#MLMuse -- Naivety in Naive Bayes' Classifiers

Classifying our data and predicting the outcomes from our historical data are huge tasks at the moment. For performing these tasks, we have a robust family of Supervised Learning Algorithms called Naive Bayes' Classifiers. Naive Bayes' Classifiers are wholly based on the Bayes' Theorem which gives us the probability of an event, given that another event has already occurred. This is symbolically expressed as P(A B), i.e. Probability of event A will occur given that event B has already occurred.