Discussion
Which property survives the distorted estimates naive Bayes produces?
Answer: A
The estimated probabilities are badly calibrated, often near zero or one, but the class with the largest score is frequently still the right one, and classification needs only the argmax. Real features are rarely independent, the errors do not cancel exactly, and the prior does not repair them. Separating calibration from discrimination is the general point, and it recurs whenever a model is judged by accuracy alone.
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