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 201 (0 this week)

Watchers 20 (0 this week)

Forks 45

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RepositoryStats indexes 564,918 repositories, of these Western-OC2-Lab/PWPAE-Concept-Drift-Detection-and-Adaptation is ranked #174,138 (69th percentile) for total stargazers, and #109,685 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #3,937/16,265.

Western-OC2-Lab/PWPAE-Concept-Drift-Detection-and-Adaptation is also tagged with popular topics, for these it's ranked: machine-learning (#3,231/7699), iot (#479/1131), anomaly-detection (#108/308)

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: 2024-09-21 @ 11:27pm, id: 396987143 / R_kgDOF6mLBw