Question: Describe the "textbook" example of a learning curve that exhibits high avoidable bias. Be sure to explain the relationship between training error, dev error, and desired performance at the largest training set size.

Sample answer: In a standard learning curve for high avoidable bias, the model's training error stays far above the desired performance level (which is our estimate of the optimal error rate) even at the largest training-set size. This large gap between training error and desired performance indicates that the model does not do well on the training set, meaning it has large avoidable bias. Furthermore, in this pattern, the gap between the training curve and the dev curve is small, which indicates that the model has small variance despite the bias.

Key points:

• Training error remains far above the desired performance level.
• Large gap between training error and desired performance indicates large avoidable bias.
• Model does not perform well on the training set.
• Small gap between training error and dev error.
• Small gap between training and dev error indicates small variance.

Rubric: A full credit response must clearly identify the two main gaps at the largest training set size: the large gap between training error and desired performance (indicating high bias) and the small gap between training error and dev error (indicating small variance).