Unfortunately we can only provide so much help without a reproducible
example. Can you use a dataset that everyone would have access to to
reproduce the problem? Otherwise it is difficult for anyone to help you.
Regards,
Charles
On Tue, Mar 1, 2016 at 12:35 AM, jake88 <youtub...@telus.net> wrote:
> I am new to R and neural networks . So I trained and predicted an elman
> network like so :
>
> require ( RSNNS )
> mydata = read.csv("mydata.csv",header = TRUE)
> mydata.train = mydata[1000:2000,]
> mydata.test = mydata[800:999,]
>
> fit <- elman ( mydata.train[,2:10],mydata.train[,1], size =100
> learnFuncParams =c (0.1) , maxit =1000)
> pred <-predict (fit , mydata.test[,2:10])
>
> So pred contains the predictions .
> The problem I am having is that when I run pred <-predict (fit ,
> mydata.test[1,2:10]) repeatedly , it gives me different results each time .
> Should not the weights and bias be set permanently in the network and give
> the same result everytime ?
>
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