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].
This tool helps data analysts and domain experts identify unusual data points in their datasets. You provide a dataset (like sensor readings, customer transactions, or patient health metrics) and it returns a probability score for each data point, indicating how likely it is to be an outlier. This is especially useful for uncovering anomalies that might signal fraud, equipment malfunction, or rare scientific phenomena.
328 stars. Used by 1 other package. Available on PyPI.
Use this if you need to detect individual outliers in numerical data and want a clear, interpretable probability score for each potential anomaly.
Not ideal if your data contains missing values or needs to be scaled; these steps must be handled separately before using the tool.
Stars
328
Forks
37
Language
Python
License
—
Category
Last pushed
Feb 04, 2026
Commits (30d)
0
Dependencies
2
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1
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