Remora Optimization with Machine Learning Driven Churn Prediction for Business Improvement-Reference-Cited by-同舟云学术

Remora Optimization with Machine Learning Driven Churn Prediction for Business Improvement

Published:2023-01-05 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)
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Author:

Kumar Sumita¹,Baruah Pallavi²,Kirubakaran S³,Kumar A. Sasi⁴,Singh Kamlesh⁵,Reddy M V Jagannatha⁶

Affiliation:

1. Bharati vidyapeeth (Deemed to be University),Department of Engineering and Technology,Navi Mumbai,India

2. University of Science and Technology,Department of Computer Science and Electronics,Meghalaya,India

3. CMR college of Engineering and Technology, Kandlakoya,Department of CSE,Hyderabad,Telangana,India

4. Institute of Engineering & Technology, Srinivas University,Mentor-IT – Inurture Education Solutions Pvt Ltd, Bangalore,Department of Cloud Technology & Data Science,Srinivas Nagar, Mukka, Surathkal, Mangalore, Dakshina Kannada,Karnataka,India

5. Graphic Era Hill University,Department of Computer Science and Engineering,Dehradun,India

6. Gandhi Institute of Technology and Management (GITAM Deemed to be University),Department of CSE,Doddaballapura,Karnataka,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10053371/10052779/10053554.pdf?arnumber=10053554

Reference18 articles.

1. Machine Learning and Neural Network Models for Customer Churn Prediction in Banking and Telecom Sectors

2. Machine Learning to Develop Credit Card Customer Churn Prediction

3. Telecom Churn Prediction System Based on Ensemble Learning Using Feature Grouping

4. Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms

5. Model Optimization Analysis of Customer Churn Prediction Using Machine Learning Algorithms with Focus on Feature Reductions