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

Koen De Bock (UGent) and Dirk Van den Poel (UGent)
(2012) EXPERT SYSTEMS WITH APPLICATIONS. 39(8). p.6816-6826
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Keywords
SUPPORT VECTOR MACHINES, KNOWLEDGE DISCOVERY, RANDOM FORESTS, CLASSIFICATION, RETENTION, CLASSIFIERS, SATISFACTION, MANAGEMENT, DEFECTION, DIAGNOSIS, Database marketing, Customer churn prediction, Ensemble classification, Generalized additive models (GAMs), GAMens, Model interpretability

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MLA
De Bock, Koen, and Dirk Van den Poel. “Reconciling Performance and Interpretability in Customer Churn Prediction Using Ensemble Learning Based on Generalized Additive Models.” EXPERT SYSTEMS WITH APPLICATIONS, vol. 39, no. 8, 2012, pp. 6816–26, doi:10.1016/j.eswa.2012.01.014.
APA
De Bock, K., & Van den Poel, D. (2012). Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models. EXPERT SYSTEMS WITH APPLICATIONS, 39(8), 6816–6826. https://doi.org/10.1016/j.eswa.2012.01.014
Chicago author-date
De Bock, Koen, and Dirk Van den Poel. 2012. “Reconciling Performance and Interpretability in Customer Churn Prediction Using Ensemble Learning Based on Generalized Additive Models.” EXPERT SYSTEMS WITH APPLICATIONS 39 (8): 6816–26. https://doi.org/10.1016/j.eswa.2012.01.014.
Chicago author-date (all authors)
De Bock, Koen, and Dirk Van den Poel. 2012. “Reconciling Performance and Interpretability in Customer Churn Prediction Using Ensemble Learning Based on Generalized Additive Models.” EXPERT SYSTEMS WITH APPLICATIONS 39 (8): 6816–6826. doi:10.1016/j.eswa.2012.01.014.
Vancouver
1.
De Bock K, Van den Poel D. Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models. EXPERT SYSTEMS WITH APPLICATIONS. 2012;39(8):6816–26.
IEEE
[1]
K. De Bock and D. Van den Poel, “Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models,” EXPERT SYSTEMS WITH APPLICATIONS, vol. 39, no. 8, pp. 6816–6826, 2012.
@article{2086765,
  author       = {{De Bock, Koen and Van den Poel, Dirk}},
  issn         = {{0957-4174}},
  journal      = {{EXPERT SYSTEMS WITH APPLICATIONS}},
  keywords     = {{SUPPORT VECTOR MACHINES,KNOWLEDGE DISCOVERY,RANDOM FORESTS,CLASSIFICATION,RETENTION,CLASSIFIERS,SATISFACTION,MANAGEMENT,DEFECTION,DIAGNOSIS,Database marketing,Customer churn prediction,Ensemble classification,Generalized additive models (GAMs),GAMens,Model interpretability}},
  language     = {{eng}},
  number       = {{8}},
  pages        = {{6816--6826}},
  title        = {{Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models}},
  url          = {{http://dx.doi.org/10.1016/j.eswa.2012.01.014}},
  volume       = {{39}},
  year         = {{2012}},
}
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