2
Off-the-shelf machine learning algorithms for prediction such as regularized logistic regression cannot exploit the information of time-varying features without previously using an…
Shallow Self-Learning for Reject Inference in Credit Scoring
Nikita Kozodoi, Panagiotis Katsas, Stefan Lessmann +2
Credit scoring models support loan approval decisions in the financial services industry. Lenders train these models on data from previously granted credit applications, where the…
Evaluating software defect prediction performance: an updated benchmarking study
Libo Li, Stefan Lessmann, Bart Baesens
Accurately predicting faulty software units helps practitioners target faulty units and prioritize their efforts to maintain software quality. Prior studies use machine-learning mo…