Let's try to understand how classification models work with the help of a Naive Bayes classifier. In order to understand Naive Bayes classifiers, we need to understand the Bayes theorem. The Bayes theorem is the theorem we studied in probability, and can be explained with the help of an example.
Let's say that we have two machines, both of which produce spanners. The spanners are marked with which machine has produced them. M1 is the label for machine 1 and M2 is the label for machine 2.
Let's say that one spanner is defective and we want to find the probability that the defective spanner was produced by machine 2. The probability of event A happening provided B has already occurred is determined by the Naive Bayes ...