This is the code for the paper entitled "An Adaptive Ensemble Framework for Addressing Concept Drift in IoT Data Streams"
Authors: Yafeng Wu([email protected]), Lan Liu([email protected]), Yongjie Yu([email protected]), Guiming Chen([email protected]), Junhan Hu([email protected])
Organization: Guangdong Polytechnic Normal University, Guangzhou, China
- AEWAE+CICIDS2017.ipynb: code for the sampled CICIDS2017 dataset.
- AEWAE+NSL-KDD.ipynb: code for the sampled NSL-KDD dataset.
- AEWAE+IoTID20.ipynb: code for the sampled IoTID20 dataset.
- Python 3.6+
- Scikit-learn
- River
If you find this repository useful in your research, please cite this article as:
Wu, Yafeng; Liu, Lan; Yu, Yongjie; Chen, Guiming; Hu, Junhan (2023). An Adaptive Ensemble Framework for Addressing Concept Drift in IoT Data Streams. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.23304461.v1
@article{wu2023adaptive,
title={An Adaptive Ensemble Framework for Addressing Concept Drift in IoT Data Streams},
author={Wu, Yafeng and Liu, Lan and Yu, Yongjie and Chen, Guiming and Hu, Junhan},
year={2023},
publisher={TechRxiv}
}