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Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models
De Bock, Koen W.; Van den Poel, Dirk - 2012
Persistent link: https://www.econbiz.de/10009665069
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A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees
Caigny, Arno de; Coussement, Kristof; De Bock, Koen W. - In: European journal of operational research : EJOR 269 (2018) 2, pp. 760-772
Persistent link: https://www.econbiz.de/10011864442
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Cost-sensitive business failure prediction when misclassification costs are uncertain : a heterogeneous ensemble selection approach
De Bock, Koen W.; Coussement, Kristof; Lessmann, Stefan - In: European journal of operational research : EJOR 285 (2020) 2, pp. 612-630
Persistent link: https://www.econbiz.de/10012239630
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Incorporating textual information in customer churn prediction models based on a convolutional neural network
Caigny, Arno de; Coussement, Kristof; De Bock, Koen W.; … - In: International journal of forecasting 36 (2020) 4, pp. 1563-1578
Persistent link: https://www.econbiz.de/10012547130
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Explainable profit-driven hotel booking cancellation prediction based on heterogeneous stacking-based ensemble classification
Liu, Zhenkun; De Bock, Koen W.; Zhang, Lifang - In: European journal of operational research : EJOR 321 (2025) 1, pp. 284-301
Persistent link: https://www.econbiz.de/10015094978
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Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction
Liu, Zhenkun; Jiang, Ping; De Bock, Koen W.; Wang, Jianzhou - In: Technological forecasting and social change : an … 198 (2024), pp. 1-16
Persistent link: https://www.econbiz.de/10015076450