Suppose the feature vector x can only take values −1 or +1, and the Bayes rule is as follows: decide 0 when x = −1 and decide 1 when x = +1. Suppose the cost of a correct decision is 0, but the cost of an incorrect decision is as follows. The cost of deciding 0 when actual class is 1 is $5 and the cost of deciding 1 when the class is 0 is $10. What is the expression for the average cost of the decision rule (in terms of P (x|0), P (x|1), P (0|x), P (1|x), P(0), and P(1))?