Cost-sensitive ensemble learning: a unifying framework von Petrides, George, Verbeke, Wouter

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Fraud analytics using descriptive, predictive, and social network techniques: a guide to data science for fraud detection von Baesens, Bart, Van Vlasselaer, Veronique, Verbeke, Wouter

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A survey and benchmarking study of multitreatment uplift modeling von Olaya, Diego, Coussement, Kristof, Verbeke, Wouter

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Data Mining Techniques for Software Effort Estimation: A Comparative Study von Dejaeger, K., Verbeke, W., Martens, D., Baesens, B.

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A Data-Driven Method for Energy Consumption Prediction and Energy-Efficient Routing of Electric Vehicles in Real-World Conditions von De Cauwer, Cedric, Verbeke, Wouter, Coosemans, Thierry, Faid, Saphir, Van Mierlo, Joeri

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A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models von Verbraken, T., Verbeke, W., Baesens, B.

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Claims fraud detection with uncertain labels von Vandervorst, Félix, Verbeke, Wouter, Verdonck, Tim

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Robust instance-dependent cost-sensitive classification von De Vos, Simon, Vanderschueren, Toon, Verdonck, Tim, Verbeke, Wouter

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A study of the U.S. domestic air transportation network: temporal evolution of network topology and robustness from 2001 to 2016 von Siozos-Rousoulis, Leonidas, Robert, Dimitri, Verbeke, Wouter

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Conventional, Hybrid, or Electric Vehicles: Which Technology for an Urban Distribution Centre? von Verbeke, Wouter, Macharis, Cathy, Van Mierlo, Joeri, De Cauwer, Cedric, Lebeau, Philippe, Coosemans, Thierry

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Treatment effect optimisation in dynamic environments von Berrevoets, Jeroen, Verboven, Sam, Verbeke, Wouter

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Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022 Grenoble, France, September 19-23, 2022, Proceedings Pa...

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Why you should stop predicting customer churn and start using uplift models von Devriendt, Floris, Berrevoets, Jeroen, Verbeke, Wouter

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Cost-sensitive ensemble learning: a unifying framework von Petrides, George, Verbeke, Wouter

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Instance-dependent cost-sensitive learning for detecting transfer fraud von Höppner, Sebastiaan, Baesens, Bart, Verbeke, Wouter, Verdonck, Tim

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Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies von Vanderschueren, Toon, Verdonck, Tim, Baesens, Bart, Verbeke, Wouter

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Fraud analytics: A decade of research von Bockel-Rickermann, Christopher, Verdonck, Tim, Verbeke, Wouter

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Social network analysis for customer churn prediction von Verbeke, Wouter, Martens, David, Baesens, Bart

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Building comprehensible customer churn prediction models with advanced rule induction techniques von Verbeke, Wouter, Martens, David, Mues, Christophe, Baesens, Bart

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Weight-of-evidence through shrinkage and spline binning for interpretable nonlinear classification von Raymaekers, Jakob, Verbeke, Wouter, Verdonck, Tim

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