A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
$ npx skills add yzhao062/pyodAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
$ npx skills add yzhao062/pyodA python library for user-friendly forecasting and anomaly detection on time series.
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$ npx skills add huggingface/datasetsHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep PyNomaly if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.