While conducting an exploratory analysis of a dataset, you discover that categorical feature A has substantial predictive power, but it is sometimes missing. What should you do?

A. Drop feature A if more than 15% of values are missing. Otherwise, use feature A as-is. B. Compute the mode of feature A and then use it to replace the missing values in feature A. C. Replace the missing values with the values of the feature with the highest Pearson correlation with feature A. D. Add an additional class to categorical feature A for missing values. Create a new binary feature that indicates whether feature A is missing.