Hi

I was exploring the AMORE package, to check if I can implement and
train networks with customised architectures. I am basically training a
network
which has 2 inputs, 2 neurons in the hidden layer and 2 output neurons.
I aim to remove the connection between a neuron from the hidden layer and
a neuron in the output layer. I am using the following code :-

#initialising of the network
net.custom <- newff(n.neurons=c(2,2,2),
             learning.rate.global=1e-2,
             momentum.global=0.5,
             error.criterium="LMS",
             Stao=NA, hidden.layer="tansig",
             output.layer="purelin",
             method="ADAPTgdwm")

#Remodeling of the network to remove connection between neuron[1] and neuron
[4]
net.custom$neurons[[1]]$output.links <- c(3)
net.custom$neurons[[1]]$output.aims  <- c(1)

net.custom$neurons[[4]]$weights <- net.sofm$neurons[[4]]$weights[1]
net.custom$neurons[[4]]$input.links <- c(2)
net.custom$neurons[[2]]$output.aims <- c(2,1)

#Initializing matrices for training of the network
P <- matrix(c(c(1,2,3,4),c(1,2,3,4)),nrow = 4, ncol=2)
target <- P #Just to keep things simple for now.


# We train the network according to P and target.
result <- train(net.sofm, P, target, error.criterium="LMS", report=TRUE,
show.step=100, n.shows=5 )

## Running the above line gives me the following error

Error in train.method(net, P, T, show.step) :
  INTEGER() can only be applied to a 'integer', not a 'double'

I was unable to fix the error by using P <- as.interger (martix(....)).
Apart from this
we could not think of any other method to fix this problem.

The sessionInfo is as follows :-
R version 2.10.1 (2009-12-14)
i386-pc-mingw32

locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] AMORE_0.2-12
>
I wonder changing the values of ouput.links, input.links etc is sufficient
for
changing the connections between the neurons. Is there any other
package in R which allows me to design and train neural network.


Thank You

Suyog P


-- 
Masters Student
Department of Chemical and Biological Eng,
University at Buffalo,
Buffalo, NY .
Ph: 801 814 3893

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