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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 261–270 of 309 papers

TitleStatusHype
Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN—0
AutoCP: Automated Pipelines for Accurate Prediction Intervals—0
Calibrated Reliable Regression using Maximum Mean Discrepancy—0
PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value PredictionCode1
Curating a COVID-19 data repository and forecasting county-level death counts in the United StatesCode1
Statistical Verification of Autonomous Systems using Surrogate Models and Conformal Inference—0
CatBoostLSS -- An extension of CatBoost to probabilistic forecastingCode1
Online Control of the False Coverage Rate and False Sign Rate—0
Optimal Uncertainty-guided Neural Network Training—0
Per-sample Prediction Intervals for Extreme Learning Machines—0
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