getting to know the bayes theorem at its corenaive bayes classification is nothing more than keeping track of which feature gives evidence to which class to ease our understandinglet us assume the following meanings for the variables that we will use to explain naive bayesvariable possible values meaning "pos""negclass of tweet (positive or negativenon-negative integers counting the occurrence of awesome in the tweet non-negative integers counting the occurrence of crazy in the tweet during trainingwe learn the naive bayes modelwhich is the probability for class when we already know features and this probability is written as since we cannot estimate this directlywe apply trickwhich was found out by bayesif we substitute with the probability of both features and occurring and think of as being our class we arrive at the relationship that helps us to later retrieve the probability for the data instance belonging to the specified classthis allows us to express by means of the other probabilitieswe could also say that