MATLAB: Using the Neural Network toolbox, why do I get more solutions than I should be getting

fitting toolneural network

I created a neural network using the fitting tool. Inputs were 98×2 whereas Outputs were 98×1. After the network called "net" was created, I tried to simulate it using the command (y1=sim(net,[numbers looking outputs for])). Normally, I should be getting 1 answer for the two input values that I chose. However, for some reason I am getting as many answers as inputs. Any idea what might be causing that?

Thank you

Best Answer

Transpose your data matrices

 [ I N ] = size(Input)
 [ O N ] = size(Output)

Thank you for formally accepting my answer

Greg

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MATLAB: Multiple Nonlinear Regression Equation using Neural Network Toolbox

R = 0.999 doesn't mean much unless you can convince us that you did not over-train an over-fit net:

size(x) = [ I N ] % I = 6, N = ?

size(t) = [ O N ] % O =1, N = ?

How was the data divided? Ntrn, Nval, Ntst = ?

Did you use TRAINBR, TRAINLM or TRAINSCG?

Number of training equations Ntrneq = Ntrn*O = ?

How many nodes in the hidden layer? H = ?

Number of unknown weights and biases Nw = {I+1)*H+(H+1)*O = O + (I+O+1)*H = ?

Number of estimation degrees of freedom = Nw - Ntrneq = ?

What are the normalized mean-square errors for the train, val and test subsets? For example,

ttrn = t(trainInd), etc

NMSEtrn = mse(ttrn -ytrn) / var(ttrn,1)

R2trn = 1 - NMSEtrn

Rtrn = sqrt(R2trn)

is Rtst = 0.999?

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A neural net is trained on known input/target examples. I do not see any way you can estimate the as and bs with a neural net.

Hope this helps.

Thank you for formally accepting my answer

Greg

MATLAB: Problem using NARX NN time series tool

 [ I N ] = size(Input)
 [ O N ] = size(Output)

P.S. posting the code in question generally gets faster answers than trying to explain in words. Ideally, use both

Hope this helps.

Thank you for formally accepting my answer

Greg

Best Answer

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MATLAB: Multiple Nonlinear Regression Equation using Neural Network Toolbox

MATLAB: Problem using NARX NN time series tool

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