There are 0 repository under prediction-intervals topic.
An extension of XGBoost to probabilistic modelling
Conformal classifiers, regressors and predictive systems
An extension of LightGBM to probabilistic modelling
Quantile Regression Forests compatible with scikit-learn.
An extension of CatBoost to probabilistic modelling
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
Valid and adaptive prediction intervals for probabilistic time series forecasting
👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
Bringing back uncertainty to machine learning.
Official implementation of the paper "PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction" by Eli Simhayev, Gilad Katz and Lior Rokach.
Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.
Adaptive Conformal Prediction Intervals (ACPI) is a Python package that enhances the Predictive Intervals provided by the split conformal approach by employing a weighting strategy.
Prediction Intervals with specific value prediction
Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
**curve_fit_utils** is a Python module containing useful tools for curve fitting
Implementation of Conformal Convolution T-learner (CCT) and Conformal Monte Carlo (CMC) learner
DualAQD: Dual Accuracy-quality-driven Prediction Intervals
Prediction intervals for trees using conformal intervals. Docs at https://pitci.readthedocs.io/en/latest/
implementation of fair dummies
An HR predictive analytics tool for forecasting the likely range of a worker’s future job performance using multiple ANNs with custom loss functions.
Uncertainty quantification of black hole mass estimation
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.
Complete mathematical and statistical analysis of linear regression model
The project involves the multivariate regression analysis of a dataset.
Analysis of Predictive inference with jackknife+, a new method for creating prediction intervals with stronger coverage guarantees
Developed a linear regression model to forecast case shipments considering various predictor variables such as time trends (month), seasonality (seasonal index), and promotions. Conducted Durbin Watson test and generated a forecast and prediction interval.
Plotting of the Confidence interval and Prediction interval for a Linear Regression model.