Why does the naive bayes algorithm make the naive assumption that features are independent to each other? Naive Bayes is called naive because it makes the naive assumption that features have zero correlation with each other. They are independent of each other. Why does naive Bayes want to make such an assumption?
By doing so, the joint distribution can be found easily by just multiplying the probability of each feature whilst in the real world they may not be independent and you have to find the correct joint distribution. It is naive due to this simplification.