IBM / UQ360
Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.
Why this job: works in the areas we cover, but does not say which job it does
What it does
Use of meta-models to augment sklearn's gradient boosted regressor with prediction interval. See detailed example here.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 57 days ago
- Stars
- 270
- On GitHub
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 47% closed
- 8 still open
- Pull requests
- 17 merged
- 4 waiting
- Releases
- None
- Never published
- 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 100%
- R <1%
Topics
- uncertainty-quantification
- metrics
- uncertainty-estimates
- machine-learning
- artificial-intelligence
- trusted-ai
- uncertainty
- bayesianneuralnetwork
- calibration
Project record
- JobOther AI tools
- StatusListed
- Commits191
- Forks67
- Watching18
- Stars in 28 days0
- CreatedApr 28, 2021
- First seen by usNov 7, 2026
- CheckedNov 8, 2026