Learning a Bayes classifier without independence assumptions requires an unrealistic number of training examples. Compute the number of parameters to be learned for a model Y = f(X) where Y is a boolean variable, and X is vector of N boolean features. What is the number of parameters under Naive Bayes assumptions? p(Y | X) = p(X | Y) p(Y) / p(X) Number of parameters for p(Y) Number of parameters for p(X | Y) Number of parameters under Naive Bayes independence assumption: