A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy

Owing to saturated markets, fierce competition, dynamic criteria, along with introduction of new attractive offers, the considerable issue customer churn was faced by telecommunication industry. Thus, an efficient Churn Prediction (CP) model is required for monitoring churn. Therefore, this work proposes a novel framework predict through deep learning namely Swish Recurrent Neural Network (S-RNN). Finally, SRNN adapted classify Customer (CC) and normal customer. If result customer, network utilisation history analysed retention process. Whereas, number customers based on area usage not recognised in frameworkOwing S-RNN