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Prediction Intervals

A prediction interval is an estimate of an interval in which a future observation will fall, with a certain probability, given what has already been observed. Prediction intervals are often used in regression analysis.

Papers

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Showing 251–260 of 309 papers

TitleStatusHype
Machine learning for recovery factor estimation of an oil reservoir: a tool for de-risking at a hydrocarbon asset evaluation—0
A framework for predicting, interpreting, and improving Learning Outcomes—0
Explainable boosted linear regression for time series forecasting—0
Ridge Regression Revisited: Debiasing, Thresholding and Bootstrap—0
Moment Multicalibration for Uncertainty Estimation—0
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction IntervalsCode1
CD-split and HPD-split: efficient conformal regions in high dimensions—0
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep EnsemblesCode1
Efficient Conformal Prediction via Cascaded Inference with Expanded AdmissionCode1
Conformal Prediction Intervals for Neural Networks Using Cross Validation—0
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