Machine learning python question.

Problem 4: Using Newton's Method for Logistic Regression Learning (15 code + 5 report = 20 points) For this problem, you will train a logistic regression model, whose loss function (also known as the logistic-loss or log-loss) is given by: J(w) log (1 + exp(-yiw'x;)) -y;) (9) n 1 = i=1 1 For Logistic Regression, typically a different formulation is presented. The decision rule is written as: -1 = { ; (6) if Oi 0.5 where, 1 Oi = 0(wTxi) 1 + exp -(wTxi) However, one can see that it is equivalent to checking if w T Xi