Application of customer churn prediction based on weighted selective ensembles

Customer churn leads to the losses of enterprise. To deal with the customer churn problem of the customer relationship management, this paper set up the model based on the characteristics of amount and imbalance data and verify on the real data of telecom. By comparing with the Bayes, Decision Tree (DT), Artificial Neural Networks (ANN) and Support Vector Machine (SVM), the ensemble learning algorithms have the potential advantages. The effect of ensemble is obvious advantage especially the base classifiers are Support Vector Machines and has better hit rate, lift coefficient and accuracy rate. It can be used as an effective measure for customer churn prediction.