Data Sets Where the Naive Bayes Assumption Holds Discussion topic: The Naive Bayes assumption assumes that feature values are independent given the label. This is a very bold assumption. For this discussion, think of an example where this assumption would and would not hold. Present an example scenario where the Naive Bayes assumption would or would not hold. Explain why the assumption would or would not hold. For example, the Naive Bayes classifier is often used in spam filtering, where the data is emails and the label is spam or not-spam. The Naive Bayes assumption implies that the words in an email are conditionally independent, given that you know that an email is spam or not. Clearly this is not true: we know, for example, that a spam email containing a word like "sale" is much more likely to contain a word like "price". More generally, neither the words in spam or not-spam emails are drawn independently at random, since we don't randomly choose words when constructing sentences in natural languages