Question: Answer in one to three sentences explaining what high bias means and what kind of error review can help diagnose it.

Sample answer: High bias means the model is not capturing the pattern in the data it learned from, so its predictions remain weak even on familiar examples. Looking at mistakes made on the training data can help confirm that the model is underfitting.

Key points:

• High bias means the model performs poorly on the data used for learning.
• Checking errors on the training data can help diagnose the problem.

Rubric: The answer must explain that high bias appears as poor performance on the learning data and that reviewing training-data errors can be useful.