Uncertainty quantification of black hole mass estimation
-
Updated
Jul 24, 2023 - Jupyter Notebook
Uncertainty quantification of black hole mass estimation
The project involves the multivariate regression analysis of a dataset.
An HR predictive analytics tool for forecasting the likely range of a worker’s future job performance using multiple ANNs with custom loss functions.
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.
Analysis of Predictive inference with jackknife+, a new method for creating prediction intervals with stronger coverage guarantees
DualAQD: Dual Accuracy-quality-driven Prediction Intervals
Complete mathematical and statistical analysis of linear regression model
Plotting of the Confidence interval and Prediction interval for a Linear Regression model.
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.
Prediction intervals for trees using conformal intervals. Docs at https://pitci.readthedocs.io/en/latest/
Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
Implementation of Conformal Convolution T-learner (CCT) and Conformal Monte Carlo (CMC) learner
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.
👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
Bringing back uncertainty to machine learning.
implementation of fair dummies
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
**curve_fit_utils** is a Python module containing useful tools for curve fitting
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 Intervals with specific value prediction
Add a description, image, and links to the prediction-intervals topic page so that developers can more easily learn about it.
To associate your repository with the prediction-intervals topic, visit your repo's landing page and select "manage topics."