In what way does improper handling of missing data affect the generalization capability of a model?
- Depends on the amount of missing data.
- Hampers generalization.
- Improves generalization.
- No effect on generalization.
Improper handling of missing data can lead to the model learning incorrect or misleading patterns from the data. This can hamper the model's ability to generalize well to unseen data.
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