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| A Study on Prediction of Telecom Customer Churn Based on Dynamic Selection,
Optimization and Integration of Cost Sensitivity |
| LUO Ban, SHAO Pei-Ji, XIA Guo-En |
| 1. University of Electronic Science and Technology of China, Chengdu, China;
2. Guangxi University of Finance and Economics, Nanning, China |
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Abstract On account that the different samples have the prediction complementarities between different section characters and different classification algorithms in feature space and based on the theory of Telecom customer churn prediction, this paper established the profits functions to predict Telecom customer churn integrating multiclassifiers, and a new customer churn prediction model is put forward in Telecom based on the dynamic selection and optimizing integrating of cost sensitivity. Firstly, the training set samples are clustered into multiple subareas by using Kmeans clustering algorithm. Then, the customer churn prediction subclassifiers are established based on the samples in the subareas by using NaiveBayes Algorithm, Multilayer Perceptron and J48 Algorithm, respectively. Finally, the subarea subclassifiers are integrated and optimized by use of the Improved Artificial Fishschool Algorithm（IAFSA）. The experiment results show that the classifying performance of the model based on the dynamic integration of multiclassifiers and optimizing integrating of cost sensitivity not only excels the three single model constructed based on the whole samples, but also excels the model integrating of the three single model by IAFSA.
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Received: 29 January 2010
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2012, Vol. 9 
