Influenza Forecasting Framework based on Gaussian Processes: Difference between revisions
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== Abstract == | == Abstract == | ||
This paper presents a novel framework for seasonal epidemic forecasting using Gaussian process regression. Resulting retrospective forecasts, trained on a subset of the publicly available CDC influenza-like-illness (ILI) data-set, outperformed four state-of-the-art models when compared using the official CDC scoring rule (log-score). | |||
== Background == | == Background == | ||
Revision as of 00:12, 16 November 2020
Abstract
This paper presents a novel framework for seasonal epidemic forecasting using Gaussian process regression. Resulting retrospective forecasts, trained on a subset of the publicly available CDC influenza-like-illness (ILI) data-set, outperformed four state-of-the-art models when compared using the official CDC scoring rule (log-score).