Three Categories Customer Churn Prediction Based on the Adjusted Real Adaboost

摘要

It is necessary for enterprises to establish a customer churn management system. In this article, we take the heterogeneity into consideration and divide the churn people into two classes according to the data characteristics. Moreover, we try to modify the bias of multi-class unbalanced data classification. Then we propose a new method based on Real Adaboost for the problem. The proposed method takes the within-group error into consideration and creates another view of reweighing the cases. Empirical study on our sample data shows that the new method performs better than the other method.