Just started experimenting with the java library and aint NN fascinating "creatures" ;)
Some questions occur to me.
Once trained is it possible (or advisable!) to train again with a different dataset, or would it be recommended to start from scratch with the old dataset and the new dataset together...
What is a sensible error target? for example is there any practical advantage to say 0.0005 and 0.005 in terms of the end accuracy of the net
Is there a rule of thumb for layer size and number of layers, for example if I have 144 inputs :o and 26 outputs.....
Sigmoid activation tends to get stuck in valleys (sometimes without escape)
where hyperbolic tangent does't seem to at least with my dataset (5,200 items), is this to be expected or just a peculiarities of my data/network?
(my inputs don't have -tive values)