Question 123 of 280
Single answerYou are developing an ML model to predict house prices. While preparing the data, you discover that an important predictor variable, distance from the closest school, is often missing and does not have high variance. Every instance (row) in your data is important. How should you handle the missing data?
ADelete the rows that have missing values.
BApply feature crossing with another column that does not have missing values.
✓CPredict the missing values using linear regression.
.
DReplace the missing values with zeros
✓
Correct Answer: C
Predict the missing values using linear regression. .
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Explanation
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