Machine learning and ARIMA model averaging for adaptive public health forecasting: Ontario COVID-19 case study
Read the original at arxiv.org→arXiv:2608.20406v1 Announce Type: new Abstract: Public health forecasts must respond to abrupt changes in surveillance data without over-extrapolating noise, reporting artifacts, or temporary trends. We evaluated...
Original headline: "Machine Learning and ARIMA Model Averaging for Adaptive Public Health Forecasting: Comparative Evaluation and an Ontario COVID-19 Case Study"
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- Aug 24, 04:00 UTC arXiv cs.LG lead source Machine Learning and ARIMA Model Averaging for Adaptive Public Health Forecasting: Comparative Evaluation and an Ontario COVID-19 Case Study