Title :
The Explanation of Support Vector Machine in Customer Churn Prediction
Author :
Li Yi ; Xia Guo-en
Author_Institution :
Comput. Sch., Wuhan Univ., Wuhan, China
Abstract :
In this paper, an explainable prediction model is established to select the optimum features and parameters, then the selected optimum parameters are applied to predicting potential customer churning in one foreign telecom company, discovering that the model not only achieves a desirable prediction but is also explainable through selected features, and that a balanced relation between accuracy and explaining of customer churn prediction model as well as that a unified structural frame for customer churn prediction model is thus established.
Keywords :
customer relationship management; support vector machines; customer churn prediction; features selection; foreign telecom company; optimum parameter; potential customer churning; prediction model; support vector machine; unified structural frame; Accuracy; Biological system modeling; Data models; Mathematical model; Prediction algorithms; Predictive models; Support vector machines;
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
DOI :
10.1109/ICEEE.2010.5660501