(a) Suppose we have a large training set with 100,000 samples. There are 3 different classes and 4 different features in the training set. Each distinct features can take 5 different values. How many parameters do we need to estimate, if we don't make the naive Bayes assumption? How many parameters do we need to estimate, if we make the naive Bayes assumption