Machine Learning and ARIMA Model Averaging for Adaptive Public Health Forecasting: Comparative Evaluation and an Ontario COVID-19 Case Study
These findings support selecting forecasting models according to operating conditions rather than relying on a single universally preferred approach, and provide a practical framework for combining complementary statistical and machine-learning forecasts.
Yu Zou, Ye Li, Johra Moosa et al.
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