bias and variance of trained neural network

 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

Iniciar sesión para comentar.

Más respuestas (1)

Categorías

Más información sobre Deep Learning Toolbox en Centro de ayuda y File Exchange.

Etiquetas

Preguntada:

el 1 de Dic. de 2013

Comentada:

el 8 de Dic. de 2018

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by