If a fraud detector has a 3% error rate, about how large should the eyeball development set be to expect roughly 90 mistakes?

If a classifier makes fewer mistakes, the eyeball dev set can usually be smaller and still collect enough errors for analysis.

A validation set with a 5% mistake rate needs about _____ examples to contain roughly 100 wrong predictions.

Match each classifier-error concept to its dev-set implication.

Order the steps for estimating the required size of an Eyeball dev set from a model's error rate.

Why does a low classifier error rate call for a larger review set?

A classifier with an 8% error rate needs an Eyeball dev set of 2,500 examples to collect about 100 mistakes.

The _____ the classifier error rate, the larger the review set must be to collect enough misclassified examples.

Approximate Review-Set Sizes Needed to See About 100 Errors

Order the logic that explains why a better classifier can require a bigger dev set for error review.

How Dev-Set Error Rate Affects Eyeball Dev Set Size

Sizing a Manual Review Set for a High-Accuracy Defect Detector

Why a 2,000-Item Manual Review Set Fits a 5% Error Rate