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Open source
24 alternativesFrouros
An open source Python library for drift detection in machine learning systems.
About Frouros
Frouros is an open-source Python library for drift detection in machine learning systems. It provides classical and more recent algorithms for both concept drift and data drift detection, with quickstart examples using DDM for concept drift and the Kolmogorov-Smirnov test for data drift. The repository does not state pricing or platform requirements.
Key features
- Open-source Python library for drift detection in machine learning systems
- Detects concept drift and data drift
- Includes classical and more recent algorithms for both drift types
- Provides DDM concept drift detector and Kolmogorov-Smirnov data drift detector
- Supports detector configuration with warning and drift levels
- Computes metrics such as PrequentialError
Best for: Machine learning developers and researchers who need to monitor or test for concept and data drift in Python systems.
Good for
- Open source and implemented in Python
- Covers both concept drift and data drift detection
- Includes classical and more recent detection algorithms
Frouros at a glance
- Website
- github.com/IFCA/frouros
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Frouros FAQ
What types of drift can Frouros detect?
Frouros detects concept drift and data drift in machine learning systems.
Which detectors are shown in the quickstart?
The quickstart shows DDM for concept drift and the Kolmogorov-Smirnov test for data drift.
What metric is used in the concept drift example?
The concept drift example uses PrequentialError with alpha set to 1.0, which is equivalent to normal accuracy.
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