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How does the source define high bias, and what analysis can help?
Question: Answer in one to three sentences using the source's relationship between training-set fit and error analysis.
Sample answer: High bias means the algorithm is not fitting the training set well. In that case, error analysis on the training data can be useful.
Key points:
- High bias is poor training-set fit.
- Training-data error analysis can be useful.
Rubric: The answer must state both the poor training-set fit and the usefulness of training-data error analysis.
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Reviewing Poor Training Examples to Identify Training Error Categories
When is error analysis on the training data potentially useful?
High bias means the algorithm is not fitting the training set well.
For high bias, error analysis may be performed on the _____ data.
Match each training-error-analysis concept with its source-grounded meaning.
Order the reasoning process for deciding whether to analyze training errors.
Explain why training-data error analysis is relevant when an algorithm has high bias.
What analysis should a team consider after observing poor training-set fit?
How does the source define high bias, and what analysis can help?
How should training-data error analysis relate to other high-bias techniques?
Training-data error analysis can follow a protocol similar to Eyeball dev set error analysis.