The feature independence assumption in Naive Bayes simplifies the classification problem by
- ignoring the prior probabilities altogether.
- assuming that classes are independent of the input features.
- assuming that the prior probabilities of all classes are independent of one another.
- allowing the probability of each feature given the class to be estimated individually.
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