Customer attrition in retailing: An application of Multivariate Adaptive Regression Splines

作者：

Highlights：

• We propose a model for partial churn prediction in retailing.

• We use Logistic regression and Multivariate Adaptive Regression Splines as classifiers.

• We compare the performance of MARS with Logistic regression.

• We consider Logistic regression combined with stepwise feature selection.

• Stepwise feature selection approach outperforms MARS.

摘要

•We propose a model for partial churn prediction in retailing.•We use Logistic regression and Multivariate Adaptive Regression Splines as classifiers.•We compare the performance of MARS with Logistic regression.•We consider Logistic regression combined with stepwise feature selection.•Stepwise feature selection approach outperforms MARS.

论文关键词：Marketing,Customer relationship management,Churn analysis,Retailing,Classification,Logistic regression,Multivariate Adaptive Regression Splines

论文评审过程：Available online 7 June 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.05.069