Perceptron Learning Algorithm
I'm trying to program the perceptron example but can't figure out how to assign the sign of the first step.
I drew a line between two points on the xy plane [1,1] in both directions.
Then I randomly generated another 10 points, assigning them +1 if they fell above the line and 1 if they fell below the line. I stored those values in ideal function g.
Then I gave each point a random first guess of +1/1 as my initial function h.
If I start with all the weights as 0, then w*x = 0 for all points.
At that rate, PLA will never converge.
What is my conceptual error?
