henrikbostrom/crepes
Python package for conformal prediction
Wraps standard scikit-learn classifiers and regressors to output calibrated p-values and prediction sets/intervals with guaranteed coverage through conformal prediction methods. Supports multiple strategies including standard, Mondrian, and class-conditional variants, with optional online calibration for semi-online prediction and exchangeability testing via martingale analysis. Integrates seamlessly with scikit-learn's ecosystem through wrapper classes while providing customizable non-conformity scores and difficulty estimates.
558 stars and 19,742 monthly downloads. Available on PyPI.
Stars
558
Forks
45
Language
Python
License
BSD-3-Clause
Category
Last pushed
Oct 09, 2025
Monthly downloads
19,742
Commits (30d)
0
Dependencies
3
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