Assume you have a two class problem and that the class-conditional densities for the classes i = 1,2 are p(x| i) = N(x; 0; ) with - (69) = (19) and Xy = a) Draw the contours of equal probability for both p(x | 1) and p(x | 2). b) If the prior probabilities for each class are P(1) = P(2) = 0.5 then compute and draw the decision boundaries obtained using the Bayes' optimal classifier. c) In your diagram indicate the regions where the classifier will predict class 1 and where it will predict class 2. Hint: (| ,) = |2|- #exp { - 1/(x - 1) 2 - 1 (x-)}