Why is it problematic for a model to fit too closely to the training data?
- It improves generalization
- It increases model simplicity
- It leads to poor performance on unseen data
- It reduces model bias
Fitting too closely to the training data leads to overfitting and poor performance on unseen data, as the model captures noise and fails to generalize well.
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