Conformal Predictions for Time Series Probabilistic Forecasting

Chris Kuo/Dr. Dataman
Dataman in AI
Published in
8 min readApr 12, 2024

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Real-world applications and planning require probabilistic forecasts rather than a point estimate. Probabilistic forecasts, also called prediction intervals or prediction uncertainty, can give planners a sense of uncertainty. However, the typical machine learning models such as linear regressions, random forecasts, or gradient boosting machines, are designed to produce mean…

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Chris Kuo/Dr. Dataman
Dataman in AI

The Dataman articles are my reflections on data science and teaching notes at Columbia University https://sps.columbia.edu/faculty/chris-kuo