A municipal breakwater-station log summarizer recites last January’s incident IDs almost verbatim and fails on this week’s new icing pattern. Which bias-and-variance effect is that?
Select an answer to reveal the explanation.
Short Explanation
Think of a summarizer reciting last January’s incident IDs and missing this week’s icing. That is high variance, or overfitting. Memorized quirks do not travel.
Full Explanation
Overfitting is a bias-and-variance effect that produces inaccuracy on new data. Reciting last January’s IDs and failing a new icing pattern is that effect. More storage, underfitting, and a benchmark win are the wrong names.