You're comparing two Polynomial Regression models: one with a low degree and one with a high degree. The higher degree model fits the training data perfectly but has poor test performance. How do you interpret this, and what actions would you take?
- Choose the high degree model
- Choose the low degree model or consider regularization
- Ignore test performance
- Increase the degree further
The high degree model is likely overfitting the training data, leading to poor test performance. Choosing the low degree model or applying regularization to the high degree model can improve generalization.
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