1: Naive Bayes classifier In this problem, we will study the decision boundary of multinomial Naive Bayes model for binary text classification. The decision boundary is often specificed as the level set of a function: {x X : h(x) = 0}, where x for which h(x) > 0 is in the positive class and x for which h(x) < 0 is in the negative class. 1. [2 points] Give an expression of h(x) for the Naive Bayes model p(y | x), where denotes the parameters of the model