Koen W. De Bock

According to our database, Koen W. De Bock authored at least 19 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda.

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

Eur. J. Oper. Res., 2024

Explainable Analytics for Operational Research.

Koen W. De Bock, Kristof Coussement, Arno De Caigny

Eur. J. Oper. Res., 2024

Hybrid black-box classification for customer churn prediction with segmented interpretability analysis.

Arno De Caigny, Koen W. De Bock, Sam Verboven

Decis. Support Syst., 2024

Coupling Neural Networks Between Clusters for Better Personalized Care.

Mathias Kraus, Nico Hambauer, Kristina Müller, Pavlina Kröckel, Nalika Ulapane, Arno De Caigny, Koen W. De Bock, Kristof Coussement

Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

2022

A decision-analytic framework for interpretable recommendation systems with multiple input data sources: a case study for a European e-tailer.

Kristof Coussement, Koen W. De Bock, Stijn Geuens

Ann. Oper. Res., 2022

2021

Targeting customers for profit: An ensemble learning framework to support marketing decision-making.

Stefan Lessmann, Johannes Haupt, Kristof Coussement, Koen W. De Bock

Inf. Sci., 2021

Spline-rule ensemble classifiers with structured sparsity regularization for interpretable customer churn modeling.

Koen W. De Bock, Arno De Caigny

Decis. Support Syst., 2021

2020

Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach.

Koen W. De Bock, Kristof Coussement, Stefan Lessmann

Eur. J. Oper. Res., 2020

Leveraging fine-grained transaction data for customer life event predictions.

Arno De Caigny, Kristof Coussement, Koen W. De Bock

Decis. Support Syst., 2020

2019

Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis.

C. Gary Mena, Arno De Caigny, Kristof Coussement, Koen W. De Bock, Stefan Lessmann

CoRR, 2019

2018

A framework for configuring collaborative filtering-based recommendations derived from purchase data.

Stijn Geuens, Kristof Coussement, Koen W. De Bock

Eur. J. Oper. Res., 2018

A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees.

Arno De Caigny, Kristof Coussement, Koen W. De Bock

Eur. J. Oper. Res., 2018

2017

The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles.

Koen W. De Bock

Expert Syst. Appl., 2017

2015

Maximize What Matters: Predicting Customer Churn With Decision-Centric Ensemble Selection.

Annika Baumann, Stefan Lessmann, Kristof Coussement, Koen W. De Bock

Proceedings of the 23rd European Conference on Information Systems, 2015

2012

Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models.

Koen W. De Bock, Dirk Van den Poel

Expert Syst. Appl., 2012

2011

An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction.

Koen W. De Bock, Dirk Van den Poel

Expert Syst. Appl., 2011

2010

Predicting Website Audience Demographics forWeb Advertising Targeting Using Multi-Website Clickstream Data.

Koen W. De Bock, Dirk Van den Poel

Fundam. Informaticae, 2010

Ensemble classification based on generalized additive models.

Koen W. De Bock, Kristof Coussement, Dirk Van den Poel

Comput. Stat. Data Anal., 2010

Ensembles of Probability Estimation Trees for Customer Churn Prediction.

Koen W. De Bock, Dirk Van den Poel

Proceedings of the Trends in Applied Intelligent Systems, 2010