Machine Learning

CS 5350/6350, Fall 2020

The Naive Bayes Classifier

In this lecture, we will look at the naive Bayes classifier. We will first see how we can predict labels using the maximum a posteriori criterion and then examine the naive Bayes assumption. Then we will see how we can learn the naive Bayes classifier using a probabilistic criterion. Finally, we will look at some practical issues, with specific focus on smoothing.