Inference, estimation, and decision-making from data
You can't judge a model by its training error; it has already seen that data, so it can cheat by memorizing. You need its error on data it has never seen. But holding out a single test set wastes data and gives a noisy estimate. Cross-validation solves both problems.
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▶ Cross-Validation