Ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Autogluon | 7,205 |  | 14 | a month ago | 1,168 | December 10, 2023 | 299 | apache-2.0 | Python | |
| Fast and Accurate ML in 3 Lines of Code | ||||||||||
| Merlion | 3,179 |  | 3 | 9 months ago | 18 | June 28, 2022 | 14 | bsd-3-clause | Python | |
| Merlion: A Machine Learning Framework for Time Series Intelligence | ||||||||||
| Ad_examples | 738 | 2 years ago | 2 | mit | Python | |||||
| A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network. | ||||||||||
| Modeltime.ensemble | 70 | 1 | 6 months ago | 10 | April 18, 2023 | 11 | other | R | ||
| Time Series Ensemble Forecasting | ||||||||||
| Mars_express__esn | 9 | 6 years ago | mit | Jupyter Notebook | ||||||
| Tackling ESA's Mars Express Power Challenge with Echo State Networks | ||||||||||
| Unsupervisedensembles | 5 | 6 years ago | gpl-3.0 | R | ||||||
| Unsupervised ensemble learning methods for time series forecasting. Bootstrap aggregating (bagging) for double-seasonal time series forecasting and its ensembles. | ||||||||||
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Python
Streaming
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Autoencoder
Anomaly Detection
Ensemble Learning