vc1492a / PyNomaly
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
Why this job: works in the areas we cover, but does not say which job it does
What it does
PyNomaly is a Python 3 implementation of LoOP (Local Outlier Probabilities). LoOP is a local density based outlier detection method by Kriegel, Kröger, Schubert, and Zimek which provides outlier scores in the range of [0,1] that are directly interpretable as the probability of a sample being an outlier.
Get started
pip install PyNomaly # or pip3 install ... if you're using both Python 3 and 2.- Maintenance
- Active
- Last commit 5 months ago
- Stars
- 331
- On GitHub
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.4.0
- Released 5 months ago
- Built with
- Python
- 98% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 96% closed
- 2 still open
- Pull requests
- 34 merged
- 2 waiting
- Releases
- 3
- 2 in the last year
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 98%
- TeX 2%
Topics
- outlier-detection
- anomaly-detection
- machine-learning
- outlier-scores
- probability
- outliers
- anomalies
- nearest-neighbors
Project record
- JobOther AI tools
- StatusListed
- Commits232
- Forks37
- Watching23
- Stars in 28 days+1
- CreatedMay 19, 2017
- First seen by usNov 7, 2026
- CheckedNov 8, 2026