MATLAB: Neural networks, MSE goal

mse goalneural networks

Respected colleague
Would we perhaps be able to explain the term linked to neural networks MSEgoal = 0.01*Ndof*MSE00a/Ntrneq.
This term is quite often seen in training neural networks , but it unfortunately is not completely clear for me.
I need a more detailed explanation of the term , maybe some references, example or just explanations.
Also on this occasion, I wish to thank Mr. Greg Heath for excellent explanations and tutorials . Mr Greg Heath explanations are much better than many that can be found in the available literature . Thank you very much for that .

Best Answer

You could have searched the NEWSGROUP and ANSWERS.
Anyway,
See: WIKIPEDIA: Degrees of Freedom
 Ntrn    = number of training examples
 O       = dimension of target examples
 Ntrneq  = Ntrn*O  number of training equations
 Nw      = number of unknown weights
 Ntrndof = Ntrneq-Nw number of estimation degrees of freedom
REFERENCE: THE NAIVE CONSTANT OUTPUT MODEL
 output = repmat(mean(target,2),1,Ntrn)
 MSE00  = MSE of the naive constant output model
 error  = target - output;
 MSE00  = mean(error.^2)
        = var(target,1)  % biased 
 MSE00a = var(target,0)  % unbiased

% "a" ==> "adjusted" for loss of degrees of freedom
 Unbiased MSEtrn of a NN with Nw weights
 Ntrndof = Ntrn - Nw
 MSEtrn  = SSEtrn/Ntrneq        % biased
 MSEtrna = SSEtrn/Ntrndof       % unbiased
NN training goal
 MSEtrna = MSE00a/100
 SSEtrn  = Ntrndof*MSE00a/100
 MSEtrn  = 0.01*Ntrndof*MSE00a/Ntrneq
Hope this helps.
Thank you for formally accepting my answer
Greg
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