Discussion
What is naive Bayes?
Answer: B
The classifier assumes each feature independent of the others given the class, giving a network with the class as a single parent of every feature. The assumption is almost always false and the classifier is nonetheless remarkably effective. Empty networks, rule approximations and data free estimation are different notions. A model whose central assumption is known to be wrong and which works anyway is worth understanding precisely, since the reason it works is not obvious.
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