Naive bayes classifier:
A full Bayesian classifier is a supervised learning technique that assigns a class to a record by finding other records with attributes just like it has, and finding the most prevalent class among them. Naive Bayes (NB) recognizes that finding exact matches is unlikely to be feasible in most cases, and does not require that. Working with the set of attribute values for a record in to be classified, NB multiplies together the probabilities that each attribute value occurs in class 1 [class 2], and then multiplies the result by the proportion of records belonging to class 1 [class 2]. The probability a record belongs to class 1 is then the above result for class 1, divided by the results for classes 1 and 2 added together.