What primary problem does a model with 1% training error and 5% training-dev error exhibit when optimal error is ~0%?

True or False: When training error is 1%, training-dev error is 5%, and optimal error is ~0%, the algorithm primarily has high bias.

When training error is 1% and training-dev error is 5%, with near-zero optimal error, the algorithm has high _____.

Match each error metric to its role in diagnosing high variance in the cat detection scenario.

Order the steps for diagnosing the primary error type when given training, training-dev, and dev error values.

Which gap in the error analysis directly signals high variance in a model with 1% training error, 5% training-dev error, and 5% dev error?

True or False: In the ML Yearning cat detection example used to illustrate high variance, the dev error and training-dev error are both 5%.

The avoidable _____ is only ~1% in this scenario because training error (1%) is very close to optimal error (~0%).

Match each diagnostic gap to the problem type it reveals in the cat detection error analysis.

Order the reasoning steps that lead to the conclusion 'this model has high variance' given the cat detection error values.