On Dec 18, 3:08 pm, "MOOON MOOON" <shaheed...@yahoo.com> wrote:
> Hello,
>
> Assume I have this matrix, A :
> A=[ 25 11 2010 10 23 75
> 30 11 2010 11 24 45
> 31 12 2010 19 24 44
> 31 12 2010 22 27 32
> 1 1 2011 14 27 27
> 2 12 2011 15 28 30
> 3 12 2011 16 24 42 ];
>
> The first 5 columns represent the inputs of some measured parameters
>
> and the last column is the corresponding output. The number of rows is the number
>
> of taking these measurements.
>
> I want to use Matlab Neural network GRNN with the function newgrnn
>
> ( or any other NN function )
>
> to train the data up to the 5th row and test the remaining 2 rows inputs
>
> to evaluate their corresponding outputs.
>
> I have tried many many times to do this but it always gives me error
>
> and the program did not run correctly.
>
> I have looked to newgrnn help example but it is only for one input
>
> while I have in this example 5 inputs.
>
> My question is how do we put the inputs and the output in the newgrnn
>
> function structure. Actually, I have very large matrix with 22 inputs
>
> and one output and the size of my matrix is 26352 by 23
>
> but the above is only sample example.
>
> Regatds
All of the neural network algorithms have the same format.
For training with N Idimensional input column vectors and
the N corresponding Odimensional target output column vectors
size(p) = [ I N ]
size(t) = [ O N]
Hope this helps.
Greg
