Study of telecom customer churn prediction based on cost sensitive SVM
基于代价敏感SVM的电信客户流失预测研究*

To deal with the problem of unbalanced data classification and asymmetry misclassification cost in customer churn prediction,applied cost sensitive learning to the improved SVM which Veropoulos suggested it could handle the problem unbalanced data classification well to the model of customer churn prediction. The cost sensitive SVM was compared with traditional SVM, C4.5 and ANN through real telecom customer churn data. And found that it has a distinct improvement in accuracy rate, hit rate, covering rate and lift coefficient. It can be used as an effective measure for customer churn prediction.