Western-OC2-Lab / PWPAE-Concept-Drift-Detection-and-Adaptation

Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" published in IEEE GlobeCom 2021.

Date Created 2021-08-16 (3 years ago)

Commits 33 (last one about a year ago)

Stargazers 207 (1 this week)

Watchers 21 (0 this week)

Forks 44

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RepositoryStats indexes 595,856 repositories, of these Western-OC2-Lab/PWPAE-Concept-Drift-Detection-and-Adaptation is ranked #176,658 (70th percentile) for total stargazers, and #105,912 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #4,053/17,543.

Western-OC2-Lab/PWPAE-Concept-Drift-Detection-and-Adaptation is also tagged with popular topics, for these it's ranked: machine-learning (#3,300/8063), iot (#489/1170), anomaly-detection (#110/336)

All Topics

iot drift lightgbm cicids2017 data-stream concept-drift streaming-data change-detector drift-detection online-learning machine-learning adaptive-learning anomaly-detection ensemble-learning iot-data-analytics real-time-analytics intrusion-detection-system

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The only known language in this repository is Jupyter Notebook

updated: 2024-12-19 @ 03:05am, id: 396987143 / R_kgDOF6mLBw