Extrapolation
Predicting for inputs outside the range of the data a model learned from, where it's only guessing.
A regression will happily price a 25-year-old tent: it just follows the line. But only six of the 800 trade-ins are older than ten, and none older than 12. Beyond that, the model is guessing. It assumes the 8%-a-year pattern carries on forever, when vintage gear might be worth more, or nothing. Predicting outside the range of the training data is called extrapolation, and a good tool says when it's doing it.
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Each year multiplies the quote by about 0.92, so the dollar loss per year shrinks as the item ages, and an expensive item loses more dollars than a cheap one. That's the multiplicative pattern the log model captures and the dollar model couldn't.
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Project: a price model · Multiple regression on log prices, one-hot categories, percentage effects and an extrapolation flag. About 45 minutes.
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