i’ve completed putting the quickprop algorithm into my feedforward network and i’m now running some tests on it. it seems that the method i was using in the cascade network of calculating the error on all of the training set and minimizing that does not seem to work as well as simply going through the training set and calculating the error on a single point, then adjusting the weights after each point. this is more similar to the old method i used on feedforward nets in which the weights were adjusted after each point in the training set. a {2, 4, 4, 1} net was able to match the “x” problem after 1000 epochs and get close to the solution in less than 100 using the new method, while the old method was unable to even get close within 1500 epochs. the current file is ffqp3.nb.
on another computer i’ve decided to try this new method on the old cascade network on the spiral problem and see what happens.
