An Enhanced Bank Customers Churn Prediction Model Using A Hybrid Genetic Algorithm And K-Means Filter And Artificial Neural Network-Reference-Cited by-同舟云学术

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An Enhanced Bank Customers Churn Prediction Model Using A Hybrid Genetic Algorithm And K-Means Filter And Artificial Neural Network

Published:2021-02-23 Issue: Volume: Page:
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Container-title:2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)
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Author:

Yahaya R.,Abisoye O. A.,Bashir S. A.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9428727/9428791/09428805.pdf?arnumber=9428805

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparative Study of Bank Customers Churn Prediction using AI/ML;2024 IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT);2024-04-06

2. Churn Prediction using Various Machine Learning Algorithms;International Journal of Advanced Research in Science, Communication and Technology;2022-12-13

3. Analysis of ensemble classifiers for bank churn prediction;2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS);2022-11-04

4. Prediction of Churning behavior in Telecom using Machine Learning;2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon);2022-10-16

5. Detecting the Risk of Customer Churn in Telecom Sector: A Comparative Study;Mathematical Problems in Engineering;2022-07-18

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