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2020 – today
- 2024
[j16]C. Gary Mena, Kristof Coussement, Koen W. De Bock, Arno De Caigny, Stefan Lessmann
:
Exploiting time-varying RFM measures for customer churn prediction with deep neural networks. Ann. Oper. Res. 339(1-2): 765-787 (2024)- [j15]Arno De Caigny, Koen W. De Bock, Sam Verboven:
Hybrid black-box classification for customer churn prediction with segmented interpretability analysis. Decis. Support Syst. 181: 114217 (2024) - [j14]Koen W. De Bock, Kristof Coussement, Arno De Caigny:
Explainable Analytics for Operational Research. Eur. J. Oper. Res. 317(2): 243-248 (2024) - [j13]Koen W. De Bock, Kristof Coussement, Arno De Caigny, Roman Slowinski, Bart Baesens, Robert N. Boute, Tsan-Ming Choi, Dursun Delen, Mathias Kraus, Stefan Lessmann, Sebastián Maldonado, David Martens, María Óskarsdóttir, Carla Vairetti, Wouter Verbeke, Richard Weber:
Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda. Eur. J. Oper. Res. 317(2): 249-272 (2024) - [c3]Mathias Kraus, Nico Hambauer, Kristina Müller, Pavlina Kröckel, Nalika Ulapane, Arno De Caigny, Koen W. De Bock, Kristof Coussement:
Coupling Neural Networks Between Clusters for Better Personalized Care. HICSS 2024: 3627-3636 - 2022
- [j12]Kristof Coussement, Koen W. De Bock, Stijn Geuens:
A decision-analytic framework for interpretable recommendation systems with multiple input data sources: a case study for a European e-tailer. Ann. Oper. Res. 315(2): 671-694 (2022) - 2021
- [j11]Koen W. De Bock, Arno De Caigny:
Spline-rule ensemble classifiers with structured sparsity regularization for interpretable customer churn modeling. Decis. Support Syst. 150: 113523 (2021) - [j10]Stefan Lessmann, Johannes Haupt, Kristof Coussement, Koen W. De Bock:
Targeting customers for profit: An ensemble learning framework to support marketing decision-making. Inf. Sci. 557: 286-301 (2021) - 2020
- [j9]Arno De Caigny, Kristof Coussement, Koen W. De Bock:
Leveraging fine-grained transaction data for customer life event predictions. Decis. Support Syst. 130: 113232 (2020) - [j8]Koen W. De Bock, Kristof Coussement, Stefan Lessmann:
Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach. Eur. J. Oper. Res. 285(2): 612-630 (2020)
2010 – 2019
- 2019
- [i1]C. Gary Mena, Arno De Caigny, Kristof Coussement, Koen W. De Bock, Stefan Lessmann:
Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis. CoRR abs/1909.11114 (2019) - 2018
- [j7]Stijn Geuens, Kristof Coussement, Koen W. De Bock:
A framework for configuring collaborative filtering-based recommendations derived from purchase data. Eur. J. Oper. Res. 265(1): 208-218 (2018) - [j6]Arno De Caigny, Kristof Coussement, Koen W. De Bock:
A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees. Eur. J. Oper. Res. 269(2): 760-772 (2018) - 2017
- [j5]Koen W. De Bock:
The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles. Expert Syst. Appl. 90: 23-39 (2017) - 2015
- [c2]Annika Baumann, Stefan Lessmann, Kristof Coussement, Koen W. De Bock:
Maximize What Matters: Predicting Customer Churn With Decision-Centric Ensemble Selection. ECIS 2015 - 2012
- [j4]Koen W. De Bock, Dirk Van den Poel:
Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models. Expert Syst. Appl. 39(8): 6816-6826 (2012) - 2011
- [j3]Koen W. De Bock, Dirk Van den Poel:
An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction. Expert Syst. Appl. 38(10): 12293-12301 (2011) - 2010
- [j2]Koen W. De Bock, Kristof Coussement, Dirk Van den Poel:
Ensemble classification based on generalized additive models. Comput. Stat. Data Anal. 54(6): 1535-1546 (2010) - [j1]Koen W. De Bock, Dirk Van den Poel:
Predicting Website Audience Demographics forWeb Advertising Targeting Using Multi-Website Clickstream Data. Fundam. Informaticae 98(1): 49-70 (2010) - [c1]Koen W. De Bock, Dirk Van den Poel:
Ensembles of Probability Estimation Trees for Customer Churn Prediction. IEA/AIE (2) 2010: 57-66
Coauthor Index
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