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How Regularization Usually Changes Bias and Variance
Question: When a model is trained with a penalty or constraint such as L2 regularization, L1 regularization, or dropout, what typically happens to its bias and variance?
Sample answer: Regularization usually lowers variance and raises bias.
Key points:
- It reduces variance.
- It increases bias.
Rubric: Give full credit only if the response clearly says that regularization decreases variance and increases bias.
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