[12 points] You will train a Naive Bayes classifier to predict class labels Y as a function of input features A and B. Y , A, and B are all binary variables, with domains 0 and 1. You are given 10 training points from which you will estimate your distribution. A 1 1 1 0 1 0 1 0 1 1 B 1 1 0 1 0 1 1 1 0 0 Y 1 1 0 1 0 1 0 0 1 1 What are the maximum likelihood estimates for the tables P(Y ), P(A|Y ), and P(B|Y )? Answer Consider a new data point (A = 1, B = 0). What label would this classifier assign to this sample? Answer Compute the new distribution for P(A|Y) using Laplace Smoothing with k = 2 for smoothing out your distribution