Learning a perceptron’s weights means varying the direction of the straight line until all the positive examples are on one side and all the negative ones on the other. In one dimension, the boundary is a point; in two, it’s a straight line; in three, it’s a plane; and in more than three, it’s a hyperplane. It’s hard to visualize things in hyperspace, but the math works just the same way. In n dimensions, we have n inputs and the perceptron has n weights. To decide whether the perceptron fires or not, we multiply each weight by the corresponding input and compare the sum of all of them with
...more
