Re: Regression then PLA
I'm coming up against this as well. Maybe I have a bug, but I'm finding that even though the regression finds an almost perfect line with, usually, very few points misclassified, I give the weights from the regression to PLA as initial weights and the PLA line bounces all over the place before settling down.
Scaling the regression weights up by a factor of 10 or 100 would speed up the PLA a lot, I think, by preventing the PLA update from moving the weights so much. That would have a similar effect to using a small alpha. But we're not supposed to do either thing, right?
