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Arno De Caigny
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A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees
A De Caigny, K Coussement, KW De Bock
European Journal of Operational Research 269 (2), 760-772, 2018
5222018
Predicting student dropout in subscription-based online learning environments: The beneficial impact of the logit leaf model
K Coussement, M Phan, A De Caigny, DF Benoit, A Raes
Decision Support Systems 135, 113325, 2020
1292020
Incorporating textual information in customer churn prediction models based on a convolutional neural network
A De Caigny, K Coussement, KW De Bock, S Lessmann
International Journal of Forecasting 36 (4), 1563-1578, 2020
1242020
Churn prediction with sequential data and deep neural networks. a comparative analysis
CG Mena, A De Caigny, K Coussement, KW De Bock, S Lessmann
arXiv preprint arXiv:1909.11114, 2019
352019
Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach
A De Caigny, K Coussement, W Verbeke, K Idbenjra, M Phan
Industrial Marketing Management 99, 28-39, 2021
322021
Spline-rule ensemble classifiers with structured sparsity regularization for interpretable customer churn modeling
KW De Bock, A De Caigny
Decision Support Systems 150, 113523, 2021
312021
Extending business failure prediction models with textual website content using deep learning
P Borchert, K Coussement, A De Caigny, J De Weerdt
European Journal of Operational Research 306 (1), 348-357, 2023
272023
Leveraging fine-grained transaction data for customer life event predictions
A De Caigny, K Coussement, KW De Bock
Decision Support Systems 130, 113232, 2020
272020
Explainable AI for operational research: A defining framework, methods, applications, and a research agenda
KW De Bock, K Coussement, A De Caigny, R Slowiński, B Baesens, ...
European Journal of Operational Research, 2023
142023
Exploiting time-varying RFM measures for customer churn prediction with deep neural networks
G Mena, K Coussement, KW De Bock, A De Caigny, S Lessmann
Annals of Operations Research, 1-23, 2023
92023
Does it pay off to communicate like your online community? Evaluating the effect of content and linguistic style similarity on B2B brand engagement
M Meire, K Coussement, A De Caigny, S Hoornaert
Industrial Marketing Management 106, 292-307, 2022
92022
A decision support framework to incorporate textual data for early student dropout prediction in higher education
M Phan, A De Caigny, K Coussement
Decision Support Systems 168, 113940, 2023
82023
Do the US president's tweets better predict oil prices? An empirical examination using long short-term memory networks
S Beyer Díaz, K Coussement, A De Caigny, LF Pérez, S Creemers
International Journal of Production Research 62 (6), 2158-2175, 2024
42024
Investigating the beneficial impact of segmentation-based modelling for credit scoring
K Idbenjra, K Coussement, A De Caigny
Decision Support Systems 179, 114170, 2024
12024
Coupling Neural Networks Between Clusters for Better Personalized Care
M Kraus, N Hambauer, K Müller, P Kröckel, N Ulapane, A De Caigny, ...
12024
Industry-sensitive language modeling for business
P Borchert, K Coussement, J De Weerdt, A De Caigny
European Journal of Operational Research 315 (2), 691-702, 2024
2024
Hybrid black-box classification for customer churn prediction with segmented interpretability analysis
A De Caigny, KW De Bock, S Verboven
Decision Support Systems, 114217, 2024
2024
Explainable analytics for operational research
K de Bock, K Coussement, A De Caigny
European Journal of Operational Research, 2024
2024
CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation
P Borchert, J De Weerdt, K Coussement, A De Caigny, MF Moens
arXiv preprint arXiv:2310.12024, 2023
2023
Towards more inclusive fan engagement
A De Caigny
IESEG School of Management, France, 2023
2023
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