Support Vector Machine and Its Application in Customer Churn Prediction
SVM方法及其在客户流失预测中的应用研究

Customer churn analysis and prediction play an important role in customer relationship management and improve benefit of enterprise.A Support Vector Machine model is established to predict customer churn.Customer churn characteristic is presented in this paper.According to the churn data which is large scale and imbalance,this paper presents a two-class model based on improved SVM to predict customer churn.The class weighted SVM model CW-SVM is presented,and the accuracy is improved by adjusting the class weight and the position of boundary.The efficiency is improved by translating the SVM to the Core Vector Machine and a new algorithms CWC-SVM is presented.The arithmetic performance is better than others based on the test of real credit debt data set in the commercial bank.