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Discuss the potential drawbacks of using median imputation for a numerical feature in a dataset where the missing values are not missing at random. Explain how this could affect the model's ability to generalize to new data and suggest an alternative approach to handle such missing data.
A
Median imputation can introduce bias if the missingness is related to the target variable.
B
Median imputation is always unbiased and appropriate for all types of missing data.
C
Median imputation should not be used for numerical features.
D
Median imputation is only suitable for categorical features.