Abstract
Predicting client churn in telecommunication industries becomes the most significant topic for analysis in recent years. Because its helps in detecting which customer are likely to change or cancel their subscription to a service. Analysis of information that is extracted from telecommunication companies will help to seek out the explanations of client churn and also uses the knowledge to retain the purchasers. Thus, predicting churn is extremely necessary for telecommunication firms to retain their customers. During this paper, we have designed the classification model using call tree, evaluated the performance measures, and compared its performance with logistic regression model.
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Rai, S., Khandelwal, N., Boghey, R. (2020). Analysis of Customer Churn Prediction in Telecom Sector Using CART Algorithm. In: Luhach, A., Kosa, J., Poonia, R., Gao, XZ., Singh, D. (eds) First International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-15-0029-9_36
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