Assuming Independence in Naive Bayes If features of the Naive Bayes are not independent then what are the consequences of the results?

Similar questions were discussed several times in other questions tagged as naive-bayes so I encourage you to check them as well. In general, you would always never have features that are, strictly speaking, independent. Naive Bayes algorithm pretends that they are to simplify the computations because it is a very simple algorithm. The probabilities that it computes are not correct in the sense of reflecting the true probabilities, because of making a usually incorrect assumption on independence. Nonetheless, the algorithm has proven useful as a classification algorithm, where for many applications (e.g. simple NLP problems) it works very well. It's not really about if the assumptions hold, because they usually won't, but if it works well enough for your problem.
