Bagging and Boosting Classification Trees to Predict Churn

By Aurélie Lemmens, Christophe Croux. 2006

426 citations recorded by the source corpus.

Subfields: Marketing, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/40df978f0a0148ddd78b843762fc6a68be5092d3

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Citations in the corpus

Optimization of Tree Ensembles (2017, background): “…of application areas; examples include chemistry (Svetnik et al. 2003), genomics (D´ıaz-Uriarte and De Andres 2006), ecology (Elith et al. 2008, Cutler et al. 2007), economics (Varian 2014, Bajari et al. 2015), marketing (Lemmens and Croux 2006) and operations management (Ferreira et al. 2015).”
Customer Equity: Measurement, Management and Research Opportunities (2007, positive): “Lemmens and Croux (2006) show that when these models are used they can significantly improve the predictive accuracy of a simple binary choice model.”
Customer churn prediction using improved balanced random forests (2009, neutral): “…algorithms, such as sequential patterns (Chiang, Wang, Lee, & Lin, 2003), genetic modeling (Eiben, Koudijs, & Slisser, 1998), classification trees (Lemmens & Croux, 2003), neural networks (Mozer, Wolniewicz, Grimes, Johnson, & Kaushansky, 2000), and SVM (Zhao, Li, Li, Liu, & Ren, 2005), have been…”
A comparison of machine learning techniques for customer churn prediction (2015, background): “Boosting has been successfully applied to the prediction of customer churn in retail [36] and telecommunications companies [37].”
Market Segmentation Trees (2019, background): “Lemmens and Croux (2006) uses classification trees to predict customer churn.”
Differential Privacy in Telco Big Data Platform (2015, background): “Although RF often achieves a better prediction performance [16, 26, 12], it is still necessary to analyze the effectiveness of DP techniques for DTs.”
Customer Metrics and Their Impact on Financial Performance (2006, neutral): “Li et al. (2005) used latent dimension of Kamakura et al.”
A comparative analysis of machine learning techniques for student retention management (2010, background): “…toxic augite. owned research company, Knowledge Based Systems Inc., in College Station, Texas, as a research scientist for five years, during which he led a number of decision support and other information systems related research projects funded by federal agencies such as DoD, NASA, NIST and DOE.”
Modeling CLV: A test of competing models in the insurance industry (2007, background): “5) (Lemmens and Croux 2006); duration models for a customer’s relationship duration (1.”
New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2012, methodology): “Numerous classification techniques have been adopted for churn prediction, including traditional statistical methods such as logistic regression (Lemmens and Croux, 2006; Neslin et al., 2006; Burez and Van den Poel, 2009), non-parametric statistical models like for instance k-nearest neighbor…”