neural networks, MSE goal

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Miljan Kovacevic
Miljan Kovacevic 2016-8-27
回答： Greg Heath 2016-8-27
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 .

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Greg Heath
Greg Heath 2016-8-27
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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