Naive Bayes Classification🔗
This class provides a gentle introduction to the Bayesian approach to Supervised Learning. We will consider the question of estimating the distribution of a label $y$ given an input $x$ and some data. A first, very naive way to tackle this problem will involve a strong hypothesis of conditional independence, which we will call the naive Bayes assumption. This will open the door to the method of Naive Bayes Classification.
Pre-class refresher activities and solution
Summary card
Lecture notes
References🔗
Exploring conditions for the optimality of naive Bayes.
Zhang, H. International Journal of Pattern Recognition and Artificial Intelligence, 19(02), 183-198, (2005).