移动客户流失分析系统在数据挖掘的基础上，实现了客户流失模型的管理应用。
The analysis system of subscriber churn in wireless carriers was constructed based on data mining.
通过在客户流失模型中包含这种信息，公司可以在出现客户不满的最初迹象时及时采取措施。
By including this in the churn model, the company could then set up processes to trigger immediate action at the first sign of customer discontent.
客户流失模型是通过对流失客户的数据进行分析后得出的，包括基本模型和行为模型。
Customer churn model, consists of basic model and behavioral model, is built based on analysis of the churned customers' basic data and behavioral history.
接着在前面的基础上又介绍了电信行业客户流失模型建立的原则，探讨了数据挖掘过程的标准化模型。
Then, this paper describes the principles of establishing the model of the telecom industry customer churn, and discusses the standard data mining process.
如果一个模型只用一个流失率，那就是它假设客户关系的生命周期中流失率不变。
If the model USES only one churn rate, the assumption is that the churn rate is constant across the life of the customer relationship.
通过尽早发现不满意的客户，减少客户流失：电信行业的公司已经为防止客户流失建立了详细的预测分析模型。
Reduce customer churn by identifying unhappy customers as early as possible: Companies in the telecommunication sector already have elaborate predictive analytic models for customer churn.
并将CRM中关于客户关系的理念应用到数据仓库中，提出了如交叉销售、风险客户、客户流失等数据模型。
Furthermore, the concept of customer relationship in CRM is applied into data warehouse, and build the models of overlapped sales, risking customer and customer losing.
最后利用训练后的模型对每个客户的流失可能性进行预测以及生成公司可能流失的客户列表。
At last, this paper succeeds to establish customer churn prediction model, gets the churn probability of each customer, and produces a possible churn customers' list.
其次，重点设计了保险公司的客户流失预测模型。
Second, the focus on the design of the insurance company's customer churn prediction models.
该文提出了支持挖掘模型交换和移动通信客户流失分析的决策树算法框架。
This paper proposes a framework for decision tree construction algorithms that supports both model exchange and mobile communication churn analysis.
CIAS的商业逻辑层包括交叉销售、客户响应、客户细分、客户流失、客户利润，五个商业模型。
The business rules level of CIAS consists of five kinds of business models: cross selling, customer responsibility, customer segmentation, customer churn, customer profitability.
分析和预测模型可以识别客户流失的驱动因素，优化配置资源，以及指示对高风险、高价值客户的联系策略。
Analytics and predictive modeling can help to identify drivers of churn, prioritize resources and alert contact strategy for customers that are both high-risk and high-value.
提出了一种基于神经网络的客户流失预测模型。
A customer churn prediction model based on neural network was put forward.
最后利用训练后的模型对每个客户的流失可能性进行预测以及生成公司可能流失的客户规则。
At last, this paper succeeds to establish customer churn prediction model, and generate the rule of the customers which may loss.
最后，为了更加深入的探讨流失预警模型，本文还采用逻辑回归模型建立了客户流失预警模型。
Finally, in order to understand this issue more deeply, we also build churn prediction model with Logistic regression model.
最后，为了更加深入的探讨流失预警模型，本文还采用逻辑回归模型建立了客户流失预警模型。
Finally, in order to understand this issue more deeply, we also build churn prediction model with Logistic regression model.
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