How does Random Forest handle missing values during the training process?
- Both imputation using mean/median and using random values
- Ignores missing values completely
- Randomly selects a value
- Uses the mean or median for imputation
Random Forest can handle missing values by using mean or median imputation for numerical attributes and random value selection or mode imputation for categorical ones. This flexibility helps in maintaining robustness without losing significant data.
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