Apologies for the lengthy title.My question is about the weight update rule for logistic regression using stochastic gradient descent.
I have just started experimenting on Logistic Regression.I came across two weight update expressions and did not know which one is more accurate and why they are different.
The first Method:
whereg stands for the logistic functiong' stands for g's derivativew stands for weighthw(x) represents the logistic regression hypothesis
The other method:
Source (Paper authored by Charles Elkan): Logistic Regression and Stochastic Gradient Training.