Prediction Intervals Python Packages

skforecast

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

quantile-forest

Quantile Regression Forests compatible with scikit-learn.

crepes

Python package for conformal prediction

scpi-pkg

Synthetic Control Methods

xgboostlss

An extension of XGBoost to probabilistic modelling

lightgbmlss

An extension of LightGBM to probabilistic modelling

doubt

Bringing back uncertainty to machine learning.

conformal-tights

👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster

insurance-conformal

Distribution-free prediction intervals for insurance pricing: conformal coverage guarantees, Tweedie non-conformity scores, SCR bounds, and anytime-valid sequential monitoring.

selfcalibratingconformal

An implementation of Self-Calibrating Conformal Prediction, accepted to Neurips 2024. SC-CP combines Venn-Abers calibration and conformal prediction to deliver calibrated point predictions alongside prediction intervals with finite-sample validity conditional on these predictions.

comport-ai

An HR predictive analytics tool for forecasting the likely range of a worker’s future job performance using multiple ANNs with custom loss functions.

pitci

Prediction intervals for trees using conformal intervals - pitci

neo-ls-svm

Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation