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ConformalPrediction.jl is a package for Predictive Uncertainty Quantification (UQ) through Conformal Prediction (CP) in Julia. It is designed to work with supervised models trained in MLJ (Blaom et al. 2020). Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use of dedicated calibration data.
Features
- Examples available
- Documentation available
- Package for Predictive Uncertainty Quantification (UQ) through Conformal Prediction (CP) in Julia
- Licensed under the MIT License
- Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates
- Repeated sampling and dedicated calibration data
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