Naïve Bayes ClassificationNaïve Bayes Classification: "The underlying idea is to use individual words present in the text as indications for what category it is most likely to belong to, using Bayes Theorem, named after the cheerful-looking Reverend Bayes.
Imagine that you received an email containing the words “Nigeria”, “Prince”, “Diamonds” and “Money”. It is very likely that if you look into your spam folder, you’ll find quite a few emails containing these words, whereas, unless you are in the business of importing diamonds from Nigeria and have some aristocratic family, your “normal” emails would rarely contain these words. They have a much higher frequency within the category “Spam” than within the Ham, which makes them a potential flag for undesired business ventures.
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