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Explain the mechanism and primary trade-off of early stopping.
Question: How does early stopping work during model training, and what is its effect on bias and variance?
Sample answer: Early stopping works by stopping gradient descent early based on the dev-set error. This approach acts similarly to regularization, reducing the model's variance but increasing its bias.
Key points:
- Stops gradient descent early based on dev-set error
- Reduces variance
- Increases bias
Rubric: The answer must explain that gradient descent is stopped early based on dev-set error and state that this reduces variance while increasing bias.
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Machine Learning Yearning @ DeepLearning.AI
Related
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