Problem 3 10 points The prediction rule for a logistic-regression, binary classifier is if P(y= 1|x) >P(y= 0|x) then output 1 otherwise, output 0. Assume that our wR2 (i.e., there are two weights w1 and w2 only) and there is a bias bR. The label y{0,1}. The input features xR2. Question: Derive the decision boundary equation for this classifier. Hints: The decision boundary of this logistic regression classifier is a line at the point when P(y= 1|x) = P(y= 0|x) From the above equation, continue deriving step-by-step (with justifications) to arrive at the equation for the linear decision boundary (of this logistic regression classifier) separating two classes (y= 0 and y= 1).