Ghent University Academic Bibliography

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

Koen De Bock (UGent) and Dirk Van den Poel (UGent)

(2011) EXPERT SYSTEMS WITH APPLICATIONS. 38(10). p.12293-12301
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Predicting website audience demographics for web advertising targeting using multi-website clickstream data

Koen De Bock (UGent) and Dirk Van den Poel (UGent)

(2010) FUNDAMENTA INFORMATICAE. 98(1). p.49-70
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Ensemble classification based on generalized additive models

Koen De Bock (UGent) , Kristof Coussement and Dirk Van den Poel (UGent)

(2010) COMPUTATIONAL STATISTICS & DATA ANALYSIS. 54(6). p.1535-1546
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- Miscellaneous
GAMens: Applies GAMens, GAMrsm and GAMbag ensemble classifiers. R Package version 1.11.

Koen De Bock (UGent) , Kristof Coussement and Dirk Van den Poel (UGent)

(2010) R CRAN website.
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- Conference Paper
- P1
- open access
Ensembles of probability estimation trees for customer churn prediction

Koen De Bock (UGent) and Dirk Van den Poel (UGent)

(2010) LECTURE NOTES IN COMPUTER SCIENCE. 6097. p.57-66
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- Conference Paper
- C3
Demographic Classification of Anonymous Web Site Visitors Using Click Stream Information: A Practical Method for Supporting Online Advertising

Koen De Bock (UGent) and Dirk Van den Poel (UGent)

(2009) Proceedings of the 2009 Joint Statistical Meetings (JSM), Session 507.

Academic Bibliography

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

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

Predicting website audience demographics for web advertising targeting using multi-website clickstream data

Ensemble classification based on generalized additive models

GAMens: Applies GAMens, GAMrsm and GAMbag ensemble classifiers. R Package version 1.11.

Ensembles of probability estimation trees for customer churn prediction

Demographic Classification of Anonymous Web Site Visitors Using Click Stream Information: A Practical Method for Supporting Online Advertising

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