ad_examples
shubhomoydas
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.
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8 data points · 2021-08-01 → 2026-04-01How do you feel about this project?
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Question copied to clipboardWhat is the shubhomoydas/ad_examples GitHub project? Description: "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.". Written in Python. Explain what it does, its main use cases, key features, and who would benefit from using it.
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