The first formula is loss function of the linear regression model.

m L(w, b) = 1 2m I (1(2(2) - 2(2))2 (1) i= where h(x) = wx + b. The loss function of logistic regression model is: m L(w, b) = - m y() log(h(x())) + (1 -y(2) ) log(1 - h(x())) (2) i=1 where h((x) = Ite-(with) . Please prove that although both models have different loss functions, their optimization are same since they have the same derivatives L(w,b) L(w,b) ab