joneswack/conformal-predictions-from-scratch
Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.
This educational project helps machine learning researchers and practitioners deeply understand how Conformal Prediction methods work. It takes raw data and a trained machine learning model, and outputs predictions augmented with reliable uncertainty estimates. This is designed for those who need to confidently apply or develop new methods for quantifying prediction reliability.
229 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or advanced practitioner who needs to understand the fundamental mechanics of Conformal Prediction to build confidence or innovate new methods.
Not ideal if you are looking for a plug-and-play library to quickly add uncertainty estimates to your models without needing to delve into the underlying mathematics.
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Last pushed
Jan 14, 2024
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