An Enhanced Bank Customers Churn Prediction Model Using A Hybrid Genetic Algorithm And K-Means Filter And Artificial Neural Network
2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)(2021)
Abstract
Customer churn prediction is an important issue in banking industry and has gained attention over the years. Early identification of customers likely to leave a bank is vital in order to retain such customers. Predicting churning is a data mining tasks that require several data mining approaches. Churn prediction based on Artificial Neural Networks (ANNs) have been successful, however, they are af...
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Key words
Training,Filtering,Training data,Artificial neural networks,Filtering algorithms,Predictive models,Data models
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