Re: Perceptron: should w_0 (bias) be updated?
Right, so the obvious solution is to normalize w after the update. This causes w0 to converge along with w1 and w2. I actually implemented this in my solution for the homework submission, but it has an effect on the on number of iterations that are required for a given initial dividing line, depending on how far from the origin it is. In general, after implementing normalization, the number of required iterations required for convergence went up. As a result I got different answers for 7 and 9.
