Abstract: Machine learning often lacks transparent performance indicators, especially in generating point predictions. This paper addresses this limitation through conformal prediction, a ...
Accurate wind power prediction can effectively alleviate the pressure of the power system peak frequency regulation, and is more conducive to the economic dispatch of the power system. To enhance wind ...
Abstract: Conformal prediction (CP) is known to theoretically guarantee prediction interval coverage under the exchangeability assumption. However, industrial time series collected from real-world ...
Example of how prediction distributions (PDs; panel A) combined with prediction intervals (PIs; panel B) can be used to understand the generality of population effect size. The overall and ...
Evolution & Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia Division of Ecology and Evolution, Research School of ...
To generate a high-confidence statistical forecast with upper and lower confidence limits, you can combine a statistical forecasting model with the computation of prediction intervals. Confidence ...
In machine learning, reliable predictions and uncertainty quantification are critical for decision-making, particularly in safety-sensitive domains like healthcare. Model calibration ensures ...
The short-term fluctuation of wind power can affect its prediction accuracy. Thus, a short-term segmentation prediction method of wind power based on ramp segment division is proposed. A time-series ...
After estimating a regression model, allow the users to specify a set of values for the input variable, and produce the point prediction, the confidence interval and prediction interval for a given ...
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