(i) In the first graph, the model’s performance tries to cover all data samples, even if they aren’t aligned with the true function. This model is thought to be overfitting, with decreased accuracy.
(ii) In the second graph, the model’s performance equals the true function, indicating that the model has optimal accuracy and is referred to as a perfect fit.
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