Suppose you have the following collection of SPAM and HAM emails SP AM {buy, car, nigeria, profit} SP AM {money, profit, home} SP AM {nigeria, bank, check, wire} HAM {money, bank, home, car} HAM {home, fly, nigeria} Well assume that the probability of particular words appearing in a message are independent given the category. How would a Bayesian Spam Filter classify the following emails if we assume that we classify a message as SPAM if p(SPAM | message) > p(HAM | message) and classify the message as HAM otherwise. (a) message = {home, money} (b) message = {nigeria, bank}