In environmental forecasting, what is the main risk of an "overfitted" Deep Learning model?

Question

Accepted Answer

It memorizes specific historical events (noise) and fails to predict accurately when new, unseen weather patterns occur.

Answer

It requires significantly more computational power than the hardware allows.

Answer

It produces predictions that are too generalized and ignore local weather specifics.

Answer

It cannot process non-linear data such as humidity or wind speed.

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