<ul><li>Electricity demand forecasting is essential to prevent blackouts and ensure supply meets demand.</li><li>A combination of a Generalized Additive Models (GAM) with a State-Space model leads to adaptive (online) forecasting.</li><li>The formula and adaptation parameters of the GAM need to be fixed before model training, affecting predictive performance.</li><li>The DRAGON package is used to optimize these parameters in automated online generalized additive model selection.</li></ul>

AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting

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