Could you possibly redescribe the Problem 3.17b for me? I don't quite understand the requirements of this question. What's the relation between it and the gradient descent algorithm for logistic regression of the textbook?
Quote:
Originally Posted by htlin
The chapter shows that the optimal column vector, subject to the firstorder Taylor's approximation, is the negative gradient. Problem 3.7(d) asks you to consider secondorder Taylor's approximation instead, though.
Hope this helps.
