The nave Bayes classifier computes probabilities directly from the data. Using the same data from Problem 1, why not simply compute P(outcome = red | (x1 = yes & x2 = up & x3 = right & x4 = on & x5 = high)) directly for the first test set observation? In other words, what advantage does the process you went through to actually solve Problem 1 have over simply counting the number of observations with the exact input values of yes, up, right, on, and high, counting the number of observations with the exact input values of yes, up, right, on and high AND an outcome of red, and then simply dividing the latter by the former