ChOracle: A Unified Statistical Framework for Churn Prediction-Reference-Cited by-同舟云学术

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ChOracle: A Unified Statistical Framework for Churn Prediction

Published:2020 Issue: Volume: Page:1-1
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Khodadadi Ali,Hosseini Seyedabbas,Pajouheshgar Ehsan,Mansouri Farnam,Rabiee Hamid R.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/4358933/09109662.pdf?arnumber=9109662

Cited by 10 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. AI-based early detection to prevent user churn in MMORPG;Korean Journal of Applied Statistics;2024-08-31

2. A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners;IEEE Access;2024

3. Customer churn prediction model in cloud environment using DFE-WUNB: ANN deep feature extraction with Weight Updated Tuned Naïve Bayes classification with Block-Jacobi SVD dimensionality reduction;Engineering Applications of Artificial Intelligence;2023-11

4. Predicting Churn in Online Games by Quantifying Diversity of Engagement;Big Data;2023-08-01

5. A Machine Learning Model for Customer Churn Prediction using CatBoost Classifier;2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS);2023-05-17

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