Given a dataset with 40% missing values in a critical feature, how do you decide whether to drop the feature, impute it, or use a model that handles missingness?
Problem
Given a dataset with 40% missing values in a critical feature, how do you decide whether to drop the feature, impute it, or use a model that handles missingness?
Your answer
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