Question: In linear regression, what does the term \'overfitting\' refer to?

Options:

1. The model performs well on training data but poorly on unseen data
2. The model is too simple to capture the underlying trend
3. The model has too few features
4. The model is perfectly accurate

Correct Answer: The model performs well on training data but poorly on unseen data

Solution:

Overfitting occurs when a model learns the noise in the training data instead of the actual underlying pattern, leading to poor performance on unseen data.