Gaining insight into student satisfaction using comprehensible data mining techniques
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Other versions of this item:
- Dejaeger, Karel & Goethals, Frank & Giangreco, Antonio & Mola, Lapo & Baesens, Bart, 2012. "Gaining insight into student satisfaction using comprehensible data mining techniques," European Journal of Operational Research, Elsevier, vol. 218(2), pages 548-562.
References listed on IDEAS
- Martens, David & Baesens, Bart & Van Gestel, Tony & Vanthienen, Jan, 2007. "Comprehensible credit scoring models using rule extraction from support vector machines," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1466-1476, December.
- A. Giangreco & A. Sebastiano & R. Peccei, 2009. "Trainees' reactions to training: an analysis of the factors affecting overall satisfaction with training," Post-Print hal-00323772, HAL.
- Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
- Bart Baesens & Rudy Setiono & Christophe Mues & Jan Vanthienen, 2003. "Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation," Management Science, INFORMS, vol. 49(3), pages 312-329, March.
- A. Giangreco & A. Carugati & A. Sebastiano & D. Della Bella, 2010. "Trainees' reactions to training : shaping groups and courses for happier trainees," Post-Print hal-00569508, HAL.
- A. Giangreco & A. Carugati & A. Sebastiano, 2010. "Are we doing the right thing ? Food for thought on training evaluation and its context," Post-Print hal-00569308, HAL.
- repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
- Altman, Edward I. & Rijken, Herbert A., 2004. "How rating agencies achieve rating stability," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2679-2714, November.
- M. Ruth & K. Donaghy & P. Kirshen, 2006. "Introduction," Chapters,in: Regional Climate Change and Variability, chapter 1 Edward Elgar Publishing.
- Verbeke, Wouter & Dejaeger, Karel & Martens, David & Hur, Joon & Baesens, Bart, 2012. "New insights into churn prediction in the telecommunication sector: A profit driven data mining approach," European Journal of Operational Research, Elsevier, vol. 218(1), pages 211-229.
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- repec:spr:infosf:v:20:y:2018:i:2:d:10.1007_s10796-016-9704-4 is not listed on IDEAS
- Asil Oztekin, 0. "Information fusion-based meta-classification predictive modeling for ETF performance," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
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