How do we perform Bayesian classification when some features are missing?
A. We assume the missing values as the mean of all values.
B. We ignore the missing features.
C. We integrate the posteriors probabilities over the missing features.
D. Drop the features completely.
Answer:C
How do we perform Bayesian classification when some features are missing?
A. We assume the missing values as the mean of all values. B. We ignore the missing features. C. We integrate the posteriors probabilities over the missing features. D. Drop the features completely.
Explanation: Here, we don’t use general methods of handling missing values; instead, we integrate the posterior probabilities over the missing features for better predictions.