Customer Churn Prediction in the Telecom Sector with Machine Learning and Adaptive k-Means Cluster using Imbalance Data-Reference-Cited by-同舟云学术

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Customer Churn Prediction in the Telecom Sector with Machine Learning and Adaptive k-Means Cluster using Imbalance Data

Published:2024-03-15 Issue: Volume:11 Page:1-5
ISSN:
Container-title:2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT)
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Author:

Aravinda N L¹,Reddy R Archana²,Dhandayuthapani V Bala³,Nayak Jithendra P R⁴,Husseen Ahmad⁵

Affiliation:

1. Mallareddy Engineering College for Women (Autonomous) Hyderabad,Electronics and Communication Engineering Department,Telangana,India

2. School of Computer Science and Engineering SR University Warangal,Telangana,India

3. University of Technology and Applied Sciences Shinas branch,Department of IT College of Computing and Information Sciences,Oman

4. Srinivas Institute of Technology Valachil,Department of CSE,Mangalore,India

5. The Islamic university Najaf,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10515307/10515308/10515832.pdf?arnumber=10515832

Reference13 articles.

1. Customer churning analysis using machine learning algorithms

2. Feature Selection Using Selective Opposition Based Artificial Rabbits Optimization for Arrhythmia Classification on Internet of Medical Things Environment

3. ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry

4. Defining Traffic States using Spatio-temporal Traffic Graphs

5. Customer Churn Detection for insurance data using Blended Logistic Regression Decision Tree Algorithm (BLRDT);Jajam;International Journal of Intelligent Systems and Applications in Engineering,2023

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