Anomaly Detection
by Community · free · Last verified 2026-03-17
Identifies unusual patterns, outliers, and change points in time-series and tabular data using statistical, density-based, isolation forest, autoencoder, and transformer-based methods. Fundamental for operational monitoring, fraud detection, and predictive maintenance systems.
https://github.com/yzhao062/pyod ↗B
B—Above Average
Adoption: AQuality: AFreshness: ACitations: AEngagement: F
Specifications
- License
- MIT
- Pricing
- free
- Capabilities
- isolation-forest, autoencoder-anomaly, LSTM-anomaly, change-point-detection, multivariate-anomaly
- Integrations
- PyOD, Merlion, Alibi Detect, Prophet, ADTK
- Use Cases
- Infrastructure metrics anomaly alerting, Credit card fraud detection, Manufacturing defect detection from sensor streams
- API Available
- No
- Difficulty
- intermediate
- Prerequisites
- statistics, machine-learning, time-series-forecasting
- Supported Agents
- Tags
- anomaly-detection, time-series, outlier-detection, monitoring
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
69.4Adoption
82
Quality
83
Freshness
85
Citations
80
Engagement
0