This is the repository for the paper CloudChurn: A Boosting-Integrated model for Churn Prediction in Cloud Services, which is submitted to KDD 2024 Applied Data Science (ADS) Track.
The data involved in this project has a high level of confidentiality. Even after encryption, it cannot be authorized to be disclosed. Therefore, the project code will only involve the relevant parts of the CloudChurn model.
If you have any problem with our work, please contact Hengyu Ye (cs_22_yhy@sjtu.edu.cn)
This project is supported by Huawei Cloud Computing Technologies Co.
The implement of Transformer Encoder is based on the repo: https://github.com/hyunwoongko/transformer/tree/master