How can mishandling missing data in a feature affect the feature's importance in a machine learning model?
- Decreases the feature's importance.
- Depends on the feature's initial importance.
- Has no effect on the feature's importance.
- Increases the feature's importance.
Mishandling missing data can distort the data distribution and skew the feature's statistical properties, which might lead to a decrease in its importance when the model is learning.
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