An engineer wanted to imitate 5-fold cross validation. He created 5 bootstraps from the original dataset. Then, he trained 5 models from the bootstraps, tested them on the original dataset, and measured the error rates. To obtain the estimated error rate, he computed the average of the 5 error rates. Why is his approach wrong? Too many original data points appeared in each bootstrap. He would underestimate the error rate. Each bootstrap was too small. He would overestimate the error rate. Each bootstrap was too large. He would underestimate the error rate. Too many original data points appeared in each bootstrap. He would overestimate the error rate

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The correct answer is Too many original data points appeared in each bootstrap He would underestimat... View the full answer