I'm reading about how Conditional Probability/ Bayes Theorem is used in Naive Bayes in Intro to Statistical Learning, but it seems like it isn't that "groundbreaking" as it is described?
If I'm not mistaken doesn't every single ML classifier use conditional probability/Bayes in its underlying assumptions, not just Naive Bayes? We are always trying to find the most likely class/label, given a set of features. And we can only deduce that using Bayes rule since we are (usually) solving for P(class|features) with P(features|class)?