MATLAB: Error in NMSE = MSE/MSE00 matrix dimensions don’t match

Deep Learning Toolboxmseneural network

Hi all

In case the target and input have multiple rows , meaning , more than one input and target , calculating the MSE , I get one single number , and for MSE00 , I have a 3 *1 matrix , since I have 8 inputs and 3 Targets

how to solve it ?

Best Answer

Apparently, you used the wrong equation. Both MSE and MSE00 are scalars.

greg MSE00

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Look for my recent NEWSGROUP posts (2015)

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Especially

 8 Jul 2015 OPENLOOP NARNET TUTORIAL EXAMPLE
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Hope this helps.

Thank you for formally accepting my answer

Greg

MATLAB: How to fix minmum mse requirement for neural network training mannually rather using default requirement

 [ I N ] = size(x)
 [ O N ] = size(t)

% Reference MSEs (From Naïve Constant Output Model y00 = mean(ttrn,2))

 Ntrn      = N-2*(0.15*N)       % Default no. of training examples
 MSEtrn00  = mean(var(ttrn',1)) % Biased training target variance (divide by Ntrn)
 MSEtrn00a = mean(var(ttrn',0)  % Degree of freedom "A"djusted (divide by Ntrn-1)

% Number of estimation degrees of freedom (See Wikipedia)

 Ntrneq    = Ntrn*O             % prod(size(ttrn)) is number of training equations
 Nw        = (I+1)*H+(H+1)*O    % Number of unknown weights for an I-H-O node topology
 Ndof      = Ntrneq-Nw          % Not useful when Nw >= Ntrneq
 etrn    = ttrn-ytrn;           % Training error
 MSEtrn  = sse(etrn)/Ntrneq     % Biased MSE
         = mse(etrn)
 MSEtrna = sse(etrn)/Ndof       % DOFA  MSE
         = Ntrneq*MSEtrn/Ndof

% Normalized MSEs

 NMSEtrn  = MSEtrn/MSEtrn00
 NMSEtrna = MSEtrna/MSEtrn00a

% Practical training goal

 NMSEtrna <= 0.01  % Independent of target scaling
 net.trainParam.goal = 0.01*Ndof*MSEtrn00a/Ntrneq