To change the structure of the multi-layer perceptron:
change the values H1, H2 and H3 corresponding to the number of units in
the first second and third hidden layer. If H3 is equal to 0, then only
two hidden layers are created ; if both H3 and H2 are equal to 0 a single
hidden layer is created and if all H1, H2 and H3 are null, no hidden layer
is created, corresponding to a single layer perceptron.
click on the Init button to build the requested structure and initialize
Repeat the same simulation as before. Set a cluster of red points (1.0)
in the center, surrounded by blue points. Which network structure and which
momentum / learning rate combination can solve such a problem ? How does
this perceptron compare with the [0,1] one ?
Define a simple XOR problem and take a network with two hidden neurons
(one hidden layer). Repeat several learning runs with different initial
conditions. How of ten does the network find a solution? How does the performance
compare with that of the [0,1] one?