Create our own target function f and data set D and see how the perceptron learning algorithm works. Take d = 2 so you can visualize the problem, and choose a random line in the plane as your target function, where one side of the line maps to +1 and the other maps to -1. Choose the inputs x, of the data set as random points in the plane, and evaluate the target function on each xn to get the corresponding output yn Now, generate a data set of size 20. Try the perceptron learning algorithm on your data set and see how long it takes to converge and how well the final hypothesis g matches your target f.