bias and variance of trained neural network

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Mohamad
Mohamad el 1 de Dic. de 2013
Comentada: Muhammad Adil Raja el 8 de Dic. de 2018
Hello How can we save the bias and variance of a trained network? thank you in advance

Respuesta aceptada

Greg Heath
Greg Heath el 2 de Dic. de 2013
[x,t] = simplefit_dataset;
net = fitnet(4);
rng(0)
[ net tr y e ] = train(net,x,t);
biaserr = mean(e(:))
varerr = var(e(:))
HTH
Thank you for formally accepting my answer
Greg
  2 comentarios
SAM
SAM el 13 de Oct. de 2017
hi Greg, how can I calculate bias and variance if I have mean square error ? or i must have err=Targets-predictions
Muhammad Adil Raja
Muhammad Adil Raja el 8 de Dic. de 2018
Hi Greg, I really like this definition of variance as it is calculated over the error and not on the model output alone. However, is there a reference to back it up? Normally the variance is defined as the variance of the model output, which rather sounds non-sensible to me.
Moreover, how to compute these values if I am using fitnet for MIMO (multiple input or multiple output) problems or while using ensembles?
Best,
MA

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Mohamad
Mohamad el 2 de Dic. de 2013
Greg Thank you very much.

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