Perceptron Learning: Bad

Some not-so-nice features...

• If the error surface is shallow in one or more directions, progress toward the optimal weights can be extremely slow.
• If the learning rate is very small, the speed of convergence will be very slow (big surprise!)
• But, if the learning rate is too high, we can actually get a divergent oscillation in the weights...