Graham Mann, Indulis Bernsteins
DIMEA 2007
When the customer churn prediction model is built, a large number of features bring heavy burdens to the model and even decrease the accuracy. This paper is aimed to review the feature selection, to compare the algorithms from different fields and to design a framework of feature selection for customer churn prediction. Based on the framework, the author experiment on the structured module with some telecom operator's marketing data to verify the efficiency of the feature selection framework. ©2009 IEEE.
Graham Mann, Indulis Bernsteins
DIMEA 2007
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