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yzhao062/pyod

A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

Latest metrics (snapshot 2026-10-14)

stars10038
forks1514
issues222
pushed_at2026-10-12T03:42:10Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-1410038

ADC Momentum: 23/100

ADC Momentum 23 Leaderboard

Growth velocity9
Consistency7
Recency88
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

descriptionA Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
urlhttps://github.com/yzhao062/pyod
languagePython
licenseBSD-2-Clause
topicsagentic-ai
anomaly-detection
data-mining
data-science
deep-learning
foundation-models
fraud-detection
graph-anomaly-detection
image-anomaly-detection
machine-learning
multimodal
nlp-anomaly-detection
created_at2017-10-03T20:29:04Z
homepagehttps://pyod.dev/

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