Analysis of Predictive inference with jackknife+, a new method for creating prediction intervals with stronger coverage guarantees
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Updated
Mar 13, 2023 - Python
Analysis of Predictive inference with jackknife+, a new method for creating prediction intervals with stronger coverage guarantees
This module contains functions, bootStrapParamCI and bootStrapPredictInterval, that follow a bootstrap approach to produce confidence intervals for model parameters and prediction intervals for individual point predictions, respectively.
An HR predictive analytics tool for forecasting the likely range of a worker’s future job performance using multiple ANNs with custom loss functions.
Prediction intervals for trees using conformal intervals. Docs at https://pitci.readthedocs.io/en/latest/
**curve_fit_utils** is a Python module containing useful tools for curve fitting
Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
Prediction Intervals with specific value prediction
Bringing back uncertainty to machine learning.
👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
Quantile Regression Forests compatible with scikit-learn.
An extension of LightGBM to probabilistic modelling
Conformal classifiers, regressors and predictive systems
An extension of XGBoost to probabilistic modelling
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