Suppose that we have unlabeled data. That is, all we have are a collection of emails and want to determine whether any of them is spam or not. Let's say we have $1,000$ rules to determine whether a particular email is spam or not. For example, one rule could be that a sender's email address should not contain the text
no_reply . If an email does contain this text, then it would be classified as spam.
Question. What are the advantages/disadvantages of a rules-based approach for detecting spam vs. a non-rules-based approach/unsupervised methods for detecting spam?
Would there even be a point in constructing a non-rules based model given that we already have a rules based model? Could we use the rules-based model to create some labeled training data and then apply supervised techniques?