Dear neural network experts,
I would like to make a neural network model for a situation
when some of the input variables can interact, while
others don't have any interactions. This information is
based on logical considerations and I have to include it
into the architecture of the net.
For example, I have 3 different groups of input variables.
Within each groups the variables are disjunct (i.e. no
interaction). Variables of different groups may interact.
This would result in either
- restrictions to some weights of a network consisting of
completely inter-linked neurons (i.e. some weights have
to be zero), or
- a combination of neural networks, one for each group of
variables and one combining the groups (nested nets?).
This network needs to be created, trained and simulated.
How can I implement this based on commands of the neural network
toolbox (newff?, trainlm?)?
I would be very happy if you can point me to an example or
similar that demonstrates how the commands have to be used
in this situation.
Many thanks in advance!