Multiple input feedforwardnet neural network toolbox
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To whom it may concern;
Although I have spent time on the following problem, I could NOT solved it.
I am trying to approximate a function in the following structure by using feedforwardnet:
where 'x1' and 'x2' are the inputs while 'y' is the output.
For this I have 'x1', 'x2' and 'y' as 1000 element vectors.
It is possible to create a net by using the following code;
newff([-1 1; -1,1],[10 1]) this returns the following net.
However since newff is obsolete I am looking for a way to do the same thing by feedforwardnet.
So could you please show me how to generate the same net by using feedforwardnet?
Greg Heath on 27 May 2015
Specialized functions NEWFIT (regression and curve-fitting) and NEWPR (classification and pattern-recognition) automatically call the generic function NEWFF. All have been obsolete since 2010 but are still available.
The current specialized functions FITNET (regression and curve-fitting) and PATTERNNET (classification and pattern-recognition) automatically call the generic function FEEDFORWARDNET.
Since you have a regression problem, use FITNET. The documentation and a corresponding simple example can be obtained from the documentation commands
More practical examples can be obtained by searching the NEWSGROUP and ANSWERS using
If searching for a good choice of number of hidden nodes
greg fitnet Hmin:dH:Hmax
and/or if searching for a good choice of random initial weights and data division
greg fitnet Ntrials
Hope this helps.
Thank you for formally accepting my answer