针对不平衡数据集的客户流失预测算法

The Unbalance Dataset Analysis Algorithm in Customer Churn Prediction

针对客户关系管理中的客户流失预测问题进行探讨,通过对客户流失数据特点的分析,以及现有预测算法的比较,将数据挖掘方法中的随机森林算法引入客户流失预测,建立预测模型,并在实际的银行业贷款客户数据集上进行实验,得到了较好的效果。

This paper focuses on the customer churn prediction in the field of customer relationship management. Based on the characteristics of customer churn data and the comparison of the current prediction algorithms, we introduce random forests algorithm, a new data mining method, into the customer churn prediction and build a prediction model. Applied to a credit debt customer database of a commercial bank, the model is proved to be effective in classifying the churn customers from the loan data.