Question

A data scientist is preparing a numeric feature, annual_income, that contains missing values in a customer churn dataset. They plan to impute the missing values with the median before training a model. They have already split the data into training and test sets. To avoid data leakage while imputing, what is the correct approach?

Accepted Answer

Compute the median from the training set only, then use that value to fill missing values in both the training and test sets

Answer

Compute the median from the full dataset before splitting, then fill missing values in both sets

Answer

Compute a separate median from the training set and another from the test set, filling each set with its own median

Answer

Drop all rows with missing annual_income values from both the training and test sets