Abstract
In various service-based industries such as telecom industry, life insurance, hospitality, banking, and gaming, Churn Prediction plays an important role. Companies are trying to establish means for predicting potential clients to turnover in the telecom sector. Therefore, it is crucial to identify the factors that rising the churn of customers and take the appropriate steps and reduce the churn. Hence the purpose of our research is to establish the model of churn prediction. The cycle where one user leaves one company and enters another is called churn. This paper would explore how to identify customers who could churn, using machine learning techniques to forecast, and helping to represent large datasets in graph form.
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Mukhopadhyay, D., Malusare, A., Nandanwar, A., Sakshi, S. (2021). An Approach to Mitigate the Risk of Customer Churn Using Machine Learning Algorithms. In: Joshi, A., Khosravy, M., Gupta, N. (eds) Machine Learning for Predictive Analysis. Lecture Notes in Networks and Systems, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-15-7106-0_13
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DOI: https://doi.org/10.1007/978-981-15-7106-0_13
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